papers-we-love_papers-we-love/nautilus.db

SQLite format 3

@  B<00>
B-<2D>
<0F>
<0E><0F><0E>
r<0C>
IV,+

<00>p
<01>?tablelinkslinksCREATE TABLE links
  (id integer primary key,
   paper_id int,
   url varchar unique not null,
   title varchar not null,
   directory varchar not null,
   status int not null,
   created varchar,
   modified varchar))=
indexsqlite_autoindex_links_1links
<0A>|	
<01>Wtablefilesfiles
CREATE TABLE files
  (id integer primary key,
   paper_id int,
   sha1 varchar unique not null,
   filename varchar not null,
   directory varchar not null,
   normalized varchar not null,
   created varchar,
   modified varchar))
=
indexsqlite_autoindex_files_1files<0B>
!!
<01>etabletagspaperstagspapers	CREATE TABLE tagspapers
  (id integer primary key,
   tag_id integer not null,
   paper_id integer not null)a
<01>%tabletagstagsCREATE TABLE tags
  (id integer primary key,
   tag varchar unique not null)';
indexsqlite_autoindex_tags_1tags<08>''
<01>qtableauthorspapersauthorspapersCREATE TABLE authorspapers
  (id integer primary key,
   author_id integer not null,
   paper_id integer not null)<29>0
<01>7tableauthorsauthorsCREATE TABLE authors
  (id integer primary key,
   name varchar unique not null,
   first_name varchar,
   middle_name varchar,
   last_name varchar)-A
indexsqlite_autoindex_authors_1authors<05>\

<01>tablepaperspapersCREATE TABLE papers
  (id integer primary key,
   title varchar unique not null,
   year int,
   abstract varchar,
   venue varchar,
   directory varchar,
   created varchar,
   modified varchar)+?
indexsqlite_autoindex_papers_1papers<00><0C><00><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F>~ytoje`[VQLGB=71+%

<0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E>}wqke_YSMGA;5/)#
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
{
u
o
i
c
]
W
Q
K
E
?
9
3
-
'
!



	
<0C><0C><0C><0C><0C><0C><0C><0C><0C><0C> with Epicc: An Essential Step Towards Holistic Security Analysis<07>Many threats present in smartphones are the result of interactions between application components, not just ar-tifacts of single components. However, current techniques for identifying inter-application communication are ad hoc and do not scale to large numbers of applications. In this paper, we reduce the discovery of inter-component communication (ICC) in smartphones to an instance of the Interprocedural Distributive Environment (IDE) problem, and develop a sound static analysis technique targeted to the Android platform. We apply this analysis to 1,200 applications selected from the Play store and characterize the locations and substance of their ICC. Experiments show that full specifications for ICC can be identified for over 93% of ICC locations for the applications studied. Further the analysis scales well; analysis of each application took on average 113 seconds to complete. Epicc, the resulting tool, finds ICC vulnerabilities with far fewer false positives than the next best tool. In this way, we develop a scalable vehicle to extend current security analysis to entire collections of applications as well as the interfaces they export.android/2017-09-11T23:06:19.5280620122017-09-11T23:06:19.528062012<EFBFBD><00>g<02>=GGFlowDroid: precise context, flow, field, object-sensitive and lifecycle-aware taint analysis for Android apps<07>Today's smartphones are a ubiquitous source of private and confidential data. At the same time, smartphone users are plagued by carelessly programmed apps that leak important data by accident, and by malicious apps that exploit their given privileges to copy such data intentionally. While existing static taint-analysis approaches have the potential of detecting such data leaks ahead of time, all approaches for Android use a number of coarse-grain approximations that can yield high numbers of missed leaks and false alarms.
 In this work we thus present FlowDroid, a novel and highly precise static taint analysis for Android applications. A precise model of Android's lifecycle allows the analysis to properly handle callbacks invoked by the Android framework, while context, flow, field and object-sensitivity allows the analysis to reduce the number of false alarms. Novel on-demand algorithms help FlowDroid maintain high efficiency and precision at the same time.
 We also propose DroidBench, an open test suite for evaluating the effectiveness and accuracy of taint-analysis tools specifically for Android apps. As we show through a set of experiments using SecuriBench Micro, DroidBench, and a set of well-known Android test applications, FlowDroid finds a very high fraction of data leaks while keeping the rate of false positives low. On DroidBench, FlowDroid achieves 93% recall and 86% precision, greatly outperforming the commercial tools IBM AppScan Source and Fortify SCA. FlowDroid successfully finds leaks in a subset of 500 apps from<00><><00><><00><><00><><00><>
<00><><00><>
<00><><00><><00><><00><><00><>{<00><>y<00><>w<00><>u<00><>s<00><>rނq܂mۂiقd؂aׂ`ւ]ԂZӂX҂WтSЂQςO΂M͂ÎG˂DȂBǂ?Ƃ=Ă9Â8‚7<00><>6<00><>4<00><>2<00><>/<00><>+<00><>(<00><>%<00><>"<00><><00><><00><><00><><00><><00><><00><><00><><00><>	<00><><00><>
<00><><00><>}<00><>|<00><>y<00><>u<00><>s<00><>r<00><>n<00><>k<00><>f<00><>d<00><>b<00><>`<00><>^<00><>\<00><>X<00><>U<00><>S<00><>P<00><>L<00><>I<00><>F<00><>D<00><>A<00><>=<00><>;<00><>8<00><>6<>5~<7E>0}<7D>-|<7C>){<7B>#z<>!y<>x<>w<>v<>u<>t<>q<>o<>n<>
l<>k<>j<>
ih|gydvcsbpam]jZgYbX`W\VYUVTSSPQMJJIEHCE?D<C8B4A1@-=)<%;":987654321<0E>^<00><0E>T^<0E><0F>A
<0A>
@
<01>
<EFBFBD><06><0C>
<0A><07><04>
<01>P<08><05>!<0E>I<02><03>@W<03><04>"<07>A<00>{/<0B><06>O	l<0C><00>*<02>D
"
1	D
+	<09>o<08><07> <00><0F><0B>
<0A><05>
<01>
T|~<06>Xx<0B><06>*Y
RRB-Trees: Efficient Immutable VectorsI#K
Immutability Changes EverythingH0e
Mathematical Aspects of Consciousness TheoryG!
NTRU PrimeF"I
New directions in cryptographyE-_
The Moral Character of Cryptographic WorkD9
Acoustic CryptanalysisC3
Crash-Only SoftwareBC
Attacks on the WEP protocolAV<04>/
Simple, Fast, and Practical Non-Blocking and Blocking Concurrent Queue Algorithms@K<04>
A Method for Obtaining Digital Signatures and Public-Key Cryptosystems?E<04>

Time, Clocks, and the Ordering of Events in a Distributed System>0e
Microreboot - A Technique for Cheap Recovery=2i
Experience with Processes and Monitors in Mesa<
Hol;-_
Message Analysis for Concurrent Languages:7s
The semantics of x86-CC multiprocessor machine code9@<04>
Finding race conditions in Erlang with QuickCheck and PULSE8F<04>
Heap architectures for concurrent languages using message passing7V<04>/
Everything you always wanted to know about synchronization but were afraid to ask67s
Panorama weaving: fast and flexible seam processing57s
High-quality single-shot capture of facial geometry4<}
Coupled 3D reconstruction of sparse facial hair and skin3$M
Procedural modeling of buildings29w
Imaging vector fields using line integral convolution15
Instant architecture0N<04>
Shape Grammars and the Generative Specification of Painting and Sculpture/<}
Diminished reality for augmented reality interior design.!
PushPull++-C
Interactive Horizon Mapping,,]
Light Propagation Volumes in Cryengine 3+)
The Redox Code*/
Blue native PAGE.)9
The rendering equation(4m
Web page classification: Features and algorithms'Z<04>7
KinectFusion: real-time 3D reconstruction and interaction using a moving depth camera&/
Deep Colorization%<}
3-Sweep: extracting editable objects from a single photo$"I
Poisson surface reconstruction#0e
Illumination for Computer Generated Pictures")W
Continuous Shading of Curved Surfaces!5o
An improved illumination model for shaded display P<04>#
GigaVoxels: ray-guided streaming for efficient and detailed voxel renderingP<04>#
Digital Video Stabilization and Rolling Shutter Correction using GyroscopesJ<04>
Piranha: A scalable architecture based on single-chip multiprocessing'S
Object Space Silhouette AlgorithimsH<04>
MEXICA: A computer model of a cognitive account of creative writingA<04>
A program optimization for automatic database result caching3k
On the resemblance and containment of documentsJ<04>
On computable numbers with an application to the EntscheidungsproblemP<04>#
2Q: A Low Overhead High Performance Buffer Management Replacement Algorithm'S
A DNA-Based Archival Storage System,]
BIG Cache Abstraction for Cache Networks'S
The chemical basis of morphogenesisB<04>
Molecular computation of solutions to combinatorial problems.A
Interactive topic modeling1g
VEWS: A Wikipedia Vandal Early Warning System/c
Safety Verification of Deep Neural Networks@<04>
The BUDS Language for Distributed Bayesian Machine Learning4m
Evaluating Generative Models for Text Generation+[
The algorithmization of counterfactuals
*Y
Causal Diagrams for Empirical Research"I
A Theory of Inferred CausationG<04>
Mastering the game of Go with deep neural networks and tree search
P<04>#
Architectural Styles and the Design of Network-based Software Architectures	-_
Security Concerns in Android mHealth Apps(U
Computing Machinery and Intelligence8u
Analyzing inter-application communication in AndroidC
Direct and Indirect Effects|<04>{
Analysis of Three Bayesip0e
Illumination for Computer Generated Pictures"<00>Z<04>5Making lockless synchronization fast: performance implications of memory reclamation<00>I	L<04>
K/Axodraw Version 2<00><00>._Programming Languages: History and Future<00>2i
ExpL[<04>9
Don't settle for eventual: scalable causal consistency for wide-area storage with COPST<00>G<04>The Derivative of a Regular Type is its Type of One-Hole Contexts<00>
<0F><00><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F>
<0A>
<0A>
<0A>
o
R
-
<0C><0C><0C>qX0<0B><0B><0B>b-
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
e
7
	<09>	<09>	<09>	<09>	_	>	<08><08><08><08>n@)<07><07><07><07>W0<06><06><06><06>{X5<05><05><05><05>jD)<04><04><04>sT7<03><03><03><03>uR+<02><02><02>vQ2
<01>
<01>
<01>
<01>
e
L
+
<00>!p)
Otmar HilligesOtmarHilligeso
David KimDavidKimn'
Shahram IzadiShahramIzadim
Bin ShengBinSheng!l)
Qingxiong YangQingxiongYangk%
Zezhou ChengZezhouCheng#j+
Daniel Cohen-OrDanielCohen-Ori!
Shi-Min HuShi-MinHuh%
Ariel ShamirArielShamirg
Zhe ZhuZheZhuf
Tao ChenTaoChene%
Hugues HoppeHuguesHoppe#d+
Matthew BolithoMatthewBolitho(c1Michael M. KazhdanMichaelM.Kazhdan"b+Bui Tuong PhongBuiTuongPhonga'
Henri GouraudHenriGouraud!`)
Turner WhittedTurnerWhitted!_)
Elmar EisemannElmarEisemann%^-
Sylvain LefebvreSylvainLefebvre!])
Fabrice NeyretFabriceNeyret\'
Cyril CrassinCyrilCrassin[#
Salim VirjiSalimVirjiZ!
Marc LevoyMarcLevoyY%
Jongmin BaekJongminBaekX%
David JacobsDavidJacobs)W1
Alexandre KarpenkoAlexandreKarpenkoV#
Bruce GoochBruceGoochU%
Elaine CohenElaineCohenT%
Mark HartnerMarkHartner!S)
Ashley HartnerAshleyHartnerR'
Mike SharplesMikeSharples0Q9Rafael Pérez Y PérezRafaelPérez YPérezP'
Adam ChlipalaAdamChlipalaO!
Ziv ScullyZivScully$N-Andrei Z. BroderAndreiZ.BroderM'
Dennis ShashaDennisShasha%L-
Theodore JohnsonTheodoreJohnsonK'
Karin StraussKarinStraussJ%
Georg SeeligGeorgSeeligI
Luis CezeLuisCeze(H1Douglas M. CarmeanDouglasM.Carmean!G)
Randolph LopezRandolphLopez!F)
James BornholtJamesBornholtE!
Gong ZhangGongZhangD
Runhui LiRunhuiLiC%
Zhi-Li ZhangZhi-LiZhang%B-
Arvind NarayananArvindNarayananA%
Eman RamadanEmanRamadan@#L M AdlemanLMAdleman%?-
Brianna SatinoffBriannaSatinoff.>7#Jordan L. Boyd-GraberJordanL.Boyd-Graber=!
Yuening HuYueningHu(<1%V. S. SubrahmanianV.S.Subrahmanian);1
Francesca SpezzanoFrancescaSpezzano:%
Srijan KumarSrijanKumar9
Min WuMinWu8
Sen WangSenWang,75#Marta Z. KwiatkowskaMartaZ.Kwiatkowska6'
Xiaowei HuangXiaoweiHuang!5)
Chris JermaineChrisJermaine*43Luis Leopoldo PerezLuisLeopoldoPerez3#
Shangyu LuoShangyuLuo2%Zekai J. GaoZekaiJ.Gao#1+
Suvrat BhooshanSuvratBhooshan0'
Raunaq RewariRaunaqRewari%/-
Prasad KawthekarPrasadKawthekar.%
Thomas VermaThomasVerma!-)
Demis HassabisDemisHassabis,'
Thore GraepelThoreGraepel'+/
#Koray KavukcuogluKorayKavukcuoglu#*+
Madeleine LeachMadeleineLeach,)5Timothy P. LillicrapTimothyP.Lillicrap!()
Ilya SutskeverIlyaSutskever%'-
%Nal KalchbrennerNalKalchbrenner&
John NhamJohnNham%'
Dominik GreweDominikGrewe#$+
Sander DielemanSanderDieleman#%
Marc LanctotMarcLanctot3";
)Vedavyas PanneershelvamVedavyasPanneershelvam)!1
!Ioannis AntonoglouIoannisAntonoglou- 5
'Julian SchrittwieserJulianSchrittwieser4=George Van Den DriesscheGeorgeVan DenDriessche'
Laurent SifreLaurentSifre#
Arthur GuezArthurGuez&/Chris J. MaddisonChrisJ.Maddison
Aja HuangAjaHuang%
David SilverDavidSilver(1David S. RosenblumDavidS.Rosenblum*3Roy Thomas FieldingRoyThomasFielding#+
Klara NahrstedtKlaraNahrstedt )Carl A. GunterCarlA.Gunter#+
Muhammad NaveedMuhammadNaveed#
Dongjing HeDongjingHe%A. M. TuringA.M.Turing"+David A. WagnerDavidA.Wagner!)
Kate GreenwoodKateGreenwood,5Adrienne Porter FeltAdriennePorterFelt!
Erika ChinErikaChin%-
Rusmin SoetjiptoRusminSoetjipto
#Rose F. LiuRoseF.Liu!
Somesh JhaSomeshJha%-
Patrick McdanielPatrickMcdaniel*
3Patrick D. McdanielPatrickD.Mcdaniel	'
Damien OcteauDamienOcteau'Yves Le TraonYvesLeTraon'
Jacques KleinJacquesKlein%-
Alexandre BartelAlexandreBartel#
Eric BoddenEricBodden#+
Christian FritzChristianFritz+3
Siegfried Rasthofe<00><>M<00><>J<00><>C݈C<00><>B<00><>X<00><>n<00><>m<>^<5E>0R<>G?<3F>Z>p{2<00><0F><0F>2<0F><0F>eG<0F>!tM
<01>
<0A>
<EFBFBD>	<09><07><04><05><06><04>2	<09><08>Hb
<0A><0B><0F>	'Z*<0E>3	i<07><07><06><0C>
9
(<0E>
<EFBFBD>P	<09><08><0F><0E>	<0B><05>
r <05>
<0A><04>
<EFBFBD>
<01>m<06><06><08><06>w<06><0C>
{~<02>
<EFBFBD><05><06>t<03><02><03>
	XG<0F>
<0A>n
`<0E>N<03>o<03><0C>"
<0A>k
<01>3
<EFBFBD><0C><02>
N	I	<09><04>4<0B><08>E<08><05><03>	<09><0B>u
<03><07>B-<04>%#[d<07>1	<09>
<EFBFBD>R<07><02>_<04>
<01>6
<EFBFBD><0E>	9
:<05><02><0B><07>>	<0F>X<0B>c<04><0F>7><08>j!
K\<02>y<0C><0C><02>G<08>JpX
_<05><0B>a
<01>l-^
<EFBFBD>
!Adi Shamir<00>-Ronald L. Rivest<00>)Leslie Lamport<00>#Armando Fox<00>'Greg Friedman<00>'Yuichi Fujiki<00>/Shinichi Kawamoto<00>'George Candea<00>+David D. Redell<00>/Butler W. Lampson<00>!Rob Arthan<00>%Konrad Slind<00>'John Harrison<00>-Richard Carlsson<00>%Jade Alglave<00>-Magnus O. Myreen<00>+Thomas Braibant<00>Tom Ridge<00>#Scott Owens<00>=Francesco Zappa Nardelli<00>%Peter Sewell<00>'Susmit Sarkar<00>%Ulf T. Wiger<00>#Thomas Arts<00>'Hans Svensson<00>#John Hughes<00>1Nicholas Smallbone<00>+Michal H. Palka<00>'Koen Claessen<00>1Jesper Wilhelmsson<00>5Konstantinos Sagonas<00>)Erik Johansson<00>5Vasileios Trigonakis<00>-Rachid Guerraoui<00>#Tudor David<00>-Valerio Pascucci<00>'Julien Tierny<00>#Brian Summa<00>!Bob Sumner<00>+Markus H. Gross<00>-Robert W. Sumner<00>+Steve Marschner<00>/Paul A. Beardsley<00>-Gioacchino Noris<00>%Bernd Bickel<00>%Thabo Beeler<00>%Luc Van Gool<00>'Andreas Ulmer<00>'Simon Haegler<00>1Leith Casey Leedom<00>%Brian Cabral<00>-William Ribarsky<00>5François X. Sillion<00>)Michael Wimmer<00>!James Gips<00>%George Stiny<00>)Sanni Siltanen<00>)Pascal Müller<00>#Peter Wonka<00>#Markus Lipp<00>-Michael F. Cohen<00>3Peter-Pike J. Sloan<00>+Anton Kaplanyan<00>#Helmut Sies<00>'
Dean P. Jones/
Hermann Schägger~-
Hans-Peter Braun}#
Ilka Wittig|+
James T. Kajiya{-
Brian D. Davisonz%
Xiaoguang Qiy5
Andrew W. Fitzgibbonx/
Andrew J. Davisonw)
Dustin Freemanv%
Steve Hodgesu'
Jamie Shottont)
Pushmeet Kohlis3
Richard A. Newcomber+
David Molyneauxq)
Otmar Hilligesp

David Kimo'
Shahram Izadin

Bin Shengm)
Qingxiong Yangl%
Zezhou Chengk+
Daniel Cohen-Orj!
Shi-Min Hui%
Ariel Shamirh
Zhe Zhug
Tao Chenf%
Hugues Hoppee+
Matthew Bolithod1
Michael M. Kazhdanc+
Bui Tuong Phongb'
Henri Gourauda)
Turner Whitted`)
Elmar Eisemann_-
Sylvain Lefebvre^)
Fabrice Neyret]'
Cyril Crassin\#
Salim Virji[!
Marc LevoyZ%
Jongmin BaekY%
David JacobsX1
Alexandre KarpenkoW#
Bruce GoochV%
Elaine CohenU%
Mark HartnerT)
Ashley HartnerS'
Mike SharplesR9
Rafael Pérez Y PérezQ'
Adam ChlipalaP!
Ziv ScullyO-
Andrei Z. BroderN'
Dennis ShashaM-
Theodore JohnsonL'
Karin StraussK%
Georg SeeligJ

Luis CezeI1
Douglas M. CarmeanH)
Randolph LopezG)
James BornholtF!
Gong ZhangE

Runhui LiD%
Zhi-Li ZhangC-
Arvind NarayananB%
Eman RamadanA#
L M Adleman@-
Brianna Satinoff?7
Jordan L. Boyd-Graber>!
Yuening Hu=1
V. S. Subrahmanian<1
Francesca Spezzano;%
Srijan Kumar:

Min Wu9
Sen Wang85
Marta Z. Kwiatkowska7'
Xiaowei Huang6)
Chris Jermaine53
Luis Leopoldo Perez4#
Shangyu Luo3%
Zekai J. Gao2+
Suvrat Bhooshan1'
Raunaq Rewari0-
Prasad Kawthekar/%
Thomas Verma.)
Demis Hassabis-'
Thore Graepel,/
Koray Kavukcuoglu++
Madeleine Leach*5
Timothy P. Lillicrap))
Ilya Sutskever(-
Nal Kalchbrenner'

John Nham&'
Dominik Grewe%+
Sander Dieleman$%
Marc Lanctot#;
Vedavyas Panneershelvam"1
Ioannis Antonoglou!5
Julian Schrittwieser =
George Van Den Driessche'
Laurent Sifre#
Arthur Guez/
Chris J. Maddison

Aja Huang%
David Silver1
David S. Rosenblum3
Roy Thomas Fielding+
Klara Nahrstedt)
Carl A. Gunter+
Muhammad Naveed#
Dongjing He%
A. M. Turing+
David A. Wagner)
Kate Greenwood5
Adrienne Porter Felt!
Erika Chin-
Rusmin Soetjipto#
Rose F. Liu
!
Somesh Jha-
Pf#H. I. SerinG<00>5Robert Bruce Findler5<00>!N. Machida<04>#Erik MeiG%Dhiru Kholia<02>F)Boris Dragovic[<00>)Luis Rodriguez<02><00>)Jacob R. Lorch
<01><00>T. Marmon/<0F><00><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F>zrjc[SKC;3+#<0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E>{skd\UNF>6.&
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
~
v
n
f
^
V
N
F
>
6
.
&



<0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C>~vnf^VNF>6.&<0B><0B><0B><0B><0B><0B><0B><0B><0B><0B><0B><0B><0B><0B>wmcYOE;1'	
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
}
s
i
_
U
K
A
7
-
#


	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	y	o	e	[	Q	G	=	3	)				
<08><08><08><08><08><08><08><08><08><08><08><08>ukaWMC9/%<07><07><07><07><07><07><07><07><07><07><07><07><07>{qg]SI?5+!
<06><06><06><06><06><06><06><06><06><06><06><06><06>wmcYOE;1'	<05><05><05><05><05><05><05><05><05><05><05><05><05>}si_UKA7-#<04><04><04><04><04><04><04><04><04><04><04><04><04>yoe[QG=3)<03><03><03><03><03><03><03><03><03><03><03><03><03>vlbXND:0&<02><02><02><02><07>k

Ji<07>j

Ii<07>i

Hi<07>h

Gi<07>g

Fi<07>f

Ei<07>e

Dh<07>d

Ch<07>c

Bh<07>b

Ah<07>a

9h<07>`

@g<07>_

?g<07>^

>g<07>]

=f<07>\

<f<07>[

;f<07>Z

:f<07>Y

9f<07>X

8f<07>W

7f<07>V

6f<07>U

5f<07>T

4f<07>S

3f<07>R

2f<07>Q
<00>f<07>P

1f<07>O

0e<07>N

/e<06>M

Md<07>L

.d<07>K
<00>d<07>J

-d<07>I

,c<07>H

+c<07>G

*c<07>F

)c<07>E

(c<07>D

'b<07>C

&a<07>B

%a<07>A

$a<07>@

#a<07>?

"a<07>>

!`<07>=

 _<07><

_<07>;

^<07>:

^<07>9

^<07>8

^<07>7

]<07>6

]<07>5

]<07>4

]<07>3

\<07>2

\<07>1

\<07>0

\<07>/

\<07>.

\<07>-

\<07>,

\<07>+

\<07>*


Z<07>)

Z<07>(

Z<07>'


Z<07>&

	Y<07>%

Y<07>$

Y<07>#

X<07>"

X<07>!

X<07> 

X<07>

X<07>


X<07>

X<07>
<00>X<07>
<00>X<07>
<00>X<07>
<00>X<07>
<00>X<07>
<00>X<07>
<00>X<07>
<00>W<07>
<00>W<07>
<00>V<07>
<00>U<07>
<00>U<07>
<00>U<07>
<00>U<07>
<00>U<07>

<00>U<07>
<00>U<07>
<00>T<07>

<00>T<07>	
<00>T<07>
<00>T<07>
<00>S<07>
<00>S<07>
<00>S<07>
<00>S<07>
<00>R<07>
<00>R<07>

<00>R<07>
<00>Q<07>
<00>Q<07>~
<00>O<07>}
<00>O<07>|
<00>N<07>{
<00>N<07>z
<00>N<07>y
<00>N<07>x
<00>N<07>w
<00>N<07>v
<00>M<07>u
<00>M<07>t
<00>M<07>s
<00>M<07>r
<00>M<07>q
<00>M<07>p
<00>M<07>o
<00>M<07>n
<00>M<07>m
<00>M<07>l
<00>M<07>k
<00>L<07>j
<00>K<07>i
<00>K<07>h
<00>K<07>g
<00>J<07>f
<00>J<07>e
<00>I<07>d
<00>I<07>c
<00>H<07>b
<00>G<07>a
<00>F<07>`
<00>F<07>_
<00>F<07>^
<00>F<07>]
<00>E<07>\
<00>E<07>[
<00>D<07>Z
<00>C<07>Y
<00>C<07>X
<00>C<07>W
<00>B<07>V
<00>B<07>U
<00>A<07>T
<00>@<07>S
<00>@<07>R
<00>?<07>Q
<00>?<07>P
<00>?<07>O
<00>><07>N
<00>=<07>M
<00>=<07>L
<00>=<07>K
<00>=<07>J
<00>=<07>I
<00><<07>H
<00><<07>G
<00>;<07>F
<00>;<07>E
<00>;<07>D
<00>:<07>C
<00>:<07>B
<00>:<07>A
<00>9<07>@
<00>9<07>?
<00>9<07>>
<00>9<07>=
<00>9<07><
<00>9<07>;
<00>9<07>:
<00>9<07>9
<00>8<07>8
<00>8<07>7
<00>8<07>6
<00>8<07>5
<00>8<07>4
<00>8<07>3
<00>8<07>2
<00>7<07>1
<00>7<07>0
<00>7<07>/
<00>6<07>.
<00>6<07>-
<00>6<07>,
<00>5<07>+
<00>5<07>*
<00>5<07>)
<00>4<07>(
<00>4<07>'
<00>4<07>&
<00>4<07>%
<00>4<07>$
<00>3<07>#
<00>3<07>"
<00>3<07>!
<00>3<07> 
<00>3<07>
<00>3<07>
<00>3<07>
<00>2<07>
<00>2<07>
<00>2<07>
<00>2<07>
<00>2<07>
<00>1<07>
<00>1<07>
<00>0<07>
<00>0<07>
<00>0<07>
<00>0<07>
<00>/<07>
<00>/<07>
<00>.<07>
<00>-<07>
<00>-<07>

<00>-<07>
<00>,<07>
<00>,<07>

<00>+<07>	
<00>*<06>

*<06>

~)<06>

})<06>

|)<06>

{(<06>

z'<06>

y'<06>


x&<06>

w&

v&~

u&}

t&|

s&{

r&z

q&y

p&x

o&w

n&v

m%u

l%t

k%s

j$r

i$q

h$p

g$o

f$n

e#m

d#l

c#k

b"j

a!i

` h

_g

^f

]e

\d

[c

Zb

Ya

X`

W_

V^

U]

T\

S[

RZ

QY

PX

OW

NV

MU

LT

KS

JR

IQ

HP

GO

FN

EM

DL

CK

BJ

AI

@H

?G

>F

=E

<D

;C

:B

9A

8@

7?

6>

5=

4<

3;

2:

19

08

/7	

6	
5

.4	
3

-
2

,
1

+
0

*
/

)
.

(
-

'
,

&
+

%
*

$
)

#
(

"
'

!
&

 
%


$


#


"


!


 




	

	

















	




















	



	

	







<00><>ZɊ <00><>f`<60>,_<>k<0F><00><0F><0F><0F><0F><0F><0F>sj^L<$<0E><0E><0E><0E><0E><0E><0E><0E>{ogZPB9 
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
t
c
Q
B
6
(
 

<0C><0C><0C><0C><0C><0C><0C><0C>s[K80(
<0B><0B><0B><0B><0B><0B><0B><0B><0B><0B>|tl\PH4(	

<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
}
q
h
\
N
C
7
'


	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	q	b	M	@	/	<08><08><08><08><08><08><08>k\?6+<07><07><07><07><07><07><07><07><07><07><07>q_@7'<06><06><06><06><06><06><06><06><06><06>\L-$<05><05><05><05><05><05><05>{eN6<04><04><04><04><04><04><04><04>ypg\PG:1(<03><03><03><03><03><03>|laOE<0
<02><02><02><02><02><02><02><02><02><02>^TG3'
<01>
<0A>q!hash table<0F>p%immutability<07>orime	<09>nripemd<11>m)future attacks
<EFBFBD>lupgrade<07>kblem<1F>jEdiffie-hellman key agreement<06>idlp
<0A>h!public-key<0B>gknapsack
<0A>f!disclosure<07>etalk	<09>dpuzzle<0F>c%cryptography<10>b'cryptographer	<09>areboot<0C>`expensive<08>_crash<15>^1persistent storage	<09>]uptime<06>\wep<07>[read<0F>Z%plementation<08>Yqueue
<0A>X!concurrent<0F>W%non-blocking<1A>V;public-key cryptosystem<11>U)decryption key<06>Tecc<12>S+electronic mail<11>R)encryption key<14>Q/key cryptosystems<06>Pdsa<14>O/encryption method<06>Ntes<06>Mdes
<EFBFBD>Llogical<06>Kdis	<09>Jcausal<08>Iclock<06>Hpen<06>Grus<07>Ffine<0E>E#microreboot<06>Dbug<15>C1priority inversion<0C>Boperating<08>Ainter<14>@/personal computer<0B>?handling<19>>9concurrent programming
<EFBFBD>=monitor<16><3memory architecture<15>;1garbage collection<14>:/allocation scheme<13>9-machine language<12>8+actual hardware<0F>7%memory model<06>6hol<10>5'correct model	<09>4erlang<15>31concurrent program<0F>2%unit testing<11>1)race condition<08>0pulse<0E>/#concurrency<06>.mcs<1C>-?synchronization primitive
<0A>,!contention$<24>+Operformance and energy efficiency<07>*lock	<09>)mosaic<0B>(panorama<07>'seam
<EFBFBD>&editing	<09>%stereo<06>$dif	<09>#facial<1B>"=reconstruction algorithm<0F>!%skin surface<0B> scanning<07>hair
<0A>!cityengine<06>cga<1C>?line integral convolution<0F>%vector field
<0A>!streamline<06>eld<06>odt
<EFBFBD>grammar<08>split<06>mar	<09>street	<09>facade	<09>carbon<07>nadp<11>)ros production<07>nadh<08>nadph<0B>
radiance<0F>%illumination<08>tance<06>
ray<1A>	;document classification<0C>hypertext<1A>;web page classification<16>3text classification<0B>relevant<07>tsdf<0C>depth map<14>/3d reconstruction<19>
9kinectfusion algorithm<1A>;deep learning technique1reference database~%colorization}cylinder|-simple 3d shapes
{!photographz%single photo
yfittingxpmvwrbfvureu9poisson reconstructiontmvsslightingrbrdfqspecular
pshadingo#reflectancenture	mshadow	lviewerk#ray tracing
jgraphic	ishaderhrendering
grealismfgpus
eoctreesdstreamingcgpubvoxelamate`gyroscope
_shutter^'camera motion]3video stabilization
\writing	[mexicaZcbrY)computer model
Xtension
WminhashV+minwise hashingUlsh
TshingleS#resemblanceRlfuQlirPlrfuOarcNacmM%data storageL'biotechnologyKarchivalJencoding
IblockinH-hamiltonian pathGhppF'dna computing
Egraph g
D!same topicCldaBitmA)topic modeling@#topic model?3vandalism detection>'early warning=edit	<vandal;9comfort and confidence:)counterfactual9-little knowledge8swiftness	7enigma6-bayesian network5causality4dag3sgs2causation
1alphago
0!board game/'reinforcement.%intelligence
-!artificial,soap+=rest architectural style	*cation)api(soa
'mhealth&)sensitive data%hipaa$5security and privacy#judge"bot!los 5machine intelligencecentprivilegedroidcomdroidcde
naturalndedoxmediationdata flow
!smartphone)essential step3market applications7n.a. n.a. pc analysis	intenticc/security analysis3android application
#android app'analysis tool
malware
leak	flowdroidappowslifecycle%bp algorithm+message passing+graphical model%facto<00><>z<00><>'r<>=P<>ZO<>q<0F><0F><00><0F><0F><0F><0F><0F>%
<0A><0F><0B><0B>
u<0C><0F><0B>U<0B>
C<0F>	<09><04>
<EFBFBD><07>
<0A>Q

)h:8(]	0[<0C>
m<05><04>M<05><0C><02><02>	A
<0E><0B><03><08><08>2<06>_H<02><02><0B>@<0E>Q	t<03><0C><06><07><03><0B><03><0C><05><0E><02><07><06><0F>z	<09>t47
<EFBFBD>
i<07>
8<0F>
<EFBFBD><0B><04>
<01>
<0A><05><0B>]
d<0E><04>1<03><08><02>)km<0F>	<09>Au<0C><06>;}I!f_<07><0E>
<EFBFBD>%<0E><05><0F>
<EFBFBD>
<0A><04>)5<06>	<09><0E><07><07>
p|}
r<07><04><0F><06>h]<04>	cP	<09>	<09><04>C<02><03>	<02>b<05>7
(	<09>F
]<02><06>		<09>
R<08>
O]
<0A>(<07>q<06>
<0A>
<0A>
!
D	<09>
Q
<EFBFBD>	N	r<06><0E>
<0A>
<0A>	<09><07><06>
~r<07><0C>.<02>,)<08>L9<08>
	<05>H1	<09><0C>\`
<EFBFBD>

<EFBFBD>l=
<EFBFBD>!hash table<00>%immutability<00>	rime<00>ripemd<00>)future attacks<00>upgrade<00>	blem<00>!Ediffie-hellman key agreement<00>dlp<00>!public-key<00>
knapsack<00>!disclosure<00>	talk<00>puzzle<00>%cryptography<00>'cryptographer<00>reboot<00>expensive<00>
crash<00>1persistent storage<00>uptime<00>wep<00>	read<00>%plementation<00>
queue<00>!concurrent<00>%non-blocking<00>;public-key cryptosystem<00>)decryption key<00>ecc<00>+electronic mail<00>)encryption key<00>/key cryptosystems<00>dsa<00>/encryption method<00>tes<00>des<00>logical<00>dis<00>causal<00>
clock<00>pen<00>rus<00>	fine<00>#microreboot<00>bug<00>1priority inversion<00>operating<00>
inter<00>/personal computer<00>
handling<00>9concurrent programming<00>monitor<00>3memory architecture<00>1garbage collection<00>/allocation scheme<00>-machine language<00>+actual hardware<00>%memory model<00>hol<00>'correct model<00>erlang<00>1concurrent program<00>%unit testing<00>)race condition<00>
pulse<00>#concurrency<00>mcs<00>?synchronization primitive<00>!contention<00>&Operformance and energy efficiency<00>	lock<00>mosaic<00>
panorama<00>	seam<00>editing<00>stereo<00>dif<00>facial<00>=reconstruction algorithm<00>%skin surface<00>
scanning<00>	hair<00>!cityengine<00>cga<00>?line integral convolution<00>%vector field<00>!streamline<00>eld<00>odt<00>grammar<00>
split<00>mar<00>street<00>facade<00>carbon<00>	nadp<00>)ros production<00>	nadh<00>
nadph<00>
radiance<00>%illumination<00>
tance<00>ray<00>;document classification<00>hypertext<00>;web page classification<00>3text classification<00>
relevant<00>	tsdf<00>depth map<00>/3d reconstruction<00>9kinectfusion algorithm<00>;deep learning technique<00>1
reference database%
colorization~
cylinder}-
simple 3d shapes|!
photograph{%
single photoz
fittingy
pmvx
rbfw
urev9
poisson reconstructionu
mvst
lightings
brdfr
specularq
shadingp#
reflectanceo
turen

shadowm

viewerl#
ray tracingk
graphicj

shaderi

renderingh
realismg
gpusf
octreese

streamingd
gpuc	
voxelb
matea

gyroscope`
shutter_'
camera motion^3
video stabilization]
writing\

mexica[
cbrZ)
computer modelY
tensionX
minhashW+
minwise hashingV
lshU
shingleT#
resemblanceS
lfuR
lirQ
lrfuP
arcO
acmN%
data storageM'
biotechnologyL
archivalK
encodingJ
blockinI-
hamiltonian pathH
hppG'
dna computingF
graph gE!
same topicD
ldaC
itmB)
topic modelingA#
topic model@3
vandalism detection?'
early warning>
edit=

vandal<9
comfort and confidence;)
counterfactual:-
little knowledge9

swiftness8

enigma7-
bayesian network6

causality5
dag4
sgs3

causation2
alphago1!
board game0'
reinforcement/%
intelligence.!
artificial-
soap,=
rest architectural style+

cation*
api)
soa(
mhealth')
sensitive data&	
hipaa%5
security and privacy$	
judge#
bot"
los!5
machine intelligence 
cent

privilege	
droid
comdroid
cde
natural
nde
dox

mediation

data flow!
smartphone)
essential step3
market applications7
n.a. n.a. pc analysis

intent
icc/
security analysis3
android application#
android app
'
analysis tool
malware
leak


N Cimplementation osmcs<00><00>
paxos
9M)crash-recovery<03><00>/
security analysisN%global state<03><0F><00><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F>~vnf^VNF>6.&<0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E>~vnf^VNF>6.&
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
~
v
n
f
^
V
N
F
>
6
.
&



<0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C>~vnf^VNF>6.&<0B><0B><0B><0B><0B><0B><0B><0B><0B><0B><0B><0B><0B>}sj`VLB8.$
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
z
p
f
\
R
H
>
4
*
 


	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	w	m	c	Y	O	E	;	2	(			
	<08><08><08><08><08><08><08><08><08><08><08><08>ukaWMC9/%<07><07><07><07><07><07><07><07><07><07><07><07><07>{qg]SI?5+!
<06><06><06><06><06><06><06><06><06><06><06><06><06>wmcYOE;1'	<05><05><05><05><05><05><05><05><05><05><05><05><05>}si_UKA7-#<04><04><04><04><04><04><04><04><04><04><04><04><04>yoe[QG=3)
<03><03><03><03><03><03><03><03><03><03><03><03>ukaWMC9/%<02><02><02><02><07>k

Gc<07>j

Fc<07>i

Eb<07>h

Db<07>g

Cb<07>f

Bb<07>e

Ab<07>d

@b<07>c

?b<07>b

>b<07>a

=b<07>`

<a<07>_

;a<07>^

:a<07>]

9a<07>\

8a<07>[

7_<07>Z

6_<07>Y

_<07>X

5_<07>W

4_<07>V

3^<07>U

2^<07>T

1^<07>S

0^<07>R

^<07>Q

]<07>P

/]<07>O

.]<07>N

-]<07>M

,]<07>L

+\<07>K
<00>\<07>J

*\<07>I

)Z<07>H

(Z<07>G

'Z<07>F

&Z<07>E

%Z<07>D

$Y<07>C

#Y<07>B

"Y<07>A

!Y<07>@

 Y<07>?

X<07>>

X<07>=

X<07><
<00>X<07>;

X<07>:

W<07>9

W<07>8

W<07>7
<00>W<07>6

W<07>5

U<07>4

U<07>3

U<07>2

U<07>1

U<07>0

S<07>/

S<07>.

S<07>-

S<07>,

S<07>+
<00>R<07>*

R<07>)
<00>R<07>(
<00>R<07>'
<00>R<07>&


Q<07>%

Q<07>$

Q<07>#


Q<07>"

	Q<07>!

O<07> 

O<07>
<00>O<07>
<00>O<07>
<00>O<07>

N<07>

N<07>

N<07>

N<07>
<00>N<07>

N<07>


N<07>

N<07>
<00>N<07>
<00>N<07>
<00>M<07>
<00>L<07>
<00>L<07>
<00>L<07>
<00>L<07>

<00>L<07>
<00>K<07>
<00>K<07>

<00>K<07>	
<00>K<07>
<00>K<07>
<00>J<07>
<00>J<07>
<00>J<07>
<00>J<07>
<00>J<07>
<00>H<07>

<00>F<07>
<00>F<07>
<00>F<07>~
<00>F<07>}
<00>F<07>|
<00>E<07>{
<00>E<07>z
<00>E<07>y
<00>E<07>x
<00>E<07>w
<00>D<07>v
<00>D<07>u
<00>D<07>t
<00>D<07>s
<00>D<07>r
<00>B<07>q
<00>B<07>p
<00>B<07>o
<00>B<07>n
<00>B<07>m
<00>A<07>l
<00>@<07>k
<00>@<07>j
<00>@<07>i
<00>@<07>h
<00>@<07>g
<00>?<07>f
<00>?<07>e
<00>?<07>d
<00>?<07>c
<00>?<07>b
<00>?<07>a
<00>?<07>`
<00>?<07>_
<00>?<07>^
<00>?<07>]
<00>><07>\
<00>><07>[
<00>><07>Z
<00>><07>Y
<00>><07>X
<00>=<07>W
<00>=<07>V
<00>=<06>U

v=<07>T
<00>=<07>S
<00><<07>R
<00><<07>Q
<00><<07>P
<00><<07>O
<00><<07>N
<00><<07>M
<00><<07>L
<00><<07>K
<00><<07>J
<00>:<06>I

:<07>H
<00>:<07>G
<00>:<07>F
<00>:<07>E
<00>9<07>D
<00>9<07>C
<00>9<07>B
<00>9<07>A
<00>9<07>@
<00>8<07>?
<00>8<07>>
<00>8<07>=
<00>8<07><
<00>8<07>;
<00>7<06>:

7<07>9
<00>6<07>8
<00>6<07>7
<00>6<07>6
<00>6<07>5
<00>6<07>4
<00>5<07>3
<00>5<07>2
<00>5<07>1
<00>5<07>0
<00>4<07>/
<00>4<07>.
<00>4<07>-
<00>4<07>,
<00>4<07>+
<00>3<07>*
<00>3<07>)
<00>3<07>(
<00>3<07>'
<00>2<07>&
<00>2<07>%
<00>2<07>$
<00>2<07>#
<00>2<07>"
<00>1<07>!
<00>1<07> 
<00>1<07>
<00>1<07>
<00>1<07>
<00>0<07>
<00>0<07>
<00>0<07>
<00>0<07>
<00>0<07>
<00>*<07>
<00>*<07>
<00>*<07>
<00>*<07>
<00>*<07>
<00>(<07>
<00>(<07>
<00>(<06>

r(<07>
<00>(<07>
<00>'<07>

<00>'<07>
<00>'<07>
<00>'<07>

<00>'<07>	
<00>&<07>
<00>&<07>
<00>&<07>
<00>&<06>

c&<07>
<00>%<06>

%<06>

~%<06>


}$<06>

|$

{$~

z$}

y$|

x#{

w#z

v#y

u#x

t#w

s"v

r"u

q"t

p"s

o"r

n q

m p

l o

k n

j m

i l

h k

g j

fi

eh

dg

cf

be

ad

`c

_b

^a

]`

\_

[^

Z]

Y\

X[

WZ

VY

UX

TW

SV

RU

QT

PS

OR

NQ

MP

LO

KN

JM

IL

HK

GJ

FI

EH

DG

CF

BE

AD

@C

?B

>A

=@

<?

;
>

:
=

9
<

8
;

7
:

69

58

47

36

25

1
4

0
3

/
2

.
1

-
0

,	/

+	.

*	-

)	,

(	+

'*

)

&(

%'

$&

#%

"$

!#

 "

!

 

















































	

	






	<00><>$<00><>j\<5C>/[<5B>k<0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F>
<01><00><00>]<5D>+1<>#GG78c295cfd7469cd3d494a48df7bd7748139e0660digital_video_stabilization_and_rolling_shutter_correction_using_gyroscopes.pdfcomputer_graphics/digital video stabilization and rolling shutter correction using gyroscopes2017-09-11T23:06:05.6673129882017-09-11T23:06:05.667312988<EFBFBD>]<5D>#3<>GG30fae8663ffba4f4abca068a9bc8735a590a9bc5A framework for automated generation of questions across formal domains.pdfcomputer_education/a framework for automated generation of questions across formal domains2017-09-11T23:06:05.6346818852017-09-11T23:06:05.634681885<EFBFBD>]<5D>?<3F>GGce8411564f95396b503868217469e2aaf1b996c9mexica-a-computer-model-of-a-cognitive-account-of-creativing-writing.pdfcomputational_creativity/mexica a computer model of a cognitive account of creativing writing2017-09-11T23:06:05.5951909182017-09-11T23:06:05.595190918<EFBFBD>
]<5D>Q{GG83cf2b3372ef98f7fa5caf94aa44e7262ee47519story-of-squeak-a-practical-smalltalk-written-in-itself.pdfcomp_sci_fundamentals_and_history/story of squeak a practical smalltalk written in itself2017-09-11T23:06:05.4806750492017-09-11T23:06:05.480675049<EFBFBD>5]<5D>9Q<39>1EE7edaa9cc255ba8e0938cb563110b204a4f393d60recursive-functions-of-symbolic-expressions-and-their-computation-by-machine-parti.pdfcomp_sci_fundamentals_and_history/recursive functions of symbolic expressions and their computation by machine parti2017-09-11T23:06:05.475392092017-09-11T23:06:05.47539209<EFBFBD>Q	]UQMGG1c1ff93040a96dfe9f1309bfe34a989d5f93bb4fhints-for-computer-system-design.pdfcomp_sci_fundamentals_and_history/hints for computer system design2017-09-11T23:06:05.4713090822017-09-11T23:06:05.471309082<EFBFBD>
]<5D>	Q<>
GGfb2db075fa0230289a4f05caf2127b95fcc9aa9cearly-lisp-history-1956-1959-herbert-stoyan-html-rendering.pdfcomp_sci_fundamentals_and_history/early lisp history 1956 1959 herbert stoyan html rendering2017-09-11T23:06:05.3734951172017-09-11T23:06:05.373495117<EFBFBD>Y		]]QUGG4712e0a50083a6bda848bf4a65fe214f0f6a7069axiomatic-basis-computer-programming.pdfcomp_sci_fundamentals_and_history/axiomatic basis computer programming2017-09-11T23:06:05.3045129392017-09-11T23:06:05.304512939<EFBFBD>q]<5D>
<1D>GG6e39523a0acd9855ff465598253c323f7dfd3cdaa-program-optimization-for-automatic-database-result-caching.pdfcaching/a program optimization for automatic database result caching2017-09-11T23:06:05.2589628912017-09-11T23:06:05.258962891<EFBFBD>]<5D><1D>GG6718cc5cd4e1484990ee79a8c3cffaad6d7271c3a-constant-algorithm-for-implementing-the-lfu-cache-eviction-scheme.pdfcaching/a constant algorithm for implementing the lfu cache eviction scheme2017-09-11T23:06:05.2532370612017-09-11T23:06:05.253237061<EFBFBD>
]<5D>)<1D>!GGd62de5f995164fff50f5ce61c0113f6bc9f042252q-a-low-overhead-high-performance-buffer-management-replacement-algorithm.pdfcaching/2q a low overhead high performance buffer management replacement algorithm2017-09-11T23:06:05.2014589842017-09-11T23:06:05.201458984<EFBFBD>8	]O+GGGe76af50e96b12fc507e73b025fe9da4a99600af9shazam-audio-search-algorithm.pdfaudio_comp_sci/shazam audio search algorithm2017-09-11T23:06:05.1690869142017-09-11T23:06:05.169086914<EFBFBD>h	]+wGG3a05eea36ffdbcf0625d5154a6458e75ca835971an-ethnographic-and-technological-study-of-breakbeats.pdfaudio_comp_sci/an ethnographic and technological study of breakbeats2017-09-11T23:06:04.4569431152017-09-11T23:06:04.456943115<EFBFBD>]<5D>=<3D>GG02cc6a5944d57d2353a55639c7b77336b94f29b6efficient-selectivity-and-backup-operators-in-monte-carlo-tree-search.pdfartificial_intelligence/efficient selectivity and backup operators in monte carlo tree search2017-09-11T23:06:04.4221010742017-09-11T23:06:04.422101074<EFBFBD>S	]a=YGGac14e6bf50d1491043baf1d854727a68f5f3f51d3-bayesian-network-inference-algorithm.pdfartificial_intelligence/3 bayesian network inference algorithm2017-09-11T23:06:04.4156010742017-09-11T23:06:04.415601074<EFBFBD>
	])#!EEbd9e0c2f5aaf68d784862ab361cc1a41fc9b32cdapi-design.pdfapi_design/ap<19>%><00><>/<18><17>w<00>g[M2"<0F><0F><0F><0C><0C>r<0B>YVd
=<0B><02>
<06><03>	<09>
^<02>g<08>M7
<01><00><07>l:<0B>
	<09><05>o
<07>
<EFBFBD>K<06>
<0E><0E><00>u<05>
1<03>
<0A>
<0A>	&)	<09>E<02><03>
<01>
<EFBFBD>P<0F><08><0F>x}
a
<0A><0E>H<05>
<EFBFBD><07> 
4<08><06>
j	S
<01>B<04>?<04>#,]
763d0321ced31b774bd4ba2f9f369c087cbd278eW,]
43c7b3780b5864f99d042392d83ab331f7fddf2aV,]
4bf4acf54bfd2e65b1ed31fe272670a7e276c534U,]
1a0ba12427c68642a4871677b9de7a337356b9f6T,]
f16c6ce0c7eabd4f5896962335879b3932138e52S,]
a2e4dc4b1cce765255e4d15084811da125c564c5R,]
3e375c8d996b8c46c83b9d3f72732d7477e5fd86Q,]
f3050b5586ddfec5da0d719338a6afa8b166985bP,]
c20baa16cb57ff4979569871d15294fa720bbc23O,]
57efc2b9ba2a725af1d66cc43c472d0314190051N,]
bde7543a8b3ce071342dfaea2a14357431d94b82M,]
1e86909765bd5603a152bbd55e511e0586f1b77fL,]
36222f8eb2ccf21ca345e15186cea64506581543K,]
9aa8f3d1df6ff6d266a531432fe9ea0bb56ad3c3J,]
00e3756119a91432622f6982b59ecd24a1340fbeI,]
1551d42b24a5b1e1ead5f0793e807869249ab93eH,]
7d7de228c501ef486534cca1829378eef8ef1081G,]
28142adcd8a406110c76dbb8e324dc211f3944d1F,]
9d2c1271f1219522d13f150c2b04123bef300dd9E,]
50158bc1a8a67295ab7bce0550886a9859000dc2D,]
49ed15db181c74c7067ec01800fb5392411c868cC,]
368427e6e351d1ac0ef97e824968ed15d0dc3d4dB,]
f52e7afce70597024c3be7df105185dd59a2c8e6A,]
fd443b2ce70c48202ba26cbc6caa471ae262e270@,]
003d5a65de0ac72daaf105ded903cb3eb88585b3?,]
11ff11e3aedaa41a67bea3623e5d2a805db6166e>,]
d65e79756ac6817d4780286045a35d34aaaaf836=,]
76c0579c23504531220601029d455dca6413b628<,]
4e63eed9e709b6c8e20a4a68300883898c7d8f37;,]
daf38d927e2b21c885efdb4b2cc46a2d9f47d679:,]
76eea8436996c7e9c8f7ad3dac34a12865edab249,]
892b955b6fb175c92f3f294ab431f97a8827748d8,]
17007f5e69efcfeff03853a33121943e2b4df4227,]
24cece61e2128780072bc58f90b8ba47f624bc276,]
f06554b06ac49f129086c8889690faaa761398bb5,]
59b3e2060ef7108c9170975219aae410f52ba0b84,]
208aee805004d575035284b1c232209e9fa26b0e3,]
3b2c76827fb4ad1b2da0d0870441e77a27ee37de2,]
177f9ad15ae9420c5c22f20da9a7c8e8dad4f32d1,]
451da9c5558de4c75f01582292063a7c980292080,]
e51582689653f238029d984cd1780c93ef672771/,]
50c42217e3c5b52eb1732f4193bf452dcc0de71b.,]
0db38d32069f3341d34c35085dc009a85ba13c13-,]
8de2fdb04edce612738eb51e14ecc426381f8ed8,,]
0f278cf94ac0d7fe15a7c4e0f283446e9fc07474+,]
eecf3aaa6aadf48778bb1daa6b09d011632b9f55*,]
b8645fcfdf5af5759dc20ae769b96be510bdff1a),]
39ac2e0fc4ec63753306f99e71e0f38133e58ead(,]
87fbf4fa017a90b5ff819bcfca17fb52d6f6a790',]
f1948a2d5dc8745f725e3ba0b24e14847778cb19&,]
4cb33680dda1fa1f0bad1ca52e07a8a34a500104%,]
8b1d8d46836a6d5eb4355315b64d85c128cbff27$,]
29f3f5918946bf0a4d75bf5244f993847d03e26c#,]
07d847f310d5fa9138f461f0a25c5e0024f1c4af",]
e95ecb39639ce118c7ddd5bd7892378eacdd105f!,]
cb4710f77feed90ae01b332c492853a5b20e2c7d ,]
a2e89c6111f3e306c56472306795af290ffb29af,]
57d70e73a995be26f01ae51f321fdaf42a089bf8,]
e2e60f19214efaa7d842b4a3b3b322964bf78dc7,]
973f17392cb7b417271e9d482d17a44a8c70c70a,]
f5222809526d8a419a1752547880ba0a9013a8ca,]
4fc240d0d9e690cb9b0bcb2f8a5e5ca918b01410,]
1cdc911f5a1b7a770b2e27bf4ebfae04c003a616,]
11825521850926501e3f353ffb7cf14b0c389320,]
4b1ed99c65d500d4a610813736169851cb496810,]
fe0ae75e97abe2686e6bc8cbe94bfd08934e36da,]
a9d9352d43986d4a5a3554a84b99580225ec00cf,]
c5cf25551312490d3f3f3a6b62c5c3492b63f1f1,]
0ec3651f70a50c371a1f9502fc7d3eab272d5cff,]
0f007df1707d77a72237248b0d7fd93b37fc9db7,]
6125b966172dd6cde3563f2ae10d8f782d14e1de,]
78c295cfd7469cd3d494a48df7bd7748139e0660,]
30fae8663ffba4f4abca068a9bc8735a590a9bc5,]
ce8411564f95396b503868217469e2aaf1b996c9,]
83cf2b3372ef98f7fa5caf94aa44e7262ee47519
,]
7edaa9cc255ba8e0938cb563110b204a4f393d60,]
1c1ff93040a96dfe9f1309bfe34a989d5f93bb4f,]
fb2db075fa0230289a4f05caf2127b95fcc9aa9c
,]
4712e0a50083a6bda848bf4a65fe214f0f6a7069	,]
6e39523a0acd9855ff465598253c323f7dfd3cda,]
6718cc5cd4e1484990ee79a8c3cffaad6d7271c3,]
d62de5f995164fff50f5ce61c0113f6bc9f04225,]
e76af50e96b12fc507e73b025fe9da4a99600af9,]
3a05eea36ffdbcf0625d5154a6458e75ca835971,]
02cc6a5944d57d2353a55639c7b77336,]
c5cf25551312490d3f3f3a6b62c5c3492b63f1f1,]
5b0ccfcd8135c9599f8088443ed7de1874fa1c97k<0F><00><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><00>S<00><17>'GGhttp://www.cs.duke.edu/courses/cps296.4/spring04/papers/Adleman94.pdfMolecular Computation of Solutions to Combinatorial Problemsbiocomputing/2017-09-11T23:06:15.2661479492017-09-11T23:06:15.266147949y	M'GGhttp://en.wikipedia.org/wiki/Pcrwikipediabiocomputing/2017-09-11T23:06:15.2661479492017-09-11T23:06:15.266147949<EFBFBD>E
a<>+GGhttps://github.com/ibab/tensorflow-wavenet[Python] Implementation with the TensorFlow Machine Intelligence libraryaudio_comp_sci/2017-09-11T23:06:15.2434069822017-09-11T23:06:15.243406982<EFBFBD>6
W<>	+GGhttps://github.com/basveeling/wavenet[Python] Implementation with the Keras Neural Networks libraryaudio_comp_sci/2017-09-11T23:06:15.2434069822017-09-11T23:06:15.243406982<EFBFBD>5
<00>W+GGhttps://deepmind.com/blog/wavenet-generative-model-raw-audio/Announcement and interactive examplesaudio_comp_sci/2017-09-11T23:06:15.2434069822017-09-11T23:06:15.243406982<EFBFBD>	U_+GGhttps://arxiv.org/pdf/1609.03499.pdfWaveNet: A Generative Model for Raw Audioaudio_comp_sci/2017-09-11T23:06:15.2434069822017-09-11T23:06:15.243406982<EFBFBD>:
	e[UGGhttp://ftp.cs.ucla.edu/pub/stat_ser/r360.pdfThe algorithmization of counterfactualsartificial_intelligence/judea_pearl/2017-09-11T23:06:15.2420400392017-09-11T23:06:15.242040039<EFBFBD>=	mYUGGhttp://ftp.cs.ucla.edu/pub/stat_ser/R218-B-L.pdfCausal diagrams for empirical researchartificial_intelligence/judea_pearl/2017-09-11T23:06:15.2420400392017-09-11T23:06:15.242040039<EFBFBD>9	uIUGGhttp://ftp.cs.ucla.edu/pub/stat_ser/r156-reprint.pdfA theory of inferred causationartificial_intelligence/judea_pearl/2017-09-11T23:06:15.2420400392017-09-11T23:06:15.242040039<EFBFBD>[

c<>UGGhttp://ftp.cs.ucla.edu/pub/stat_ser/r30.pdfReverend Bayes on inference engines: A distributed hierarchical approachartificial_intelligence/judea_pearl/2017-09-11T23:06:15.2420400392017-09-11T23:06:15.242040039<EFBFBD>i	<00>!<21>=GGhttp://airesearch.com/wp-content/uploads/2016/01/deepmind-mastering-go.pdfMastering the Game of Go with Deep Neural Networks and Tree Searchartificial_intelligence/2017-09-11T23:06:15.2211870122017-09-11T23:06:15.221187012<EFBFBD>	W#=GGhttp://bayes.cs.ucla.edu/jp_home.htmlJudea Pearlartificial_intelligence/2017-09-11T23:06:15.2211870122017-09-11T23:06:15.221187012<EFBFBD>5	yU=GGhttp://www.csee.umbc.edu/courses/471/papers/turing.pdfComputing Machinery and Intelligenceartificial_intelligence/2017-09-11T23:06:15.2211870122017-09-11T23:06:15.221187012<EFBFBD>S<00><0B>{=GGhttps://github.com/papers-we-love/papers-we-love/blob/master/artificial_intelligence/3-bayesian-network-inference-algorithm.pdfAnalysis of Three Bayesian Network Inference Algorithms: Variable Elimination, Likelihood Weighting, and Gibbs Samplingartificial_intelligence/2017-09-11T23:06:15.2211870122017-09-11T23:06:15.221187012<EFBFBD><00>'<27>Q#GGhttps://www.ics.uci.edu/~fielding/pubs/dissertation/fielding_dissertation.pdfArchitectural Styles and the Design of Network-based Software Architectures (REST) by Roy Fieldingapi_design/2017-09-11T23:06:15.1943510742017-09-11T23:06:15.194351074<EFBFBD>f
g<>gGGhttp://www.bodden.de/pubs/far+14flowdroid.pdfFlowDroid: Precise Context, Flow, Field, Object-sensitive and Lifecycle-aware Taint Analysis for Android Appsandroid/2017-09-11T23:06:15.1916579592017-09-11T23:06:15.191657959<EFBFBD>{
u<>GGhttp://www.cse.psu.edu/~duo114/pubs/octeau-sec13.pdfEffective Inter-Component Communication Mapping in Android with Epicc: An Essential Step Towards Holistic Security Analysisandroid/2017-09-11T23:06:15.1916579592017-09-11T23:06:15.191657959<EFBFBD>?
<00>uGGhttps://www.eecs.berkeley.edu/~daw/papers/intents-mobisys11.pdfAnalyzing Inter-Application Communication in Androidandroid/2017-09-11T23:06:15.1916579592017-09-11T23:06:15.191657959<EFBFBD>M

<00>+qGGhttp://blog.sei.cmu.edu/post.cfm/secure-coding-tools-analyzing-android-apps-118Two Secure Coding To/<2F>"-<2D>s&<26>.<2E><00><>|,<2C>e*<2A>Ue<>C)<29>4'<27>"%<25>#t"c!O:&Y0<0F><0F>5<0E>Y<0C>

><0C>	o<06><07><06>[N<03>u<04>
<01>
<01><00><08><0E><03>j4<05><04>.
<0A>
Z<00>%<02><02>Z<00>	
vh3	<0B>.#
>
<EFBFBD>W	1g<0E>6q
http://sigops.org/sosp/sosp13/papers/p33-david.pdf95o
http://www.sci.utah.edu/~bsumma/projects/weaving/8_<04>A
http://www.disneyresearch.com/project/high-quality-single-shot-capture-of-facial-geometry/7d<04>K
http://www.disneyresearch.com/project/coupled-3d-reconstruction-of-sparse-facial-hair-and-skin/6=
http://shapegrammar.org/53k
http://shapegrammar.org/ifip/SGBestPapers72.pdf4=
http://cs.brown.edu/courses/csci2370/2000/1999/cabral.pdf3F<04>
http://peterwonka.net/Publications/pdfs/2014.SG.Lipp.PushPull.pdf2[<04>9
http://www.peterwonka.net/Publications/pdfs/2003.SG.Wonka.InstantArchitecture.high.pdf1h<04>S
http://www.peterwonka.net/Publications/pdfs/2006.SG.Mueller.ProceduralModelingOfBuildings.final.pdf0Q<04>%
http://www.proun-game.com/Oogst3D/CODING/InteriorMapping/InteriorMapping.pdf/?<04>

http://research.microsoft.com/en-us/um/people/cohen/bs.pdf.A<04>
http://www.crytek.com/download/Light_Propagation_Volumes.pdf-9w
https://github.com/luanfujun/deep-photo-styletransfer,(U
https://arxiv.org/pdf/1703.07511.pdf+X<04>3
http://www.cs.tau.ac.il/~dcor/articles/2013/3-Sweep-Extracting-Editable-Objects.pdf*I<04>
http://research.microsoft.com/pubs/155416/kinectfusion-uist-comp.pdf)@<04>
http://www.cs.jhu.edu/~misha/Code/PoissonRecon/Version5.71/(I<04>
http://research.microsoft.com/en-us/um/people/hoppe/poissonrecon.pdf'S<04>)
http://www.cs.rpi.edu/~cutler/classes/advancedgraphics/S08/lectures/kajiya.pdf&G<04>
http://www.cs.northwestern.edu/~ago820/cs395/Papers/Phong_1975.pdf%c<04>I
http://page.mi.fu-berlin.de/block/htw-lehre/wise2015_2016/bel_und_rend/skripte/gouraud1971.pdf$A
http://gigavoxels.imag.fr/#6q
http://maverick.inria.fr/Publications/2009/CNLE09/"A<04>
http://maverick.inria.fr/Publications/2009/CNLE09/CNLE09.pdf!K<04>
https://www.cs.drexel.edu/~david/Classes/CS586/Papers/p343-whitted.pdf H<04>
http://graphics.stanford.edu/papers/stabilization/karpenko_gyro.pdf.a
http://barroso.org/publications/isca00.pdfz<04>w
https://www.researchgate.net/publication/220080099_MEXICA_A_computer_model_of_a_cognitive_account_of_creative_writingi<04>U
http://www.ams.org/journals/tran/1965-117-00/S0002-9947-1965-0170805-7/S0002-9947-1965-0170805-7.pdf0e
http://www.turingarchive.org/browse.php/B/12=
https://www.cs.virginia.edu/~robins/Turing_Paper_1936.pdf\<04>;
http://gatekeeper.dec.com/ftp/pub/dec/SRC/publications/broder/positano-final-wpnums.pdfF<04>
http://adam.chlipala.net/papers/SqlcachePOPL17/SqlcachePOPL17.pdf*Y
http://www.vldb.org/conf/1994/P439.PDF<17><04>%
https://github.com/papers-we-love/papers-we-love/blob/master/caching/a-constant-algorithm-for-implementing-the-lfu-cache-eviction-scheme.pdfS<04>)
https://homes.cs.washington.edu/~luisceze/publications/dnastorage-asplos16.pdfD<04>
http://www.dna.caltech.edu/courses/cs191/paperscs191/turing.pdfJ<04>
http://www.cs.duke.edu/courses/cps296.4/spring04/papers/Adleman94.pdf$M
http://en.wikipedia.org/wiki/Pcr.a
https://github.com/ibab/tensorflow-wavenet)W
https://github.com/basveeling/wavenetB<04>
https://deepmind.com/blog/wavenet-generative-model-raw-audio/(U
https://arxiv.org/pdf/1609.03499.pdf0e
http://ftp.cs.ucla.edu/pub/stat_ser/r360.pdf
4m
http://ftp.cs.ucla.edu/pub/stat_ser/R218-B-L.pdf8u
http://ftp.cs.ucla.edu/pub/stat_ser/r156-reprint.pdf/c
http://ftp.cs.ucla.edu/pub/stat_ser/r30.pdf
O<04>!
http://airesearch.com/wp-content/uploads/2016/01/deepmind-mastering-go.pdf	)W
http://bayes.cs.ucla.edu/jp_home.html:y
http://www.csee.umbc.edu/courses/471/papers/turing.pdf<07><04>
https://github.com/papers-(<04>https://githu+<2B><04>
https://github.com/papers-we-love/papers-we-love/blob/master/sublinear_algorithms/1985-Flajolet-Probabilistic-counting.pdf
(Q<04>%
http://www.proun-game.com/Oogst3D/CODING/InteriorMapping/InteriorMapping.pdf/$X<04>3
http://www.cs.tau.ac.il/~dcor/articles/2013/3-Sweep-Extracting-Editable-Objects.pdf* F<04>
http://research.microsoft.com/pubs/80693/vl2-sigcomm09-final.pdf<00>A
http://gigavoxels.imag.fr/#
<00>o<0E>
<0C><0B>
<EFBFBD>	<09><08><07><06><04><03><02><00>
<01><00>]<5D>#3<>GG
30fae8663ffba4f4abca068a9bc8735a590a9bc5A framework for automated generation of questions across formal domains.pdfcomputer_education/a framework for automated generation of questions across formal domains2017-09-11T23:06:05.6346818852017-09-11T23:06:05.634681885<EFBFBD>
]<5D>+1<>#GG78c295cfd7469cd3d494a48df7bd7748139e0660digital_video_stabilization_and_rolling_shutter_correction_using_gyroscopes.pdfcomputer_graphics/digital video stabilization and rolling shutter correction using gyroscopes2017-09-11T23:06:05.6673129882017-09-11T23:06:05.667312988<EFBFBD>
]<5D>?<3F>GGce8411564f95396b503868217469e2aaf1b996c9mexica-a-computer-model-of-a-cognitive-account-of-creativing-writing.pdfcomputational_creativity/mexica a computer model of a cognitive account of creativing writing2017-09-11T23:06:05.5951909182017-09-11T23:06:05.595190918<EFBFBD>
]<5D>Q{GG
83cf2b3372ef98f7fa5caf94aa44e7262ee47519story-of-squeak-a-practical-smalltalk-written-in-itself.pdfcomp_sci_fundamentals_and_history/story of squeak a practical smalltalk written in itself2017-09-11T23:06:05.4806750492017-09-11T23:06:05.480675049<EFBFBD>7]<5D>9Q<39>1EE
7edaa9cc255ba8e0938cb563110b204a4f393d60recursive-functions-of-symbolic-expressions-and-their-computation-by-machine-parti.pdfcomp_sci_fundamentals_and_history/recursive functions of symbolic expressions and their computation by machine parti2017-09-11T23:06:05.475392092017-09-11T23:06:05.47539209<EFBFBD>S	]UQMGG
1c1ff93040a96dfe9f1309bfe34a989d5f93bb4fhints-for-computer-system-design.pdfcomp_sci_fundamentals_and_history/hints for computer system design2017-09-11T23:06:05.4713090822017-09-11T23:06:05.471309082<EFBFBD>	
]<5D>	Q<>
GG
fb2db075fa0230289a4f05caf2127b95fcc9aa9cearly-lisp-history-1956-1959-herbert-stoyan-html-rendering.pdfcomp_sci_fundamentals_and_history/early lisp history 1956 1959 herbert stoyan html rendering2017-09-11T23:06:05.3734951172017-09-11T23:06:05.373495117<EFBFBD>[		]]QUGG
4712e0a50083a6bda848bf4a65fe214f0f6a7069axiomatic-basis-computer-programming.pdfcomp_sci_fundamentals_and_history/axiomatic basis computer programming2017-09-11T23:06:05.3045129392017-09-11T23:06:05.304512939<EFBFBD>r
]<5D>
<1D>GG6e39523a0acd9855ff465598253c323f7dfd3cdaa-program-optimization-for-automatic-database-result-caching.pdfcaching/a program optimization for automatic database result caching2017-09-11T23:06:05.2589628912017-09-11T23:06:05.258962891<EFBFBD>
]<5D><1D>GG
6718cc5cd4e1484990ee79a8c3cffaad6d7271c3a-constant-algorithm-for-implementing-the-lfu-cache-eviction-scheme.pdfcaching/a constant algorithm for implementing the lfu cache eviction scheme2017-09-11T23:06:05.2532370612017-09-11T23:06:05.253237061<EFBFBD>
]<5D>)<1D>!GGd62de5f995164fff50f5ce61c0113f6bc9f042252q-a-low-overhead-high-performance-buffer-management-replacement-algorithm.pdfcaching/2q a low overhead high performance buffer management replacement algorithm2017-09-11T23:06:05.2014589842017-09-11T23:06:05.201458984<EFBFBD>:	]O+GGG
e76af50e96b12fc507e73b025fe9da4a99600af9shazam-audio-search-algorithm.pdfaudio_comp_sci/shazam audio search algorithm2017-09-11T23:06:05.1690869142017-09-11T23:06:05.169086914<EFBFBD>j	]+wGG
3a05eea36ffdbcf0625d5154a6458e75ca835971an-ethnographic-and-technological-study-of-breakbeats.pdfaudio_comp_sci/an ethnographic and technological study of breakbeats2017-09-11T23:06:04.4569431152017-09-11T23:06:04.456943115<EFBFBD>]<5D>=<3D>GG
02cc6a5944d57d2353a55639c7b77336b94f29b6efficient-selectivity-and-backup-operators-in-monte-carlo-tree-search.pdfartificial_intelligence/efficient selectivity and backup operators in monte carlo tree search2017-09-11T23:06:04.4221010742017-09-11T23:06:04.422101074<EFBFBD>U	]a=YGG
ac14e6bf50d1491043baf1d854727a68f5f3f51d3-bayesian-network-inference-algorithm.pdfartificial_intelligence/3 bayesian network inference algorithm2017-09-11T23:06:04.4156010742017-09-11T23:06:04.415601074<EFBFBD>
	])#!EE
bd9e0c2f5aaf68d784862ab361cc1a41fc9b32cdapi-design.pdfapi_design/api design2017-09-11T23:06:04.390895022017-09-11T23:06:04.39089502

<01>x
<0A>
p{
b	<09>	w<07>#1]<04><03><02>
<01><00><00>#]<5D>5#<23>-GG
,29f3f5918946bf0a4d75bf5244f993847d03e26cnetwork-challenges-of-data-recovery-in-erasure-coded-distributed-storage-systems.pdfdatastores/network challenges of data recovery in erasure coded distributed storage systems2017-09-11T23:06:07.3144809572017-09-11T23:06:07.314480957<EFBFBD>"]<5D>1#<23>)GG
)07d847f310d5fa9138f461f0a25c5e0024f1c4afmegastore-providing-scalable-highly-available-storage-for-interactive-services.pdfdatastores/megastore providing scalable highly available storage for interactive services2017-09-11T23:06:07.2573869632017-09-11T23:06:07.257386963<EFBFBD>~!]<5D>#<23>
GG
'e95ecb39639ce118c7ddd5bd7892378eacdd105ffreenet-a-distributed-anonymous-information-and-retrieval-system.pdfdatastores/freenet a distributed anonymous information and retrieval system2017-09-11T23:06:07.2520090332017-09-11T23:06:07.252009033<EFBFBD>* 	]C#;GG
&cb4710f77feed90ae01b332c492853a5b20e2c7dflat-datacenter-storage.pdfdatastores/flat datacenter storage2017-09-11T23:06:07.2170839842017-09-11T23:06:07.217083984<EFBFBD>Z	]s#kGG
%a2e89c6111f3e306c56472306795af290ffb29afdynamo-amazons-highly-available-key-value-store.pdfdatastores/dynamo amazons highly available key value store2017-09-11T23:06:07.1755410162017-09-11T23:06:07.175541016<EFBFBD>Q	]k#aGG
"57d70e73a995be26f01ae51f321fdaf42a089bf8database-metatheory--asking-the-big-queries.pdfdatastores/database metatheory asking the big queries2017-09-11T23:06:07.1400959472017-09-11T23:06:07.140095947<EFBFBD>o
]<5D>#GG
$e2e60f19214efaa7d842b4a3b3b322964bf78dc7bigtable-a-distributed-storage-system-for-structured-data.pdfdatastores/bigtable a distributed storage system for structured data2017-09-11T23:06:07.0712219242017-09-11T23:06:07.071221924<EFBFBD>3	]G-?GG
#973f17392cb7b417271e9d482d17a44a8c70c70alevel-ancestor-simplified.pdfdata_structures/level ancestor simplified2017-09-11T23:06:07.0427290042017-09-11T23:06:07.042729004<EFBFBD>	]/-'GG
 f5222809526d8a419a1752547880ba0a9013a8calca-revisited.pdfdata_structures/lca revisited2017-09-11T23:06:07.0380878912017-09-11T23:06:07.038087891<EFBFBD>!	]5--GG
4fc240d0d9e690cb9b0bcb2f8a5e5ca918b01410ideal-hash-trees.pdfdata_structures/ideal hash trees2017-09-11T23:06:07.0322880862017-09-11T23:06:07.032288086<EFBFBD>1	]E-=GG<00>1cdc911f5a1b7a770b2e27bf4ebfae04c003a616epidemic-broadcast-trees.pdfdata_structures/epidemic broadcast trees2017-09-11T23:06:06.9530539552017-09-11T23:06:06.953053955<EFBFBD>	]''GG
11825521850926501e3f353ffb7cf14b0c389320tidy_data.pdfdata_science/tidy data2017-09-11T23:06:06.8811560062017-09-11T23:06:06.881156006<EFBFBD>]<5D>'/<2F>GG
4b1ed99c65d500d4a610813736169851cb496810a-comprehensive-study-of-convergent-and-communative-replicated-data-types.pdfdata_replication/a comprehensive study of convergent and communative replicated data types2017-09-11T23:06:06.6977900392017-09-11T23:06:06.697790039<EFBFBD>r
]<5D>	%<25>
GGPfe0ae75e97abe2686e6bc8cbe94bfd08934e36daa-new-approach-to-linear-filtering-and-prediction-problems.pdfdata_fusion/a new approach to linear filtering and prediction problems2017-09-11T23:06:06.6447390142017-09-11T23:06:06.644739014<EFBFBD>"	]5/-GG
!a9d9352d43986d4a5a3554a84b99580225ec00cfdata-compression.pdfdata_compression/data compression2017-09-11T23:06:06.5855659182017-09-11T23:06:06.585565918<EFBFBD>	
])'!GGFc5cf25551312490d3f3f3a6b62c5c3492b63f1f1ntru-prime.pdfcryptography/ntru prime2017-09-11T23:06:06.5104699712017-09-11T23:06:06.510469971<EFBFBD>L	]c'[GG
0ec3651f70a50c371a1f9502fc7d3eab272d5cffcommunication-theory-of-secrecy-systems.pdfcryptography/communication theory of secrecy systems2017-09-11T23:06:06.4779880372017-09-11T23:06:06.477988037<EFBFBD>	
])1!GG-0f007df1707d77a72237248b0d7fd93b37fc9db7pushpull++.pdfcomputer_graphics/pushpull++2017-09-11T23:06:06.0258610842017-09-11T23:06:06.025861084<EFBFBD>l	
]1wGG16125b966172dd6cde3563f2ae10d8f782d14e1deimaging_vector_fields_using_line_integral_convolution.pdfcomputer_graphics/imaging vector fields using line integral convolution2017-09-11T23:06:05.8729819342017-09-11T23:06:05.872981934

$-g<0E>

S<0B>
<EFBFBD>	<09>	3<08>t<06>-<02><04>
$
$<00>t0
]<5D>5}EE
8451da9c5558de4c75f01582292063a7c98029208a-hundred-impossibility-proofs-for-distributed-computing.pdfdistributed_systems/a hundred impossibility proofs for distributed computing2017-09-11T23:06:07.682752932017-09-11T23:06:07.68275293<05>
~]<5D>?5<>7GGf06554b06ac49f129086c8889690faaa761398bbbeehive-lookup-performance-for-power-law-query-distributions-in-peer-to-peer-overlays.pdfdistributed_systems/beehive lookup performance for power law query distributions in peer to peer overlays2017-09-11T23:06:07.8799250492017-09-11T23:06:07.8799250492]<5D>75<37>/GG59b3e2060ef7108c9170975219aae410f52ba0b8a-versatile-scheme-for<6F>B1	
]S5KGGr177f9ad15ae9420c5c22f20da9a7c8e8dad4f32da-note-on-distributed-computing.pdfdistributed_systems/a note on distributed computing2017-09-11T23:06:07.8596940922017-09-11T23:06:07.859694092<EFBFBD>#]<5D>5#<23>-GG
,29f3f5918946bf0a4d75bf5244f993847d03e26cnetwork-challenges-of-data-recovery-in-erasure-coded-distributed-storage-systems.pdfdatastores/network challenges of data recovery in erasure coded distributed storage systems2017-09-11T23:06:07.3144809572017-09-11T23:06:07.314480957<EFBFBD>52]<5D>C5<43>;GG
63b2c76827fb4ad1b2da0d0870441e77a27ee37dea-response-to-cheriton-and-skeens-criticism-of-causal-and-totally-ordered-communication.pdfdistributed_systems/a response to cheriton and skeens criticism of causal and totally ordered communication2017-09-11T23:06:07.8636289062017-09-11T23:06:07.863628906<00>]S5KGG177f9ad15ae9420c5c22f20da9a7c8e8dad4f32da-note-on-distributed-computing.pdfdistributed_systems/a note on distributed computing2017-09-11T23:06:07.8596940922017-09-11T23:06:07.859694092<EFBFBD>m/	]}5uGG
5e51582689653f238029d984cd1780c93ef672771a-history-of-the-virtual-synchrony-replication-model.pdfdistributed_systems/a history of the virtual synchrony replication model2017-09-11T23:06:07.6757680662017-09-11T23:06:07.675768066<EFBFBD>.	]'/GG
150c42217e3c5b52eb1732f4193bf452dcc0de71bprimecoin.pdfdigital_currency/primecoin2017-09-11T23:06:07.6694719242017-09-11T23:06:07.669471924<EFBFBD>-	]%/GG
30db38d32069f3341d34c35085dc009a85ba13c13peercoin.pdfdigital_currency/peercoin2017-09-11T23:06:07.6654379882017-09-11T23:06:07.665437988<EFBFBD>,	]#/GG
48de2fdb04edce612738eb51e14ecc426381f8ed8bitcoin.pdfdigital_currency/bitcoin2017-09-11T23:06:07.6606379392017-09-11T23:06:07.660637939<EFBFBD>+	]91GG
20f278cf94ac0d7fe15a7c4e0f283446e9fc07474out-of-the-tar-pit.pdfdesign/out of the tar pit2017-09-11T23:06:07.6535400392017-09-11T23:06:07.653540039<EFBFBD>\*	]u#mGG
0eecf3aaa6aadf48778bb1daa6b09d011632b9f55warp-multi-key-transactions-for-key-value-stores.pdfdatastores/warp multi key transactions for key value stores2017-09-11T23:06:07.6474089362017-09-11T23:06:07.647408936<EFBFBD>\)	]u#mGG
/b8645fcfdf5af5759dc20ae769b96be510bdff1atransactional-storage-for-geo-replicated-systems.pdfdatastores/transactional storage for geo replicated systems2017-09-11T23:06:07.6410458982017-09-11T23:06:07.641045898<EFBFBD>@(	]Y#QGG
-39ac2e0fc4ec63753306f99e71e0f38133e58eadtao-facebook-distributed-datastore.pdfdatastores/tao facebook distributed datastore2017-09-11T23:06:07.5965590822017-09-11T23:06:07.596559082<EFBFBD>F'	]_#WGG
*87fbf4fa017a90b5ff819bcfca17fb52d6f6a790stasis-flexible-transactional-storage.pdfdatastores/stasis flexible transactional storage2017-09-11T23:06:07.5536740722017-09-11T23:06:07.553674072<EFBFBD>k&
]<5D>#{GG
(f1948a2d5dc8745f725e3ba0b24e14847778cb19spartan-a-distributed-array-framework-with-smart-tiling.pdfdatastores/spartan a distributed array framework with smart tiling2017-09-11T23:06:07.4223029792017-09-11T23:06:07.422302979<EFBFBD>X%	]q#iGG
.4cb33680dda1fa1f0bad1ca52e07a8a34a500104spanner-google's-globally-distributed-database.pdfdatastores/spanner google's globally distributed database2017-09-11T23:06:07.3493959962017-09-11T23:06:07.349395996<EFBFBD>$]<5D>/#<23>'GG
+8b1d8d46836a6d5eb4355315b64d85c128cbff27rados-a-scalable-reliable-storage-service-for-petabyte-scale-storage-clusters.pdfdatastores/rados a scalable reliable storage service for petabyte scale storage clusters2017-09-11T23:06:07.3200139162017-09-11T23:06:07.320013916
<07>
<01><06><05>o<03>BR
F<02><0B>
<EFBFBD><08>
<01>?
Fa<00>bF	]u5kGG28142adcd8a406110c76dbb8e324dc211f3944d1high-level-specifications--lessons-from-industry.pdfdistributed_systems/high level specifications lessons from industry2017-09-11T23:06:08.4614240722017-09-11T23:06:08.461424072<EFBFBD>vE
]<5D>5GG9d2c1271f1219522d13f150c2b04123bef300dd9herbivore-a-scalable-and-efficient-protocol-for-anonymous.pdfdistributed_syst<73>
>]<5D>5<>GG
@11ff11e3aedaa41a67bea3623e5d2a805db6166ecopysets-reducing-the-frequency-of-data-loss-in-cloud-storage.pdfdistributed_systems/copysets reducing the frequency of data loss in cloud storage2017-09-11T23:06:08.1418569342017-09-11T23:06:08.141856934<EFBFBD>t:
]<5D>5{GG
>daf38d927e2b21c885efdb4b2cc46a2d9f47d679commodifying-replicated-state-machines-with-openreplica.pdfdistributed_systems/commodifying replicated state machines with openreplica2017-09-11T23:06:07.9118620612017-09-11T23:06:07.911862061<EFBFBD>)6	]951GG
;24cece61e2128780072bc58f90b8ba47f624bc27brewers-conjecture.pdfdistributed_systems/brewers conjecture2017-09-11T23:06:07.8881889652017-09-11T23:06:07.888188965<EFBFBD>15]<5D>?5<>7GG
:f06554b06ac49f129086c8889690faaa761398bbbeehive-lookup-performance-for-power-law-query-distributions-in-peer-to-peer-overlays.pdfdistributed_systems/beehive lookup performance for power law query distributions in peer to peer overlays2017-09-11T23:06:07.8799250492017-09-11T23:06:07.879925049<EFBFBD>)4]<5D>75<37>/GG
959b3e2060ef7108c9170975219aae410f52ba0b8a-versatile-scheme-for-routing-highly-variable-traffic-in-service-overlays-and-ip.pdfdistributed_systems/a versatile scheme for routing highly variable traffic in service overlays and ip2017-09-11T23:06:07.8742758792017-09-11T23:06:07.874275879<EFBFBD>3]<5D>5<>GG
7208aee805004d575035284b1c232209e9fa26b0ea-universal-modular-actor-formalism-for-artificial-intelligence.pdfdistributed_systems/a universal modular actor formalism for artificial intelligence2017-09-11T23:06:07.8694250492017-09-11T23:06:07.869425049	<09>
]<5D>5<>GG11ff11e3aedaa41a67bea3623e5d2a805db6166ecopysets-reducing-the-frequency-of-data-loss-in-cloud-storage.pdfdistributed_systems/copysets reducing the frequency of data loss in cloud storage2017-09-11T23:06:08.1418569342017-09-11T23:06:08.1418569<EFBFBD>K=	][5SGG
Dd65e79756ac6817d4780286045a35d34aaaaf836consistent-hashing-and-random-trees.pdfdistributed_systems/consistent hashing and random trees2017-09-11T23:06:08.1365800782017-09-11T23:06:08.136580078<0C><00>]<5D>;5<>3GG76c0579c23504531220601029d455dca6413b628consistent-global-states-of-distributed-systems-fundamental-concepts-and-mechanisms.pdfdistributed_systems/consistent global states of distributed systems fundamental concepts and mechani<6E>-<]<5D>;5<>3GG
E76c0579c23504531220601029d455dca6413b628consistent-global-states-of-distributed-systems-fundamental-concepts-and-mechanisms.pdfdistributed_systems/consistent global states of distributed systems fundamental concepts and mechanisms2017-09-11T23:06:08.1307338872017-09-11T23:06:08.130733887<EFBFBD>Y;	]i5aGG
?4e63eed9e709b6c8e20a4a68300883898c7d8f37consensus-in-presence-of-partial-synchrony.pdfdistributed_systems/consensus in presence of partial synchrony2017-09-11T23:06:07.9177128912017-09-11T23:06:07.917712891<00>]<5D>5<>GG76eea8436996c7e9c8f7ad3dac34a12865edab24chain-replication-for-supporting-high-throughput-and-availability.pdfdistributed_systems/chain replication for<6F>	9]<5D>5<>GG
B76eea8436996c7e9c8f7ad3dac34a12865edab24chain-replication-for-supporting-high-throughput-and-availability.pdfdistributed_systems/chain replication for supporting high throughput and availability2017-09-11T23:06:07.9060500492017-09-11T23:06:07.906050049<EFBFBD>m8	]}5uGG
=892b955b6fb175c92f3f294ab431f97a8827748dbyzantine-fault-tolerant-distributed-commit-protocol.pdfdistributed_systems/byzantine fault tolerant distributed commit protocol2017-09-11T23:06:07.9004890142017-09-11T23:06:07.900489014<EFBFBD>;7	]K5CGG
<17007f5e69efcfeff03853a33121943e2b4df422byzantine-chain-replication.pdfdistributed_systems/byzantine chain replication2017-09-11T23:06:07.8936340332017-09-11T23:06:07.893634033

<01>	
<0A>

/:
\	azv^r
<01>}<03><02><00>iJ	]y5qGG
P9aa8f3d1df6ff6d266a531432fe9ea0bb56ad3c3in-search-of-an-understandable-consensus-algorithm.pdfdistributed_systems/in search of an understandable consensus algorithm2017-09-11T23:06:08.4855869142017-09-11T23:06:08.485586914<EFBFBD>GM]<5D>U5<55>MGG
Mbde7543a8b3ce071342dfaea2a14357431d94b82kelips-building-an-efficient-and-stable-p2p-dht-through-increased-memory-and-background-overhead.pdfdistributed_systems/kelips building an efficient and stable p2p dht through increased memory and background overhead2017-09-11T23:06:08.5111398932017-09-11T23:06:08.511139893<EFBFBD>L	]/5'GG
N1e86909765bd5603a152bbd55e511e0586f1b77fjoin-calculus.pdfdistributed_systems/join calculus2017-09-11T23:06:08.5028688962017-09-11T23:06:08.502868896<EFBFBD>rK
]<5D>5{EE<00>36222f8eb2ccf21ca345e15186cea64506581543ironFleet-proving-practical-distributed-systems-correct.pdfdistributed_systems/ironfleet proving practical distributed systems correct2017-09-11T23:06:08.494632082017-09-11T23:06:08.49463208<EFBFBD>iI	]y5qGG
L00e3756119a91432622f6982b59ecd24a1340fbeimpossibility-of-consensus-with-one-faulty-process.pdfdistributed_systems/impossibility of consensus with one faulty process2017-09-11T23:06:08.4766879882017-09-11T23:06:08.476687988<EFBFBD>H]<5D>#5<>GG
K1551d42b24a5b1e1ead5f0793e807869249ab93eimplementing-the-omega-failure-detector-in-crash-recovery-failure-model.pdfdistributed_systems/implementing the omega failure detector in crash recovery failure model2017-09-11T23:06:08.4707060552017-09-11T23:06:08.470706055<EFBFBD>
G]<5D>5<>	EE
J7d7de228c501ef486534cca1829378eef8ef1081how-the-hidden-hand-shapes-the-market-for-software-reliability.pdfdistributed_systems/how the hidden hand shapes the market for software reliability2017-09-11T23:06:08.466872072017-09-11T23:06:08.46687207<EFBFBD>dF	]u5kGG
I28142adcd8a406110c76dbb8e324dc211f3944d1high-level-specifications--lessons-from-industry.pdfdistributed_systems/high level specifications lessons from industry2017-09-11T23:06:08.4614240722017-09-11T23:06:08.461424072<EFBFBD>xE
]<5D>5GG
G9d2c1271f1219522d13f150c2b04123bef300dd9herbivore-a-scalable-and-efficient-protocol-for-anonymous.pdfdistributed_systems/herbivore a scalable and efficient protocol for anonymous2017-09-11T23:06:08.4552490232017-09-11T23:06:08.455249023<EFBFBD>[D	]k5cGG
H50158bc1a8a67295ab7bce0550886a9859000dc2harvest-yield-and-scalable-tolerant-systems.pdfdistributed_systems/harvest yield and scalable tolerant systems2017-09-11T23:06:08.4413249512017-09-11T23:06:08.441324951<EFBFBD>rC
]<5D>5{EE<00>49ed15db181c74c7067ec01800fb5392411c868cepidemic-algorithms-for-replicated-database-maintenance.pdfdistributed_systems/epidemic algorithms for replicated database maintenance2017-09-11T23:06:08.371104982017-09-11T23:06:08.37110498<EFBFBD>OB	]_5WGG<00>368427e6e351d1ac0ef97e824968ed15d0dc3d4dend-to-end-arguments-in-system-design.pdfdistributed_systems/end to end arguments in system design2017-09-11T23:06:08.3673620612017-09-11T23:06:08.367362061<EFBFBD>oA	]5wGG
Cf52e7afce70597024c3be7df105185dd59a2c8e6eluding-carnivores-file-sharing-with-strong-anonymity.pdfdistributed_systems/eluding carnivores file sharing with strong anonymity2017-09-11T23:06:08.3627729492017-09-11T23:06:08.362772949<EFBFBD>@]<5D>!5<>GG
Ffd443b2ce70c48202ba26cbc6caa471ae262e270distributed-snapshots-determining-global-states-of-distributed-systems.pdfdistributed_systems/distributed snapshots determining global states of distributed systems2017-09-11T23:06:08.2626330572017-09-11T23:06:08.262633057<EFBFBD>t?
]<5D>5{GG
A003d5a65de0ac72daaf105ded903cb3eb88585b3dapper-a-large-scale-distributed-tracing-infrastructure.pdfdistributed_systems/dapper a large scale distributed tracing infrastructure2017-09-11T23:06:08.1625371092017-09-11T23:06:08.162537109
b}<0E>
<0A><0C><0B>
<EFBFBD>
v<08><07><06>8}F?U<00>vX
]<5D>5}GG
Z4329143e227370d931a207184f3b995c0cb5c8d5self-stabilizing-systems-in-spite-of-distributed-control.pdfdistributed_systems/self stabilizing systems in spite of distributed control2017-09-11T23:06:08.7082280272017-09-11T23:06:08.708228027<EFBFBD>MS	]]5UGG
Yf16c6ce0c7eabd4f5896962335879b3932138e52on-proof-and-progress-in-mathematics.pdfdistributed_systems/on proof and progress in mathematics2017-09-11T23:06:08.6447729492017-09-11T23:06:08.644772949<EFBFBD>Y]<5D>'5<>GG
X95d36d171e5e2183c424f535fad2e8053f5cec64sift-design-and-analysis-of-a-fault-tolerant-computer-for-aircraft-contro.pdfdistributed_systems/sift design and analysis of a fault tolerant computer for aircraft contro2017-09-11T23:06:08.7147629392017-09-11T23:06:08.714762939	<09><00>]w5oGG5eb4500b8053ac8dd1a21bfca10c818e1e0a2405simple-testing-can-prevent-most-critical-failures.pdfdistributed_systems/simple testing can prevent most critical failures2017-09-11T23:06:08.8323769532017-09-11T23:06:08.832376953	<09><00>]<5D>5}<7D>g[	]w5oGG
a5eb4500b8053ac8dd1a21bfca10c818e1e0a2405simple-testing-can-prevent-most-critical-failures.pdfdistributed_systems/simple testing can prevent most critical failures2017-09-11T23:06:08.8323769532017-09-11T23:06:08.832376953<EFBFBD>vZ
]<5D>5}GG
[65d3575b1c380b1bcc14ec69ccf6989c04be9493signal-&-collect-graph-algorithms-for-the-(semantic)-web.pdfdistributed_systems/signal & collect graph algorithms for the (semantic) web2017-09-11T23:06:08.8134960942017-09-11T23:06:08.813496094<EFBFBD>'W	]75/GG
W763d0321ced31b774bd4ba2f9f369c087cbd278epaxos-made-simple.pdfdistributed_systems/paxos made simple2017-09-11T23:06:08.7029479982017-09-11T23:06:08.702947998<EFBFBD>?V	]O5GGG
U43c7b3780b5864f99d042392d83ab331f7fddf2apaxos-made-moderately-complex.pdfdistributed_systems/paxos made moderately complex2017-09-11T23:06:08.6627680662017-09-11T23:06:08.662768066<EFBFBD>CU]<5D>Q5<51>IGG
V4bf4acf54bfd2e65b1ed31fe272670a7e276c534pastry-scalable-decentralized-object-location-and-routing-for-large-scale-peer-to-peer-systems.pdfdistributed_systems/pastry scalable decentralized object location and routing for large scale peer to peer systems2017-09-11T23:06:08.6551569822017-09-11T23:06:08.655156982<EFBFBD>eT	]y5qEE1a0ba12427c68642a4871677b9de7a337356b9f6p5-a-protocal-for-scalable-anonymous-communication.pdfdistributed_systems/p5 a protocal for scalable anonymous communication2017-09-11T23:06:08.649752932017-09-11T23:06:08.64975293<00>]]5UGGf16c6ce0c7eabd4f5896962335879b3932138e52on-proof-and-progress-in-mathematics.pdfdistributed_systems/on proof and progress in mathematics2017-09-11T23:06:08.6447729492017-09-11T23:06:08.644772949<EFBFBD>)R]<5D>75<37>/GG
Ra2e4dc4b1cce765255e4d15084811da125c564c5oblivious-routing-of-highly-variable-traffic-in-service-overlays-and-ip-backbones.pdfdistributed_systems/oblivious routing of highly variable traffic in service overlays and ip backbones2017-09-11T23:06:08.6341188962017-09-11T23:06:08.634118896<EFBFBD>Q]<5D>5<>GG
T3e375c8d996b8c46c83b9d3f72732d7477e5fd86mesos-a-platform-for-fine-grained-resource-sharing-in-the-data-center.pdfdistributed_systems/mesos a platform for fine grained resource sharing in the data center2017-09-11T23:06:08.6232319342017-09-11T23:06:08.623231934<EFBFBD>rP
]<5D>
5yGG
Sf3050b5586ddfec5da0d719338a6afa8b166985bmapreduce-simplified-data-processing-on-large-clusters.pdfdistributed_systems/mapreduce simplified data processing on large clusters2017-09-11T23:06:08.6067629392017-09-11T23:06:08.606762939<EFBFBD>xO
]<5D>5GG
Oc20baa16cb57ff4979569871d15294fa720bbc23life-beyond-distributed-transactions-an-apostates-opinion.pdfdistributed_systems/life beyond distributed transactions an apostates opinion2017-09-11T23:06:08.5616230472017-09-11T23:06:08.561623047<EFBFBD>-N]<5D>;5<>3GG
Q57efc2b9ba2a725af1d66cc43c472d0314190051large-scale-incremental-processing-using-distributed-transactions-and-notifications.pdfdistributed_systems/large scale incremental processing using distributed transactions and notifications2017-09-11T23:06:08.5383491212017-09-11T23:06:08.538349121

<01>G<00><0F><0F>yL<0E><0E><0E>i<
<0A>
<0A>
<0A>
[
X
.

<04><0C><0C>zM <0B><0B><0B>l>
*<00>,
<EFBFBD>
<EFBFBD>
<EFBFBD>
\
.

	<09>	<09>	y	L	<08><08><08>k><07>Z<07><07>\/<06><06>{N <05><05>
<01><05>l><04><04><03><03>|N <02><02><00>
<01><02>j=
<01>-]703d0b290a4ece50c17854ed72ecc808ce3e6f43<00>-]23c425f022baa054c68683eaf81f5d482915ce13<00>-]239ff60210c28900f866c588f40e974d897a9f62<00>-]1396a6cd134a7f41eeb1e5d4ca8d4edf6edfc432<00>-]557b1ec3182ccb3a902cc9904a443accb438842f<00>x76e1cf37ae212298802799c2c3588030d20a769f<00>=.70882fa7790685902d4d8b56ba08a361f6e74eb1<00>,]
76eea8436996c7e9c8f7ad3dac34a12865edab249<02>76c0579c23504531220601029d455dca6413b628<-]765e049036ca947af05fb5b4f29b9daf4b363558<00>,]
763d0321ced31b774bd4ba2f9f369c087cbd278eW6e39523a0acd9855ff465598253c323f7dfd3cda-]6995ac2e570960403c02250b02e64cafed8378fd<00>-]6980e1e551cadbde62454bedf5e1324032fa1e40<00>-]6848895fe48b0ca3b0bc34c1bcdf66eb58e64308<00>,]
6718cc5cd4e1484990ee79a8c3cffaad6d7271c3,]
66401c00817c71713e86438385d91956246aeaabf,]
65d3575b1c380b1bcc14ec69ccf6989c04be9493Z,]
64832c7b1602f0922e4e818ad045d1bb5ae95-]272ef349f3b3561588a87a070de802c3c0246394<00>-]472f436ad317b23d7bd1ad53fcb4f23e8f0997a7<00>-]16c8ad89060897e39803a175470d7990bd40cd2b<00>-]59a968fa431e7117aa11005ed98ab39f1efddc30<00>,]
5ac2852c69cc7bda25677129da011dec23fc3d77v,]
59b3e2060ef7108c9170975219aae410f52ba0b84-]59776eb2358b4be265e7dae9df4f946dab25bf6f<00>,]
57efc2b9ba2a725af1d66cc43c472d0314190051N,]
57d70e73a995be26f01ae51f321fdaf42a089bf8,]
530b50510808903545d298de7e19d6e5463a72cdd,]
50c42217e3c5b52eb1732f4193bf452dcc0de71b.-]5046034fe0cddda681ad9374d306fd27eec8b5fb<00>,]
50158bc1a8a67295ab7bce0550886a9859000dc2D,]
4fc240d0d9e690cb9b0bcb2f8a5e5ca918b01410,]
4e63eed9e709b6c8e20a4a68300883898c7d8f37;,]
4cb33680dda1fa1f0bad1ca52e07a8a34a500104%,]
4bf4acf54bfd2e65b1ed31fe272670a7e276c534U,]
4ba0079fbfaf8a49f36f4e400f44c17b7f4552d4|-]4b85765a808e4c29f05bc48a17a2dced1702db9d<00>,]
4b1ed99c65d500d4a610813736169851cb496810,]
49ed15db181c74c7067ec01800fb5392411c868cC,]
4712e0a50083a6bda848bf4a65fe214f0f6a7069	,]
451da9c5558de4c75f01582292063a7c980292080,]
43c7b3780b5864f99d042392d83ab331f7fddf2aV,]
4329143e227370d931a207184f3b995c0cb5c8d5X,]
3e375c8d996b8c46c83b9d3f72732d7477e5fd86Q,]
3b2c76827fb4ad1b2da0d0870441e77a27ee37de2,]
3a05eea36ffdbcf0625d5154a6458e75ca835971,]
39ac2e0fc4ec63753306f99e71e0f38133e58ead(,]
381c0200a69d43c6605079aaf73beace048b76a6,]
368427e6e351d1ac0ef97e824968ed15d0dc3d4dB,]
36222f8eb2ccf21ca345e15186cea64506581543K-]3547ac839d02f6efe3f6f76a8289738a22528442<00>,]
30fae8663ffba4f4abca068a9bc8735a590a9bc5-]30ef9946a1733c097d541ffaae8e95f0af862a08<00>-]30baa244b66e81d737ccf9f667c9bfca4f0c18f1<00>,]
2db53cdcf4ba7c67321c022954c2b2be9c8a40bdi,]
29f3f5918946bf0a4d75bf5244f993847d03e26c#,]
28142adcd8a406110c76dbb8e324dc211f3944d1F,]
24cece61e2128780072bc58f90b8ba47f624bc276-]223b694fb70d4bd18ba0f4bd73ff3c6bc8f6370a<00>,]
2128052ca0319cdf9c9256eb52f26a23c6527094t,]
208aee805004d575035284b1c232209e9fa26b0e3,]
1e86909765bd5603a152bbd55e511e0586f1b77fL,]
1cdc911f5a1b7a770b2e27bf4ebfae04c003a616,]
1c1ff93040a96dfe9f1309bfe34a989d5f93bb4f,]
1a0ba12427c68642a4871677b9de7a337356b9f6T,]
18a74ae5e33b76a0528d0724d5c55a98dabe0b1fn,]
177f9ad15ae9420c5c22f20da9a7c8e8dad4f32d1,]
17007f5e69efcfeff03853a33121943e2b4df4227,]
158d08ec7c2134382e20b44001903ad5b8a521b2l,]
1551d42b24a5b1e1ead5f0793e807869249ab93eH,]
11ff11e3aedaa41a67bea3623e5d2a805db6166e>,]
11825521850926501e3f353ffb7cf14b0c389320,]
0f278cf94ac0d7fe15a7c4e0f283446e9fc07474+,]
0f007df1707d77a72237248b0d7fd93b37fc9db7,]
0ec3651f70a50c371a1f9502fc7d3eab272d5cff,]
0db38d32069f3341d34c35085dc009a85ba13c13--]09ac606ba306a1bea91642deb2af0909360b038f<00>,]
07f82eecbe3d530e3f967342245a4d5c8e41c05be,]
07d847f310d5fa9138f461f0a25c5e0024f1c4af"-]07ad71a8d82bf51e0b5d1d892aa6a10673a3b830<00>,]
0404bd58e5f1edbd288cd69fcbc224485af415bfs,]
02cc6a5944d57d2353a55639c7b77336b94f29b6,]
016f4930ad10f8097c42e5294b56d25bfb3c121fq,]
00e3756119a91432622f6982b59ecd24a1340fbeI,]
003d5a65de0ac72daaf105ded903cb3eb88585b3?
<00>E<00>f9<07><07><07>W*<06><06><06>rE<05><05><05>a3<04><0F><0F>yKO<0E><0E>!<0E>i<
<0A>
<0A>
<0A>
Z
,<0C><0C><0C>xJ<00><0B><0B><0B>i<}
<EFBFBD><03>
<EFBFBD>
<EFBFBD>
Y<04>
+	<09>	<09>	<09>	x	J	<08><08><08><03><03><03>pC<02><02><02>b5
<01>
<01>
<01>
S
%-]9b8aec8ef5c67da463f5ec7c174570eb7d1643a8<00><02>d0d8b7501d7f75613d5493d706d6d81852a73d6e<00>-]fec6b29569eac1a340990bb07e90355efd2434ec<00>,]
fe0ae75e97abe2686e6bc8cbe94bfd08934e36da,]
fd443b2ce70c48202ba26cbc6caa471ae262e270@,]
fc11031895c302dc52404d34de58af1a72f3b817g,]
fb2db075fa0230289a4f05caf2127b95fcc9aa9c
-]f6dce666a0f64f97f380f99cba7f14e24d5f54ad<00>,]
f52e7afce70597024c3be7df105185dd59a2c8e6A,]
f5222809526d8a419a1752547880ba0a9013a8ca,]
f3485e24d796c33f11048f74e447853ef4a6dc53c,]
f3050b5586ddfec5da0d719338a6afa8b166985bP,]
f1948a2d5dc8745f725e3ba0b24e14847778cb19&,]
f16c6ce0c7eabd4f5896962335879b3932138e52S,]
f06554b06ac49f129086c8889690faaa761398bb5-]f00e7c584731135892cb1bc133672a3d63d9e095<00>,]
eee4e109fd92ea679600a61dd7d3428efa786a64m,]
eecf3aaa6aadf48778bb1daa6b09d011632b-]a8c4718ce66e527a5fd1726e3aea5d6c8e33efff<00>-]855593c778f9f6c98a16afbd8e3097dbde09685c<00>-]8004558792c00764d173dc63c03d3a391acfe6b7<00>-]a5c83733c6abcd1a089bed36cf2ef38577ec5521<00>-]b68ff86ce8591931d3bef1294f8b46dae63780ad<00>,]
778e77ac46880d905d104d4f771fc5bb978a19ee},]
76eea8436996c7e9c8f7ad3dac34a12865edab249-]76e1cf37ae212298802799c2c3588030d20a769f<00>,]
76c0579c23504531220601029d455dca6413b628<-]765e049036ca947af05fb5b4f29b9daf4b363558<00>,]
763d0321ced31b774bd4ba2f9f369c087cbd278eW-]70882fa7790685902d4d8b56ba08a361f6e74eb1<00>-]703d0b290a4ece50c17854ed72ecc808ce3e6f43<00>,]
6e39523a0acd9855ff465598253c323f7dfd3cda-]6995ac2e570960403c02250b02e64cafed8378fd<00>-]6980e1e551cadbde62454bedf5e1324032fa1e40<00>-]6848895fe48b0ca3b0bc34c1bcdf66eb58e64308<00>-]67ea9f0fe38b6848de19578589eab498473562c3<00>,]
6718cc5cd4e1484990ee79a8c3cffaad6d7271c3,]
66401c00817c71713e86438385d91956246aeaabf,]
65d3575b1c380b1bcc14ec69ccf6989c04be9493Z,]
64832c7b1602f0922e4e818ad045d1bb5ae95dd6^-]614d66c63f8a04cf24cf19ce885f6a34be56a67c<00>,]
612b437425a8077a832c27b7f4ec057143e87a8cj,]
6125b966172dd6cde3563f2ae10d8f782d14e1de,]
5eb4500b8053ac8dd1a21bfca10c818e1e0a2405[-]c501a067498b94558da0e0510a4c29370388aee0<00>-]c2eec09d057ce3b7277395e6820f38744e67fb97<00>,]
c20baa16cb57ff4979569871d15294fa720bbc23O-]c1350b1680d30a7bdcb9837bff2e0e8c40f9a92a<00>-]c0f83a70b1c225e7705c301e1106332819bff375<00>,]
bde7543a8b3ce071342dfaea2a14357431d94b82M+]	bd9e0c2f5aaf68d784862ab361cc1a41fc9b32cd,]
bac41b59697da3ca5c80ca08f2bbbc97a3576248a,]
b8645fcfdf5af5759dc20ae769b96be510bdff1a)-]b7741ea891833418cc888b38f9f529bdb86409a4<00>-]b615e2186f1982009d863f3f2f98909f2f7815ab<00>,]
ac14e6bf50d1491043baf1d854727a68f5f3f51d,]
a9d9352d43986d4a5a3554a84b99580225ec00cf,]
a673b5ccb8fed1cb38edf75ead930569ba568c10z-]a659692ed5031c5410668d644a60d7806bb2efbb<00>,]
a2e89c6111f3e306c56472306795af290ffb29af,]
a2e4dc4b1cce765255e4d15084811da125c564c5R,]
9ed603d5743ef547a23578c5d50bd23069a6f2a8{,]
9d48eb6b89a9d7aa6feab3f6b2f57c70c1d9d18fw,]
9d2c1271f1219522d13f150c2b04123bef300dd9E,]
9aa8f3d1df6ff6d266a531432fe9ea0bb56ad3c3J-]997d371f1e063ff11e00fc6c0aef259558b92303<00>,]
993f5b0bb126caae848937b2323efabdf8bc21e9`,]
97edc89b0a19e90e2123f22315b88aaf7033bb3a~,]
973f17392cb7b417271e9d482d17a44a8c70c70a,]
95d36d171e5e2183c424f535fad2e8053f5cec64Y-]94e8fc6068b6dff5a2a688f51c44ebfdd23f7e1a<00>-]904014fb5cb22e8241c55e2fc6ae46288c5eebaf<00>,]
8eacd0f01ab0f53706561dda0ce8d1f96544a348p,]
8e1408e93d56b214a9018a7c13422715367a28bex,]
8de2fdb04edce612738eb51e14ecc426381f8ed8,,]
8b1d8d46836a6d5eb4355315b64d85c128cbff27$,]
892b955b6fb175c92f3f294ab431f97a8827748d8,]
87fbf4fa017a90b5ff819bcfca17fb52d6f6a790',]
87a6e1ec4dd1df928541467296e4cf2a0f2df0c3b,]
83cf2b3372ef98f7fa5caf94aa44e7262ee47519
-]802fed876e180f32c06ede4d1cc951ba44f79dd2<00>,]
7edaa9cc255ba8e0938cb563110b204a4f393d60-]7de4f6fddb11254d1fd5f8adfd67b6e0c9439eaa<00>,]
7d7de228c501ef486534cca1829378eef8ef1081G,]
78dec404a01664b35f3c740834597920186fbba7u,]
78c295cfd7469cd3d494a48df7bd7748139e0660
<00>
<0A>
<0B>
<EFBFBD>	<09><08>U<06><05><04><03>?<00>
<01><00>v]<5D>+1<>#GG
p5ac2852c69cc7bda25677129da011dec23fc3d77making-a-fast-curry-push-enter-versus-eval-apply-for-higher-order-languages.pdflanguages/haskell/making a fast curry push enter versus eval apply for higher order languages2017-09-11T23:06:10.5060729982017-09-11T23:06:10.506072998<EFBFBD>]w]<5D>m1<6D>eGG
n9d48eb6b89a9d7aa6feab3f6b2f57c70c1d9d18ftackling-the-awkward-squad-monadic-input-output-concurrency-exceptions-and-foreign-language-calls-in-haskell.pdflanguages/haskell/tackling the awkward squad monadic input output concurrency exceptions and foreign language calls in haskell2017-09-11T23:06:10.5499750982017-09-11T23:06:10.549975098<EFBFBD>=u	]O1GGG
m78dec404a01664b35f3c740834597920186fbba7a-poor-mans-concurrency-monad.pdflanguages/haskell/a poor mans concurrency monad2017-09-11T23:06:10.3302910162017-09-11T23:06:10.330291016<EFBFBD>[t	]m1eGG<00>2128052ca0319cdf9c9256eb52f26a23c6527094a-practical-optional-type-system-for-clojure.pdflanguages/clojure/a practical optional type system for clojure2017-09-11T23:06:10.3228588872017-09-11T23:06:10.322858887<EFBFBD>Xs	]k3cEE
o0404bd58e5f1edbd288cd69fcbc224485af415bfa-mathematical-theory-of-communication-1948.pdfinformation_theory/a mathematical theory of communication 19482017-09-11T23:06:10.315979982017-09-11T23:06:10.31597998<EFBFBD>vr
]<5D>9{GG
le36073e9e5c97e0204050c0c316d87479f94974ethe-pagerank-citation-ranking-bringing-order-to-the-web.pdfinformation_retrieval/the pagerank citation ranking bringing order to the web2017-09-11T23:06:10.3003291022017-09-11T23:06:10.300329102<EFBFBD>!q	]19)EE<00>016f4930ad10f8097c42e5294b56d25bfb3c121fokapi-at-trec3.pdfinformation_retrieval/okapi at trec32017-09-11T23:06:10.275385012017-09-11T23:06:10.27538501<EFBFBD>7p	]E9=GG<00>8eacd0f01ab0f53706561dda0ce8d1f96544a348graph_of_word_and_tw_idf.pdfinformation_retrieval/graph of word and tw idf2017-09-11T23:06:10.2680969242017-09-11T23:06:10.268096924<EFBFBD>ko	]y9qGG<00>da731f99e05dd4f1fad1d21a1c6124efeb3bcf61authoritative-sources-in-a-hyperlinked-environment.pdfinformation_retrieval/authoritative sources in a hyperlinked environment2017-09-11T23:06:10.2016918952017-09-11T23:06:10.201691895<EFBFBD>>n	]O3GGG
k18a74ae5e33b76a0528d0724d5c55a98dabe0b1fthe_lisp_ii_garbage_collector.pdfgarbage_collection/the lisp ii garbage collector2017-09-11T23:06:10.1830480962017-09-11T23:06:10.183048096<EFBFBD> m]<5D>/3<>'GG<00>eee4e109fd92ea679600a61dd7d3428efa786a64parallel_generational_copying_garbage_collection_with_a_block_structured_heap.pdfgarbage_collection/parallel generational copying garbage collection with a block structured heap2017-09-11T23:06:10.0999919432017-09-11T23:06:10.099991943<EFBFBD>l]<5D>3<>GG<00>158d08ec7c2134382e20b44001903ad5b8a521b2incremental_mature_garbage_collection_using_the_train_algorithm.pdfgarbage_collection/incremental mature garbage collection using the train algorithm2017-09-11T23:06:09.6336560062017-09-11T23:06:09.633656006<EFBFBD>,k]<5D>A'<27>9GG
j5b0ccfcd8135c9599f8088443ed7de1874fa1c97why-students-engage-in-gaming-the-system-behavior-in-interactive-learning-environments.pdfgamification/why students engage in gaming the system behavior in interactive learning environments2017-09-11T23:06:09.5316699222017-09-11T23:06:09.531669922<EFBFBD>Xj	]o'gGG
h612b437425a8077a832c27b7f4ec057143e87a8cgamification-in-education-what-how-why-bother.pdfgamification/gamification in education what how why bother2017-09-11T23:06:09.5095869142017-09-11T23:06:09.509586914<EFBFBD>i]<5D>A<>
EE<00>2db53cdcf4ba7c67321c022954c2b2be9c8a40bda-theoreticians-guide-to-the-experimental-analysis-of-algorithms.pdfexperimental_algorithmics/a theoreticians guide to the experimental analysis of algorithms2017-09-11T23:06:09.394502932017-09-11T23:06:09.39450293<EFBFBD>}h]<5D>5<>GG
ed0cb011908e333fe17309518249be05820b5239fzookeeper-wait-free-coordination-for-internet-scale-systems.pdfdistributed_systems/zookeeper wait free coordination for internet scale systems2017-09-11T23:06:09.2425061042017-09-11T23:06:09.242506104
4p
<0A><0C><0B>
f	<09><08><07><06>O<05><04><03>'
s<00><00>3<EFBFBD>		]E1=GG
~6980e1e551cadbde62454bedf5e1324032fa1e40unix-time-sharing-system.pdfoperating_systems/unix time sharing system2017-09-11T23:06:12.6897451172017-09-11T23:06:12.689745117<EFBFBD><0F>	]!1GG
zf00e7c584731135892cb1bc133672a3d63d9e095therac.pdfoperating_systems/therac2017-09-11T23:06:12.6663500982017-09-11T23:06:12.666350098<EFBFBD><1D>]<5D>/1<>'EE<00>4b85765a808e4c29f05bc48a17a2dced1702db9dsolaris-zones-operating-system-support-for-consolidating-commercial-workloads.pdfoperating_systems/solaris zones operating system support for consolidating commercial workloads2017-09-11T23:06:12.608392092017-09-11T23:06:12.60839209<EFBFBD>G<EFBFBD>	]Y1QGG
|d4723308389e064389bc4e6aee46db5fc9b214eelive-migration-of-virtual-machines.pdfoperating_systems/live migration of virtual machines2017-09-11T23:06:12.3678010252017-09-11T23:06:12.367801025<EFBFBD>G<EFBFBD>	]Y1QGG
{765e049036ca947af05fb5b4f29b9daf4b363558kvm-linux-virtual-machines-monitor.pdfoperating_systems/kvm linux virtual machines monitor2017-09-11T23:06:12.0644060062017-09-11T23:06:12.064406006<EFBFBD>K<EFBFBD>	]]1UGG<00>a659692ed5031c5410668d644a60d7806bb2efbbjails-confining-the-omnipotent-root..pdfoperating_systems/jails confining the omnipotent root.2017-09-11T23:06:11.9372780762017-09-11T23:06:11.937278076<EFBFBD>?<3F>	]K=CGG<00>c2eec09d057ce3b7277395e6820f38744e67fb97efficient-lock-free-b+trees.pdfnon_blocking_algorithms/efficient lock free b+trees2017-09-11T23:06:11.7259489752017-09-11T23:06:11.725948975<EFBFBD>+<2B>	]7=/GG
y6995ac2e570960403c02250b02e64cafed8378fda-wait-free-stack.pdfnon_blocking_algorithms/a wait free stack2017-09-11T23:06:11.3879260252017-09-11T23:06:11.387926025<EFBFBD>]<5D>
	]i=aGG<00>d5c3b8b3006fc4b24e770f028c938d4bcbd62695a-wait-free-queue-as-fast-as-fetch-and-add.pdfnon_blocking_algorithms/a wait free queue as fast as fetch and add2017-09-11T23:06:11.3326069342017-09-11T23:06:11.332606934<EFBFBD><0F>]<5D>1<>GG<00>802fed876e180f32c06ede4d1cc951ba44f79dd2scatteralloc-massively-parallel-dynamic-memory-allocation-for-the-gpu.pdfmemory_management/scatteralloc massively parallel dynamic memory allocation for the gpu2017-09-11T23:06:10.9212509772017-09-11T23:06:10.921250977<EFBFBD>K	]]1UGG
w381c0200a69d43c6605079aaf73beace048b76a6making-lockless-synchronization-fast.pdfmemory_management/making lockless synchronization fast2017-09-11T23:06:10.8874990232017-09-11T23:06:10.887499023<EFBFBD>#~	];%3GG
t97edc89b0a19e90e2123f22315b88aaf7033bb3atranscendence-of-pi.pdfmathematics/transcendence of pi2017-09-11T23:06:10.8822609862017-09-11T23:06:10.882260986<EFBFBD>7}]<5D>/a<>'GG
v778e77ac46880d905d104d4f771fc5bb978a19eetoward-a-unified-theory-of-sparse-dimensionality-reduction-in-euclidean-space.pdfmachine_learning/dimensionality_reduction/toward a unified theory of sparse dimensionality reduction in euclidean space2017-09-11T23:06:10.8137690432017-09-11T23:06:10.813769043<EFBFBD>k|	]ea]GG
u4ba0079fbfaf8a49f36f4e400f44c17b7f4552d4a-sparse-johnson-lindenstrauss-transform.pdfmachine_learning/dimensionality_reduction/a sparse johnson lindenstrauss transform2017-09-11T23:06:10.7901140142017-09-11T23:06:10.790114014<EFBFBD>{]<5D>9<>	GG
q9ed603d5743ef547a23578c5d50bd23069a6f2a8representing-game-dialogue-as-expressions-in-first-order-logic.pdflogic_and_programming/representing game dialogue as expressions in first order logic2017-09-11T23:06:10.7235681152017-09-11T23:06:10.723568115<EFBFBD>Wz	]e9]GG
xa673b5ccb8fed1cb38edf75ead930569ba568c10on-the-meanings-of-the-logical-constants.pdflogic_and_programming/on the meanings of the logical constants2017-09-11T23:06:10.7168100592017-09-11T23:06:10.716810059<EFBFBD>Ay	]Q5IGG
sd25c77b7d5f4b6742e63bc6f3b92ab220c833d23The-Early-History-Of-Smalltalk.pdflanguages/smalltalk/the early history of smalltalk2017-09-11T23:06:10.6869809572017-09-11T23:06:10.686980957<EFBFBD>Ix	]Y5QGG
r8e1408e93d56b214a9018a7c13422715367a28beDesign-Principles-Behind-Smalltalk.pdflanguages/smalltalk/design principles behind smalltalk2017-09-11T23:06:10.6670510252017-09-11T23:06:10.667051025
<03><00>m<0E>
<0A><0C><0B>
<EFBFBD>	<09>
<01>	<02>`V<06><00><05><00><19>]<5D>a<>	GG
<01>223b694fb70d4bd18ba0f4bd73ff3c6bc8f6370aray-integrating-rx-and-async-for-direct-style-reactive-streams.pdfparadigms/functional_reactive_programming/ray integrating rx and async for direct style reactive streams2017-09-11T23:06:13.0470969242017-09-11T23:06:13.047096924<EFBFBD>X<EFBFBD>	][OSGG<00>f6dce666a0f64f97f380f99cba7f14e24d5f54adorganizing-programs-without-classes.pdfparadigms/functional_programming/organizing programs without classes2017-09-11T23:06:12.9792910162017-09-11T23:06:12.979291016<EFBFBD>q<EFBFBD>	]kacGG
<01>5046034fe0cddda681ad9374d306fd27eec8b5fba-survey-of-functional-reactive-programming.pdfparadigms/functional_reactive_programming/a survey of functional reactive programming2017-09-11T23:06:12.9885161132017-09-11T23:06:12.988516113?
<01>
]<5D>=GGeb654b2087706468fe3173c4b38b940be0c85722cognitive-computing-programming-paradigm-corelet-language.pdfparadigms/new_paradigms/cognitive computing programming paradigm corelet language2017-09-11T23:06:13.0537729492017-09-11T23:06:13.053772949?
<01>]<5D>a<>	GG223b694fb70d4bd18ba0f4bd73ff3c6bc8f6370aray-integrating-rx-and-async-for-direct-style-reactive-streams.pdfparadigms/functional_reactive_programming/ray integrating rx and async for direct style reactiv<69>|<7C>
]<5D>=GG
<01>eb654b2087706468fe3173c4b38b940be0c85722cognitive-computing-programming-paradigm-corelet-language.pdfparadigms/new_paradigms/cognitive computing programming paradigm corelet language2017-09-11T23:06:13.0537729492017-09-11T23:06:13.053772949<EFBFBD>U<EFBFBD>	]OaGGG
<01>e306d45aeb2d3f72055ce72ccbebd0ccb42cdf17functional-reactive-animation.pdfparadigms/functional_reactive_programming/functional reactive animation2017-09-11T23:06:13.0229680182017-09-11T23:06:13.022968018<EFBFBD>[<5B>	]UaMGG
<01>d7341e40b11008965d60631953ad83e89aa40584deprecating-the observer-pattern.pdfparadigms/functional_reactive_programming/deprecating the observer pattern2017-09-11T23:06:12.9958210452017-09-11T23:06:12.995821045	]YOQGGc501a06749<34>=<3D>	]7a/GG
<01>09ac606ba306a1bea91642deb2af0909360b038ffrp-in-plt-scheme.pdfparadigms/functional_reactive_programming/frp in plt scheme2017-09-11T23:06:13.0173220212017-09-11T23:06:13.017322021<EFBFBD>V<EFBFBD>	]YOQGG
<01>c501a067498b94558da0e0510a4c29370388aee0why-functional-programming-matters.pdfparadigms/functional_programming/why functional programming matters2017-09-11T23:06:12.9834589842017-09-11T23:06:12.983458984<EFBFBD>d<EFBFBD>	]gO_GG
<01>59776eb2358b4be265e7dae9df4f946dab25bf6foptimal-purely-functional-priority-queues.pdfparadigms/functional_programming/optimal purely functional priority queues2017-09-11T23:06:12.9515539552017-09-11T23:06:12.951553955<EFBFBD><1A>
]<5D>O<>GG
}fec6b29569eac1a340990bb07e90355efd2434ecfunctional-programming-with-bananas-lenses-envelops-and-barbed-wire.pdfparadigms/functional_programming/functional programming with bananas lenses envelops and barbed wire2017-09-11T23:06:12.9420480962017-09-11T23:06:12.942048096<EFBFBD>X<EFBFBD>	][OSGG
<01>904014fb5cb22e8241c55e2fc6ae46288c5eebafequal-rights-for-functional-objects.pdfparadigms/functional_programming/equal rights for functional objects2017-09-11T23:06:12.9332219242017-09-11T23:06:12.933221924<EFBFBD>r<EFBFBD>	]uOmGG
d238ce802f284a57bffb618af93d009457b8320bconcatenative-programming-an-overlooked-paradigm.pdfparadigms/functional_programming/concatenative programming an overlooked paradigm2017-09-11T23:06:12.8906689452017-09-11T23:06:12.890668945<EFBFBD>i<EFBFBD>
	]uAmEE
<01>30baa244b66e81d737ccf9f667c9bfca4f0c18f1common-ground-and-coordination-in-joint-activity.pdforganizational_simulation/common ground and coordination in joint activity2017-09-11T23:06:12.787232912017-09-11T23:06:12.78723291<EFBFBD>3<EFBFBD>		]E1=GG
~6980e1e551cadbde62454bedf5e1324032fa1e40unix-time-sharing-system.pdfoperating_systems/unix time sharing system2017-09-11T23:06:12.6897451172017-09-11T23:06:12.689745117<EFBFBD><0F>	]!1GG
zf00e7c584731135892cb1bc133672a3d63d9e095therac.pdfoperating_systems/therac2017-09-11T23:06:12.6663500982017-09-11T23:06:12.666350098
<04>
<01>e
<01><05>#<02>S%R
q<04><08><0B><0C>r
<01>
Q<00>J<EFBFBD>/	]g_GGdd0854bf535d79d51104ae3d5c19c6ac7e562180macaroons-cookies-with-contextual-caveats.pdfsecurity/macaroons cookies with contextual caveats2017-09-11T23:06:14.4265568852017-09-11T23:06:14.426556885<EFBFBD>,<2C>.	]IAGG67ea9f0fe38b6848de19578589eab498473562c3ids-evasion-ptacek-newsham.pdfsecurity/ids evasion ptacek newsham2017-09<30>`<60>	]s/kGG
<01>d62e2ae46b1cfac38357e6ce32bad7b36b0b49b4extensible-pattern-matching-extensible-language.pdfpattern_matching/extensible pattern matching extensible language2017-09-11T23:06:13.2372028812017-09-11T23:06:13.237202881<EFBFBD>a<EFBFBD>	]}uGG
<01>b7741ea891833418cc888b38f9f529bdb86409a4on-the-attraction-of-two-perfectly-conducting-plates.pdfphysics/on the attraction of two perfectly conducting plates2017-09-11T23:06:13.2988210452017-09-11T23:06:13.298821045<EFBFBD>:<3A>	]M/EGG
<01>3547ac839d02f6efe3f6f76a8289738a22528442aho-corasick-string-matching.pdfpattern_matching/aho corasick string matching2017-09-11T23:06:13.1525471192017-09-11T23:06:13.152547119<EFBFBD><1D>	]91GG
<01>30ef9946a1733c097d541ffaae8e95f0af862a08buridans-principle.pdfphysics/buridans principle2017-09-11T23:06:13.2931608892017-09-11T23:06:13.293160889.	]O/GEE997d371f1e063ff11e00fc6c0aef25955<35><1F>!	]?7GG<00>70882fa7790685902d4d8b56ba08a361f6e74eb1predicate-dispatching.pdfplt/predicate dispatching2017-09-11T23:06:13.7644509282017-09-11T23:06:13.764450928<EFBFBD>:<3A>	]O/GEE
<01>997d371f1e063ff11e00fc6c0aef259558b92303warnings-for-pattern-matching.pdfpattern_matching/warnings for pattern matching2017-09-11T23:06:13.242854982017-09-11T23:06:13.24285498<EFBFBD>E<EFBFBD>	]c[EE
<01>07ad71a8d82bf51e0b5d1d892aa6a10673a3b830on-the-electrodynamics-of-moving-bodies.pdfphysics/on the electrodynamics of moving bodies2017-09-11T23:06:13.516997072017-09-11T23:06:13.51699707<EFBFBD>d<EFBFBD>	]w/oGG<00>6848895fe48b0ca3b0bc34c1bcdf66eb58e64308compiling-pattern-matching-to-good-decision-trees.pdfpattern_matching/compiling pattern matching to good decision trees2017-09-11T23:06:13.2295769042017-09-11T23:06:13.229576904	z<00>	]?7GGc0f83a70b1c225e7705c301e1106332819bff375propositions-as-types.pdfplt/propositions as types2017-09-11T23:06:13.8390410162017-09-11T23:06:13.839041016<EFBFBD>Q<EFBFBD>"	]qiGG<00>76e1cf37ae212298802799c2c3588030d20a769fprincipal-type-schemes-for-functional-programs.pdfplt/principal type schemes for functional programs2017-09-11T23:06:13.7899331052017-09-11T23:06:13.789933105
<01>	]}uGG557b1ec3182ccb3a902cc9904a443accb438842fprogramming-languages-application-and-interpretation.pdfplt/programming languages application and interpretation2017-09-11T23:06:13.7966269532017-09-11T23:06:13.796626953A	]qiGG76e1cf37ae212298802799c2c3588030d20a769fprincipal-type-schemes-for-functional-programs.pdfplt/principal type schemes for functional programs2017-09-11T23:06:13.7899331052017-09<30><1F>%	]?7GG
<01>c0f83a70b1c225e7705c301e1106332819bff375propositions-as-types.pdfplt/propositions as types2017-09-11T23:06:13.8390410162017-09-11T23:06:13.839041016<EFBFBD>]<5D>#	]}uGG<00>557b1ec3182ccb3a902cc9904a443accb438842fprogramming-languages-application-and-interpretation.pdfplt/programming languages application and interpretation2017-09-11T23:06:13.7966269532017-09-11T23:06:13.796626953<EFBFBD>S<EFBFBD>$	]skGG
<01>b615e2186f1982009d863f3f2f98909f2f7815abprogramming-with-algebraic-effects-and-handlers.pdfplt/programming with algebraic effects and handlers2017-09-11T23:06:13.8081340332017-09-11T23:06:13.808134033<EFBFBD>]<5D> 	]}uGG<00>c1350b1680d30a7bdcb9837bff2e0e8c40f9a92aon-understanding-types-data-abstract
.<07><0F><0F>yL<0E><0E><0E>h:

<0A>
<0A>
<0A>
W
*c<0C><0C><0C>tG<0B><0B><0B><07>d7

<EFBFBD>
<EFBFBD>
<EFBFBD>
U
(	<09>5	<09>	<09>	s	F	<08><08><08>-]eaf3b1c41b5cc8bc329206a175dc5149341615d1<00>-]f55238913918c61b0dad87974699d05a5d71e709<00>-]f4b381f4482586dbdd15fc92bee81ce68bcb6898<00>-]dd0854bf535d79d51104ae3d5c19c6ac7e562180<00>-]fec6b29569eac1a340990bb07e90355efd2434ec<00>,]
fe0ae75e97abe2686e6bc8cbe94bfd08934e36da,]
fd443b2ce70c48202ba26cbc6caa471ae262e270@,]
fc11031895c302dc52404d34de58af1a72f3b817g,]
fb2db075fa0230289a4f05caf2127b95fcc9aa9c
-]f6dce666a0f64f97f380f99cba7f14e24d5f54ad<00>,]
f52e7afce70597024c3be7df105185dd59a2c8e6A,]
f5222809526d8a419a1752547880ba0a9013a8ca,]
f3485e24d796c33f11048f74e447853ef4a6dc53c,]
f3050b5586ddfec5da0d719338a6afa8b166985bP,]
f1948a2d5dc8745f725e3ba0b24e14847778cb19&,]
f16c6ce0c7eabd4f5896962335879b3932138e52S,]
f06554b06ac49f129086c8889690faaa761398bb5-]f00e7c584731135892cb1bc133672a3d63d9e095<00>,]
eee4e109fd92ea679600a61dd7d3428efa786a64m,]
eecf3aaa6aadf48778bb1daa6b09d011632b9f55*-]eb654b2087706468fe3173c4b38b940be0c85722<00>,]
e95ecb39639ce118c7ddd5bd7892378eacdd105f!,]
e76af50e96b12fc507e73b025fe9da4a99600af9,]
e51582689653f238029d984cd1780c93ef672771/-]e437aad09eb0508f015c4615e3a9c738bdee9fdf<00>,]
e36073e9e5c97e0204050c0c316d87479f94974er-]e306d45aeb2d3f72055ce72ccbebd0ccb42cdf17<00>,]
e2e60f19214efaa7d842b4a3b3b322964bf78dc7,]
e1ac8e8d810a148dc3f5291795b0ac0b114db824_-]e186a8489dc6ab1c5dd30fc0501f7866d0c3d0f1<00>,]
daf38d927e2b21c885efdb4b2cc46a2d9f47d679:,]
da731f99e05dd4f1fad1d21a1c6124efeb3bcf61o-]d7341e40b11008965d60631953ad83e89aa40584<00>,]
d65e79756ac6817d4780286045a35d34aaaaf836=-]d62e2ae46b1cfac38357e6ce32bad7b36b0b49b4<00>,]
d62de5f995164fff50f5ce61c0113f6bc9f04225-]d5c3b8b3006fc4b24e770f028c938d4bcbd62695<00>-]d4723308389e064389bc4e6aee46db5fc9b214ee<00>,]
d25c77b7d5f4b6742e63bc6f3b92ab220c833d23y-]d238ce802f284a57bffb618af93d009457b8320b<00>,]
d14dee375bc275d08b09e5b7d420c28a5ef6b47a]-]d0d8b7501d7f75613d5493d706d6d81852a73d6e<00>,]
d0cb011908e333fe17309518249be05820b5239fh,]
ce8411564f95396b503868217469e2aaf1b996c9,]
cb4710f77feed90ae01b332c492853a5b20e2c7d ,]
ca9ccbcf4a8440590a81f94295a22386a422d198\
9
K	<09><0E>
<0B>
<EFBFBD><0C><08>q<06><05>K<00>)<29><	];53GG272ef349f3b3561588a87a070de802c3c0246394affective-computing.pdfaffective-computing/affective computing2018-02-02T06:25:06.4023759772018-02-02T06:25:06.402375977<EFBFBD>e<EFBFBD>;	]w5oGGa8c4718ce66e527a5fd1726e3aea5d6c8e33efffTheories-Methods-and-Current-Research-on-Emotions.pdfaffective-computing/theories methods and current research on emotions2018-01-30T06:25:06.1424230962018-01-30T06:25:06.142423096<EFBFBD><0C>:	]#+GG855593c778f9f6c98a16afbd8e3097dbde09685cmarsyas.pdfaudio_comp_sci/marsyas2017-10-27T05:25:06.0209260252017-10-27T05:25:06.020926025<EFBFBD><0E>9	]%+GGeaf3b1c41b5cc8bc329206a175dc5149341615d1essentia.pdfaudio_comp_sci/essentia2017-10-26T05:25:05.5868701172017-10-26T05:25:05.586870117<EFBFBD>.<2E>8	]G+?EE472f436ad317b23d7bd1ad53fcb4f23e8f0997a7real-time-chord-detection.pdfaudio_comp_sci/real time chord detection2017-10-25T05:25:06.011989992017-10-25T05:25:06.01198999<EFBFBD>P<EFBFBD>7	]WOOEE16c8ad89060897e39803a175470d7990bd40cd2bpurely-functional-data-structures.pdfparadigms/functional_programming/purely functional data structures2017-10-20T05:25:05.914747072017-10-20T05:25:05.91474707<EFBFBD>,<2C>0	]G?GG
<01>b68ff86ce8591931d3bef1294f8b46dae63780adsok-eternal-war-in-memory.pdfsecurity/sok eternal war in memory2017-09-11T23:06:14.8241650392017-09-11T23:06:14.824165039<0B><00>	]#%GG59a968fa431e7117aa11005ed98ab39f1efddc30ts-asap.pdftime_series/ts asap2017-09-11T23:06:15.0964880372017-09-11T23:06:15.0964880<EFBFBD>I<EFBFBD>5	]a%YGG
1396a6cd134a7f41eeb1e5d4ca8d4edf6edfc432operators-on-inhomogeneous-time-series.pdftime_series/operators on inhomogeneous time series2017-09-11T23:06:15.0884909672017-09-11T23:06:15.088490967	]g1_GG8004558792<39>U<EFBFBD>4	]g1_GG
8004558792c00764d173dc63c03d3a391acfe6b7systematic-review-in-software-engineering.pdfsystematic_review/systematic review in software engineering2017-09-11T23:06:15.0225739752017-09-11T23:06:15.022573975<EFBFBD><0B>6	]#%GG
<01>59a968fa431e7117aa11005ed98ab39f1efddc30ts-asap.pdftime_series/ts asap2017-09-11T23:06:15.0964880372017-09-11T23:06:15.096488037<EFBFBD><02>3]<5D>7<>GG
f55238913918c61b0dad87974699d05a5d71e709An-Elementary-Proof-of-a-Theorem-of-Johnson-and-Lindenstrauss.pdfsublinear_algorithms/an elementary proof of a theorem of johnson and lindenstrauss2017-09-11T23:06:15.0059938962017-09-11T23:06:15.005993896<EFBFBD>N<EFBFBD>2	]]7UGG
<01>a5c83733c6abcd1a089bed36cf2ef38577ec55211985-Flajolet-Probabilistic-counting.pdfsublinear_algorithms/1985 flajolet probabilistic counting2017-09-11T23:06:14.9164609382017-09-11T23:06:14.916460938<EFBFBD><14>1]<5D>%/<2F>GG
<01>f4b381f4482586dbdd15fc92bee81ce68bcb68982014-ssac-pointwise-predicting-points-and-valuing-decisions-in-real-time.pdfsports_analytics/2014 ssac pointwise predicting points and valuing decisions in real time2017-09-11T23:06:14.8365629882017-09-11T23:06:14.836562988
<00>/l
m<0C><0B>
)	p<08><07>Y<05><04>7~<02>
<01>
<00><00>T
<01><17>'GGhttp://www.cs.duke.edu/courses/cps296.4/spring04/papers/Adleman94.pdfMolecular Computation of Solutions to Combinatorial Problemsbiocomputing/2017-09-11T23:06:15.2661479492017-09-11T23:06:15.266147949z	
M'GGhttp://en.wikipedia.org/wiki/Pcrwikipediabiocomputing/2017-09-11T23:06:15.2661479492017-09-11T23:06:15.266147949<EFBFBD>F

a<>+GGhttps://github.com/ibab/tensorflow-wavenet[Python] Implementation with the TensorFlow Machine Intelligence libraryaudio_comp_sci/2017-09-11T23:06:15.2434069822017-09-11T23:06:15.243406982<EFBFBD>7

W<>	+GGhttps://github.com/basveeling/wavenet[Python] Implementation with the Keras Neural Networks libraryaudio_comp_sci/2017-09-11T23:06:15.2434069822017-09-11T23:06:15.243406982<EFBFBD>6

<01>W+GGhttps://deepmind.com/blog/wavenet-generative-model-raw-audio/Announcement and interactive examplesaudio_comp_sci/2017-09-11T23:06:15.2434069822017-09-11T23:06:15.243406982<EFBFBD> 	
U_+GGhttps://arxiv.org/pdf/1609.03499.pdfWaveNet: A Generative Model for Raw Audioaudio_comp_sci/2017-09-11T23:06:15.2434069822017-09-11T23:06:15.243406982<EFBFBD>;
	
e[UGG
http://ftp.cs.ucla.edu/pub/stat_ser/r360.pdfThe algorithmization of counterfactualsartificial_intelligence/judea_pearl/2017-09-11T23:06:15.2420400392017-09-11T23:06:15.242040039<EFBFBD>>	
mYUGGhttp://ftp.cs.ucla.edu/pub/stat_ser/R218-B-L.pdfCausal diagrams for empirical researchartificial_intelligence/judea_pearl/2017-09-11T23:06:15.2420400392017-09-11T23:06:15.242040039<EFBFBD>:	
uIUGGhttp://ftp.cs.ucla.edu/pub/stat_ser/r156-reprint.pdfA theory of inferred causationartificial_intelligence/judea_pearl/2017-09-11T23:06:15.2420400392017-09-11T23:06:15.242040039<EFBFBD>[

	c<>UGGhttp://ftp.cs.ucla.edu/pub/stat_ser/r30.pdfReverend Bayes on inference engines: A distributed hierarchical approachartificial_intelligence/judea_pearl/2017-09-11T23:06:15.2420400392017-09-11T23:06:15.242040039<EFBFBD>j	
<01>!<21>=GG
http://airesearch.com/wp-content/uploads/2016/01/deepmind-mastering-go.pdfMastering the Game of Go with Deep Neural Networks and Tree Searchartificial_intelligence/2017-09-11T23:06:15.2211870122017-09-11T23:06:15.221187012<EFBFBD>	
W#=GGhttp://bayes.cs.ucla.edu/jp_home.htmlJudea Pearlartificial_intelligence/2017-09-11T23:06:15.2211870122017-09-11T23:06:15.221187012<EFBFBD>6	
yU=GGhttp://www.csee.umbc.edu/courses/471/papers/turing.pdfComputing Machinery and Intelligenceartificial_intelligence/2017-09-11T23:06:15.2211870122017-09-11T23:06:15.221187012<EFBFBD>T
<01><0B>{=GGhttps://github.com/papers-we-love/papers-we-love/blob/master/artificial_intelligence/3-bayesian-network-inference-algorithm.pdfAnalysis of Three Bayesian Network Inference Algorithms: Variable Elimination, Likelihood Weighting, and Gibbs Samplingartificial_intelligence/2017-09-11T23:06:15.2211870122017-09-11T23:06:15.221187012<EFBFBD>
<01>'<27>Q#GG	https://www.ics.uci.edu/~fielding/pubs/dissertation/fielding_dissertation.pdfArchitectural Styles and the Design of Network-based Software Architectures (REST) by Roy Fieldingapi_design/2017-09-11T23:06:15.1943510742017-09-11T23:06:15.194351074<EFBFBD>g

g<>gGGhttp://www.bodden.de/pubs/far+14flowdroid.pdfFlowDroid: Precise Context, Flow, Field, Object-sensitive and Lifecycle-aware Taint Analysis for Android Appsandroid/2017-09-11T23:06:15.1916579592017-09-11T23:06:15.191657959<EFBFBD>|

u<>GGhttp://www.cse.psu.edu/~duo114/pubs/octeau-sec13.pdfEffective Inter-Component Communication Mapping in Android with Epicc: An Essential Step Towards Holistic Security Analysisandroid/2017-09-11T23:06:15.1916579592017-09-11T23:06:15.191657959<EFBFBD>@

<01>uGGhttps://www.eecs.berkeley.edu/~daw/papers/intents-mobisys11.pdfAnalyzing Inter-Application Communication in Androidandroid/2017-09-11T23:06:15.1916579592017-09-11T23:06:15.191657959<EFBFBD>N


<01>+qGGhttp://blog.sei.cmu.edu/post.cfm/secure-coding-tools-analyzing-android-apps-118Two Secure Coding Tools for Analyzing Android Appsandroid/2017-09-11T23:06:15.1916579592017-09-11T23:06:15.191657959
/I<0E>
f<0C><0B>
<EFBFBD>
	"(
@W<04><03>/3
k<00>|#	
A%1GG)http://gigavoxels.imag.fr/Project pagecomputer_graphics/2017-09-11T23:06:15.3833239752017-09-11T23:06:15.383323975<EFBFBD>;&

<01>)91GG(http://www.cs.rpi.edu/~cutler/classes/advancedgraphics/S08/lectures/kajiya.pdfThe Rendering Equationcomputer_graphics/2017-09-11T23:06:15.3833239752017-09-11T23:06:15.383323975<EFBFBD>E%

<01>e1GG"http://www.cs.northwestern.edu/~ago820/cs395/Papers/Phong_1975.pdfIllumination for computer generated picturescomputer_graphics/2017-09-11T23:06:15.3833239752017-09-11T23:06:15.383323975<EFBFBD>Z$

<01>IW1GG!http://page.mi.fu-berlin.de/block/htw-lehre/wise2015_2016/bel_und_rend/skripte/gouraud1971.pdfContinuous shading of curved surfacescomputer_graphics/2017-09-11T23:06:15.3833239752017-09-11T23:06:15.383323975<EFBFBD>"	
q1GG'http://maverick.inria.fr/Publications/2009/CNLE09/Web pagecomputer_graphics/2017-09-11T23:06:15.3833239752017-09-11T23:06:15.383323975<EFBFBD>`!
<01><05>%1GGhttp://maverick.inria.fr/Publications/2009/CNLE09/CNLE09.pdfGigaVoxels : Ray-Guided Streaming for Efficient and Detailed Voxel Renderingcomputer_graphics/2017-09-11T23:06:15.3833239752017-09-11T23:06:15.383323975<EFBFBD>N 

<01>o1GG https://www.cs.drexel.edu/~david/Classes/CS586/Papers/p343-whitted.pdfAn Improved Illumination Model for Shaded Displaycomputer_graphics/2017-09-11T23:06:15.3833239752017-09-11T23:06:15.383323975<EFBFBD>f
<01><13>#1GGhttp://graphics.stanford.edu/papers/stabilization/karpenko_gyro.pdfDigital Video Stabilization and Rolling Shutter Correction using Gyroscopescomputer_graphics/2017-09-11T23:06:15.3833239752017-09-11T23:06:15.383323975<EFBFBD>J

a<>9GGhttp://barroso.org/publications/isca00.pdfPiranha: A Scalable Architecture Based on Single-Chip Multiprocessingcomputer_architecture/2017-09-11T23:06:15.3536550292017-09-11T23:06:15.353655029<EFBFBD>
<01>w<EFBFBD>?GGhttps://www.researchgate.net/publication/220080099_MEXICA_A_computer_model_of_a_cognitive_account_of_creative_writingMEXICA: a computer model of a cognitive account of creative writing.computational_creativity/2017-09-11T23:06:15.3451440432017-09-11T23:06:15.345144043<EFBFBD>w

<01>UiQEEhttp://www.ams.org/journals/tran/1965-117-00/S0002-9947-1965-0170805-7/S0002-9947-1965-0170805-7.pdfOn the Computational Complexity of Algorithimscomp_sci_fundamentals_and_history/2017-09-11T23:06:15.321489992017-09-11T23:06:15.32148999<EFBFBD>_

e<>)QEEhttp://www.turingarchive.org/browse.php/B/12Turing, On computable numbers, with an application to the Entscheidungsproblemcomp_sci_fundamentals_and_history/2017-09-11T23:06:15.321489992017-09-11T23:06:15.32148999<EFBFBD>l

<>)QEEhttps://www.cs.virginia.edu/~robins/Turing_Paper_1936.pdfTuring, On computable numbers, with an application to the Entscheidungsproblemcomp_sci_fundamentals_and_history/2017-09-11T23:06:15.321489992017-09-11T23:06:15.32148999<EFBFBD>a

<01>;k9GGhttp://gatekeeper.dec.com/ftp/pub/dec/SRC/publications/broder/positano-final-wpnums.pdfOn the resemblance and containment of documentsclustering_algorithms/2017-09-11T23:06:15.3145280762017-09-11T23:06:15.314528076<EFBFBD>K
<01><0F>GGhttp://adam.chlipala.net/papers/SqlcachePOPL17/SqlcachePOPL17.pdfA Program Optimization for Automatic Database Result Cachingcaching/2017-09-11T23:06:15.2910549322017-09-11T23:06:15.291054932<EFBFBD>>

Y<>#GGhttp://www.vldb.org/conf/1994/P439.PDF2Q: A Low Overhead High Performance Buffer Management Replacement Algorithmcaching/2017-09-11T23:06:15.2910549322017-09-11T23:06:15.291054932<EFBFBD>
<01>%<25>
GGhttps://github.com/papers-we-love/papers-we-love/blob/master/caching/a-constant-algorithm-for-implementing-the-lfu-cache-eviction-scheme.pdfAn O(1) algorithm for implementing the LFU cache eviction schemecaching/2017-09-11T23:06:15.2910549322017-09-11T23:06:15.291054932<EFBFBD>C

<01>)S'GGhttps://homes.cs.washington.edu/~luisceze/publications/dnastorage-asplos16.pdfA DNA-Based Archival Storage Systembiocomputing/2017-09-11T23:06:15.2661479492017-09-11T23:06:15.266147949<EFBFBD>4

<01>S'GGhttp://www.dna.caltech.edu/courses/cs191/paperscs191/turing.pdfThe chemical basis of morphogenesisbiocomputing/2017-09-11T23:06:15.2661479492017-09-11T23:06:15.266147949
<00>D<0E>
<0A><0C><<0B>
<EFBFBD>
	0S<07><06>#Q<04><03><02>C
l<00><00>\:
<01>!<21>
%GG>http://research.microsoft.com/en-us/um/people/lamport/pubs/time-clocks.pdfTime, Clocks, and the Ordering of Events in a Distributed Systemconcurrency/2017-09-11T23:06:15.4043159182017-09-11T23:06:15.404315918<EFBFBD>T9

q<>/%GG6http://sigops.org/sosp/sosp13/papers/p33-david.pdfEverything You Always Wanted to Know About Synchronization but Were Afraid to Askconcurrency/2017-09-11T23:06:15.4043159182017-09-11T23:06:15.404315918<EFBFBD>88	
os-GG5http://www.sci.utah.edu/~bsumma/projects/weaving/Panorama Weaving:
Fast and Flexible Seam Processingcomputer_vision/2017-09-11T23:06:15.4028640142017-09-11T23:06:15.402864014<EFBFBD>b7

<01>As-GG4http://www.disneyresearch.com/project/high-quality-single-shot-capture-of-facial-geometry/High-Quality Single-Shot Capture of Facial Geometrycomputer_vision/2017-09-11T23:06:15.4028640142017-09-11T23:06:15.402864014<EFBFBD>l6

<01>K}-GG3http://www.disneyresearch.com/project/coupled-3d-reconstruction-of-sparse-facial-hair-and-skin/Coupled 3D Reconstruction of Sparse Facial Hair and Skincomputer_vision/2017-09-11T23:06:15.4028640142017-09-11T23:06:15.402864014}5	=-1GGhttp://shapegrammar.org/shapegrammar.orgcomputer_graphics/2017-09-11T23:06:15.3833239752017-09-11T23:06:15.383323975<EFBFBD>O4

k<>1GG/http://shapegrammar.org/ifip/SGBestPapers72.pdfShape Grammars and the Generative Specification of Painting and Sculpturecomputer_graphics/2017-09-11T23:06:15.3833239752017-09-11T23:06:15.383323975<EFBFBD>D3	
w1GG1http://cs.brown.edu/courses/csci2370/2000/1999/cabral.pdfImaging Vector Fields Using Line Integral Convolutioncomputer_graphics/2017-09-11T23:06:15.3833239752017-09-11T23:06:15.383323975<EFBFBD>"2

<01>!1GG-http://peterwonka.net/Publications/pdfs/2014.SG.Lipp.PushPull.pdfPushPull++computer_graphics/2017-09-11T23:06:15.3833239752017-09-11T23:06:15.383323975<EFBFBD>A1

<01>951GG0http://www.peterwonka.net/Publications/pdfs/2003.SG.Wonka.InstantArchitecture.high.pdfInstant Architecturecomputer_graphics/2017-09-11T23:06:15.3833239752017-09-11T23:06:15.383323975<EFBFBD>Z0

<01>SM1GG2http://www.peterwonka.net/Publications/pdfs/2006.SG.Mueller.ProceduralModelingOfBuildings.final.pdfProcedural Modeling of Buildingscomputer_graphics/2017-09-11T23:06:15.3833239752017-09-11T23:06:15.383323975<EFBFBD>g/
<01>%<25>1GG.http://www.proun-game.com/Oogst3D/CODING/InteriorMapping/InteriorMapping.pdfInterior Mapping: A new technique for rendering realistic buildingscomputer_graphics/2017-09-11T23:06:15.3833239752017-09-11T23:06:15.383323975<EFBFBD>O.
<01>
<01>1GG,http://research.microsoft.com/en-us/um/people/cohen/bs.pdfInteractive Horizon Mapping: Shadows for bump-mapped surfacescomputer_graphics/2017-09-11T23:06:15.3833239752017-09-11T23:06:15.383323975<EFBFBD>;-

<01>]1GG+http://www.crytek.com/download/Light_Propagation_Volumes.pdfLight Propagation Volumes in CryEngine 3computer_graphics/2017-09-11T23:06:15.3833239752017-09-11T23:06:15.383323975<EFBFBD>,	
w1GG*https://github.com/luanfujun/deep-photo-styletransferCodecomputer_graphics/2017-09-11T23:06:15.3833239752017-09-11T23:06:15.383323975<EFBFBD>+	
U?1GG%https://arxiv.org/pdf/1703.07511.pdfDeep Photo Style Transfercomputer_graphics/2017-09-11T23:06:15.3833239752017-09-11T23:06:15.383323975<EFBFBD>b*

<01>3}1GG$http://www.cs.tau.ac.il/~dcor/articles/2013/3-Sweep-Extracting-Editable-Objects.pdf3-Sweep: Extracting Editable Objects from a Single Photocomputer_graphics/2017-09-11T23:06:15.3833239752017-09-11T23:06:15.383323975<EFBFBD>q)
<01><15>71GG&http://research.microsoft.com/pubs/155416/kinectfusion-uist-comp.pdfKinectFusion: Real-time 3D Reconstruction and Interaction Using a Moving Depth Cameracomputer_graphics/2017-09-11T23:06:15.3833239752017-09-11T23:06:15.383323975<EFBFBD>(

<01>1GG*http://www.cs.jhu.edu/~misha/Code/PoissonRecon/Version5.71/Codecomputer_graphics/2017-09-11T23:06:15.3833239752017-09-11T23:06:15.383323975<EFBFBD>9'

<01>I1GG#http://research.microsoft.com/en-us/um/people/hoppe/poissonrecon.pdfPoisson surface reconstructioncomputer_graphics/2017-09-11T23:06:15.3833239752017-09-11T23:06:15.383323975

17<0F>3i
V/<0E><0E>{Q
<0A>
i
7<0C><0C>
<01>L<0B><00><0B>j-
<EFBFBD>
<EFBFBD>
g
/	<09>	<09>	q	>	
<08><08>T<07>fg+<06><06>uP
<05>w8<04><04>i<03><03><02>h1X<04>1http://breachattack.com/resources/BREACH%20-%20SSL,%20gone%20in%2030%20seconds.pdf
X<04>1http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.24.9333&rep=rep1&type=pdf<00>
<01>%http://infoscience.epE<04>http:/:whttp://algo.inria.fr/flajolet/Publications/FlMa85.pdf
1http://homepages.inX<04>1http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.13.9460&rep=rep1&type=pdf
._http://en.wikipedia.org/wiki/Suffix_array

http://home.pipeline.com/~hbaker1/NoMotionGC.html<00>W<04>/http://haskell.cs.yale.edu/wp-content/uploads/2012/08/Winograd-Cort-Wormholes.pdf<00>K<04>http://haskell.cs.yale.edu/wp-content/uploads/2011/02/workshop-02.pdf<00>F<04>
http://haskell.cs.yale.edu/wp-cont3ihttp://affect.media.mit.edu/pdfs/95.picard.pdf
/)Uhttp://dreammachin.es/p1-wallace.pdf
+)Uhttp://futuredata.stanford.edu/asap/
\<04>;
http://gatekeeper.dec.com/ftp/pub/dec/SRC/publications/broder/positano-final-wpnums.pdfP<04>!http://gamification-research.org/wp-content/uploads/2011/04/12-Gerling.pdf<00>0e
http://ftp.cs.ucla.edu/pub/stat_ser/r360.pdf
/c
http://ftp.cs.ucla.edu/pub/stat_ser/r30.pdf
8u
http://ftp.cs.ucla.edu/pub/stat_ser/r156-reprint.pdf4m
http://ftp.cs.ucla.edu/pub/stat_ser/R218-B-L.pdf>http://frenchy64.github.io/papers/typed-clojure-draft.pdf<00>X<04>3
http://faculty.salisbury.edu/~xswang/Research/Papers/SERelated/no-silver-bullet.pdfg9uhttp://erlang.org/download/armstrong_thesis_2003.pdf<00>E<04>http://eprints.eemcs.utwente.nl/7281/01/db-utwente-40501F46.pdf<00>$M
http://en.wikipedia.org/wiki/PcrF<04>
http://en.wikipedia.org/wiki/Moving_magnet_and_conductor_problem<00>5o
http://en.wikipedia.org/wiki/HOL_(proof_assistant?8shttp://en.wikipedia.org/wiki/Empirical_algorithmics<00>:whttp://eb.host.cs.st-andrews.ac.uk/drafts/effects.pdf<00>x<04>qhttp://dl.dropboxusercontent.com/u/220532/MindTrek_Gamification_PrinterReady_110806_SDE_accepted_LEN_changes_1.pdf<00>t<04>k
http://diyhpl.us/~bryan/papers2/distributed/distributed-systems/zab.totally-ordered-broadcast-protocol.2008.pdfj<{http://dig.cs.illinois.edu/papers/lambdaRefactoring.pdf<00>*Whttp://ddg.jaist.ac.jp/pub/HDY+04.pdf<00>M<04>http://db.disi.unitn.eu/pages/VLDBProgram/pdf/industry/p871-curtiss.pdf<00>3ihttp://davidsjohnson.net/papers/experguide.pdf<00>2ghttp://cseweb.ucsd.edu/~vahdat/papers/mop.pdf<00>F<04>
http://cs.yale.edu/homes/thomson/publications/calvin-sigmod12.pdfR8u
http://cs.brown.edu/~mph/HerlihyW90/p463-herlihy.pdfo=
http://cs.brown.edu/courses/csci2370/2000/1999/cabral.pdf37qhttp://cs.au.dk/~hosc/local/LaSC-4-3-pp223-242.pdf<00>=
http://cs-www.cs.yale.edu/homes/dna/papers/vll-vldb13.pdfWF<04>
http://cs-www.cs.yale.edu/homes/dna/papers/determinism-vldb10.pdfT@<04>
http://cs-www.cs.yale.edu/homes/dna/papers/abadi-pacelc.pdfU<{http://conal.net/papers/push-pull-frp/push-pull-frp.pdf<00>C<04>http://community.haskell.org/~simonmar/papers/parallel-gc.pdf<00>E<04>http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.148.524<00>W<04>1
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.21.2707&rep=rep1&type=pdfeX<04>3
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.161.6751&rep=rep1&type=pdfXX<04>3
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.108.1302&rep=rep1&type=pdf;8u
http://cidrdb.org/cidr2015/Papers/CIDR15_Paper16.pdfL1ehttp://chaoran.me/assets/pdf/wfq-ppopp16.pdf<00>S<04>+	http://blog.sei.cmu.edu/post.cfm/secure-coding-tools-analyzing-android-apps-118<31><04>%http://bitsavers.informatik.uni-stuttgart.de/pdf/xerox/parc/techReports/CSL-89-1_Epidemic_Algorithms_for_Replicated_Database_Maintenance.pdf<00>)W
http://bayes.cs.ucla.edu/jp_home.html.a
http://barroso.org/publications/isca00.pdf;yhttp://asc.di.fct.unl.pt/~jleitao/pdf/dsn07-leitao.pdf<00>$Khttp://arxiv.org/abs/1507.02988<00>#Ihttp://arxiv.org/abs/1004.4240<00>9uhttp://anil.recoil.org/papers/2013-asplos-mirage.pdf<00>O<04>!
http://airesearch.com/wp-content/uploads/2016/01/deepmind-mastering-go.pdf	F<04>
http://adam.chlipala.net/papers/SqlcachePOPL17/SqlcachePOPL17.pdf
9<00>%
~<03><03>:<00><02><0F>|E<0E>r<
<01>
<0A>
<0A>
v
<
<0C><0C>
F
c)<0B><0B>b[
<EFBFBD>
|
C	<09>	<09>	<09>	_	 <08><08>S6<07><07>h$<06><06>F<05><05>B<04><04>nB<04>http://i<04>U
http://www.cs.duke.edu/courses/cps3_<04>A
http://static.googleuserc@<04>
http://homepages.inf.ed.ac.uk/slindley/papers/handlers.pdf
$5mhttp://okmij.org/ftp/Haskell/extensible/more.pdf
 7qhttp://okmij.org/ftp/Haskell/extensible/exteff.pdf
[<04>7http://haskell.cs.yale.edu/wp-content/uploads/2011/02/POPL96-Modular-interpreters.pdf
N<04>http://lafo.ssw.uni-linz.ac.at/papers/2013_Onward_OneVMToRuleThemAll.pdf
8shttp://ordiecole.com/squeak/cardelli_squeak1985.pdf
>http://papers.ssrn.com/sol3/papers.cfm?abstract_id=208278
a<04>Chttp://homepages.inf.ed.ac.uk/wadler/papers/propositions-as-types/propositions-as-types.pdf<00>6ohttp://home.pipeline.com/~hbaker1/NoMotionGC.html<00>W<04>/http://haskell.cs.yale.edu/wp-content/uploads/2012/08/Winograd-Cort-Wormholes.pdf<00>K<04>http://haskell.cs.yale.edu/wp-content/uploads/2011/02/workshop-02.pdf<00>F<04>
http://haskell.cs.yale.edu/wp-content/uploads/2011/02/rt-frp.pdf<00>H<04>
http://graphics.stanford.edu/papers/stabilization/karpenko_gyro.pdfD<04>
http://research.microsoft.com/pubs/79348/presto27-greenberg.pdffD<04>	http://research.microsoft.com/pubs/255833/IronFleet-twocol.pdf<00>I<04>
http://research.microsoft.com/pubs/155416/kinectfusion-uist-comp.pdf)a<04>Chttp://research.microsoft.com/en-us/um/people/simonpj/papers/history-of-haskell/history.pdf<00>O<04>!
http://research.microsoft.com/en-us/um/people/lamport/pubs/time-clocks.pdf:Q<04>%
http://research.microsoft.com/en-us/um/people/lamport/pubs/lamport-paxos.pdfI<04>
http://research.microsoft.com/en-us/um/people/hoppe/poissonrecon.pdf'S<04>)
http://research.microsoft.com/en-us/um/people/fournet/papers/join-tutorial.pdf~?<04>

http://research.microsoft.com/en-us/um/people/cohen/bs.pdf.C<04>	
http://research.microsoft.com/apps/pubs/default.aspx?id=210931t5o
http://research.google.com/pubs/archive/41684.pdfsU<04>+http://repository.upenn.edu/cgi/viewcontent.cgi?article=1162&context=cis_papers<00>A<04>http://rd.springer.com/content/pdf/10.1007%2FBF00994018.pdf<00>;http://racket-lang.org/<00>Q<04>%
http://publications.lib.chalmers.se/records/fulltext/125252/local_125252.pdf=3ihttp://plosworkshop.org/2013/preprint/kell.pdf<00>F<04>
http://peterwonka.net/Publications/pdfs/2014.SG.Lipp.PushPull.pdf2>http://people.seas.harvard.edu/~chong/pubs/pldi13-elm.pdf<00>2ghttp://people.inf.elte.hu/center/fulltext.pdf<00>8shttp://people.ee.duke.edu/~lcarin/Lihan4.21.06a.pdf<00>3k
http://people.csail.mit.edu/rivest/Rsapaper.pdfDC<04>	
http://people.csail.mit.edu/matei/papers/2013/sosp_sparrow.pdf{8shttp://people.csail.mit.edu/jrb/Projects/dexprs.pdf<00>A<04>
http://people.cs.umass.edu/~emery/pubs/berger-asplos2000.pdfqG<04>
http://pdos.csail.mit.edu/papers/chord:sigcomm01/chord_sigcomm.pdflT<04>)http://pdf.aminer.org/000/465/194/incremental_collection_of_mature_objects.pdf<00>J<04>http://patrickthomson.ghost.io/an-introduction-to-recursion-schemes/<00>X<04>3
http://pages.cs.wisc.edu/~remzi/Classes/739/Spring2004/Papers/optimistic-survey.pdfdc<04>I
http://page.mi.fu-berlin.de/block/htw-lehre/wise2015_2016/bel_und_rend/skripte/gouraud1971.pdf$@<04>
http://orbit.dtu.dk/files/102419168/abstract_ELB_trees.pdf<00>-_
http://notes.stephenholiday.com/Kafka.pdfm2i
http://nms.lcs.mit.edu/papers/ron-sosp2001.pdfy6ohttp://msl.cs.uiuc.edu/~lavalle/papers/Lav98c.pdf<00>9w
http://mcg.cs.tau.ac.il/papers/disc2008-hopscotch.pdfQA<04>
http://maverick.inria.fr/Publications/2009/CNLE09/CNLE09.pdf!6q
http://maverick.inria.fr/Publications/2009/CNLE09/"L<04>http://luthuli.cs.uiuc.edu/~daf/courses/Signals%20AI/Papers/HMMs/0.pdf
5o
http://kowshik.github.io/JPregel/pregel_paper.pdfwG<04>http://jeffreymbradshaw.net/publications/Common_Ground_Single.pdf<00>J<04>http://infoscience.epfl.ch/record/83409/files/neg--1184036295all.pdf<00>?<04>

http://infoscience.epfl.ch/record/169879/files/RMTrees.pdfO6ohttp://ilpubs.stanford.edu:8090/422/1/1999-66.pdf<00>E<04>http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5350749<00>=}http://homes.cs.washington.edu/~pedrod/papers/cacm12.pdf<00>
`m
<0A><0C>P<0B>
<EFBFBD>	<09>	2a<07><06>b<04>`p<02>
<01>
,<00>IK
<01><07>
%GGPhttps://www.cs.unc.edu/~welch/kalman/media/pdf/Kalman1960.pdfA New Approach to Linear Filtering and Prediction Problemsdata_fusion/2017-09-11T23:06:15.4521950682017-09-11T23:06:15.452195068<EFBFBD>6O

<01>
[-GGIhttp://infoscience.epfl.ch/record/169879/files/RMTrees.pdfRRB-Trees: Efficient Immutable Vectorsdata_structures/2017-09-11T23:06:15.4833059082017-09-11T23:06:15.483305908<EFBFBD>aN
<01>
<01>/-GG@http://www.research.ibm.com/people/m/michael/podc-1996.pdfSimple, Fast, and Practical Non-Blocking and Blocking Concurrent Queue Algorithmsdata_structures/2017-09-11T23:06:15.4833059082017-09-11T23:06:15.483305908<EFBFBD>$M

<01>3-GGLhttp://www.csd.uoc.gr/~hy460/pdf/Dynamic%20Hash%20Tables.pdfDynamic Hash Tablesdata_structures/2017-09-11T23:06:15.4833059082017-09-11T23:06:15.483305908<EFBFBD>(L	
uK/GGHhttp://cidrdb.org/cidr2015/Papers/CIDR15_Paper16.pdfImmutability Changes Everythingdata_replication/2017-09-11T23:06:15.4544541022017-09-11T23:06:15.454454102<EFBFBD>;J

<01>e'GGGhttp://www.cs.bell-labs.com/who/dmr/pdfs/shannoncryptshrt.pdfA Mathematical Theory of Cryptography (1945)cryptography/2017-09-11T23:06:15.4059790042017-09-11T23:06:15.405979004<EFBFBD>I	
U/'GGFhttps://eprint.iacr.org/2016/461.pdfNTRU Prime (2016)cryptography/2017-09-11T23:06:15.4059790042017-09-11T23:06:15.405979004<EFBFBD>7H	
ym'GGDhttp://web.cs.ucdavis.edu/~rogaway/papers/moral-fn.pdfThe Moral Character of Cryptographic Work (2015)cryptography/2017-09-11T23:06:15.4059790042017-09-11T23:06:15.405979004<EFBFBD>QG
<01><05>'GGChttp://www.cs.tau.ac.il/~tromer/papers/acoustic-20131218.pdfRSA Key Extraction via Low-Bandwidth Acoustic Cryptanalysis (2013)cryptography/2017-09-11T23:06:15.4059790042017-09-11T23:06:15.405979004<EFBFBD>-F	
{W'GGEhttp://www-ee.stanford.edu/~hellman/publications/24.pdfNew Directions in Cryptography (1976)cryptography/2017-09-11T23:06:15.4059790042017-09-11T23:06:15.405979004<EFBFBD>>E	
{y'GGAhttps://crypto.stanford.edu/~dabo/papers/RSA-survey.pdfTwenty Years of Attacks on the RSA Cryptosystem (1999)cryptography/2017-09-11T23:06:15.4059790042017-09-11T23:06:15.405979004<EFBFBD>ND

k<>''GG?http://people.csail.mit.edu/rivest/Rsapaper.pdfA Method for Obtaining Digital Signatures and Public-Key Cryptosystems (1977)cryptography/2017-09-11T23:06:15.4059790042017-09-11T23:06:15.405979004<EFBFBD>JC

<01>'g#GG=https://www.usenix.org/legacy/event/osdi04/tech/full_papers/candea/candea.pdfMicroreboot -- A technique for cheap recoverycrash_only/2017-09-11T23:06:15.4053081052017-09-11T23:06:15.405308105<EFBFBD>2B

<01>+3#GGBhttps://www.usenix.org/legacy/events/hotos03/tech/full_papers/candea/candea.pdfCrash-Only Softwarecrash_only/2017-09-11T23:06:15.4053081052017-09-11T23:06:15.405308105<EFBFBD>aA
<01>	<09>/%GG@http://www.cs.rochester.edu/~scott/papers/1996_PODC_queues.pdfSimple, Fast, and Practical Non-Blocking and Blocking Concurrent Queue Algorithmsconcurrency/2017-09-11T23:06:15.4043159182017-09-11T23:06:15.404315918<EFBFBD>5@	
{i%GG<https://people.eecs.berkeley.edu/~brewer/cs262/Mesa.pdfExperience with Processes and Monitors in Mesaconcurrency/2017-09-11T23:06:15.4043159182017-09-11T23:06:15.404315918<EFBFBD>?	
o%GG;http://en.wikipedia.org/wiki/HOL_(proof_assistantHOLconcurrency/2017-09-11T23:06:15.4043159182017-09-11T23:06:15.404315918<EFBFBD>7>	
us%GG9http://www.cl.cam.ac.uk/~pes20/weakmemory/popl09.pdfThe Semantics of x86-CC Multiprocessor Machine Codeconcurrency/2017-09-11T23:06:15.4043159182017-09-11T23:06:15.404315918<EFBFBD>Y=
<01>%<25>%GG8http://publications.lib.chalmers.se/records/fulltext/125252/local_125252.pdfFinding Race Conditions in Erlang with QuickCheck and PULSEconcurrency/2017-09-11T23:06:15.4043159182017-09-11T23:06:15.404315918<EFBFBD>'<	
i_%GG:http://user.it.uu.se/~kostis/Papers/escape.pdfMessage Analysis for Concurrent Languagesconcurrency/2017-09-11T23:06:15.4043159182017-09-11T23:06:15.404315918<EFBFBD>f;
<01>3<EFBFBD>%GG7http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.108.1302&rep=rep1&type=pdfHeap Architectures For Concurrent Languages Using Message Passingconcurrency/2017-09-11T23:06:15.4043159182017-09-11T23:06:15.404315918
ef<0E>
<0A>
>~<0B>
D	i<08><07><06>?<04><03>e<02>
<01>
6<00>N`

}<7D>#GG`http://www.erlang.org/download/armstrong_thesis_2003.pdfMaking Reliable Distributed Systems in the Presence of Software Errorsdatastores/2017-09-11T23:06:15.5087839362017-09-11T23:06:15.508783936<EFBFBD>?c

<01>%S#GG]https://amplab.cs.berkeley.edu/wp-content/uploads/2013/03/mdcc-eurosys13.pdfMDCC: Multi-Data Center Consistencydatastores/2017-09-11T23:06:15.5087839362017-09-11T23:06:15.508783936<EFBFBD>~b
<01>U<EFBFBD>#GG^http://www.cs.duke.edu/courses/cps399.28/current/papers/sigmod07-YangDasdanEtAl-map_reduce_merge.pdfMap-Reduce-Merge: Simplified Relational Data Processing on Large Clustersdatastores/2017-09-11T23:06:15.5087839362017-09-11T23:06:15.508783936<EFBFBD>ba
<01><0F>-#GG[http://zoo.cs.yale.edu/classes/cs422/2013/bib/terry95managing.pdfManaging Update Conflicts in Bayou, a Weakly Connected Replicated Storage Systemdatastores/2017-09-11T23:06:15.5087839362017-09-11T23:06:15.508783936<EFBFBD>,_	
W}#GG\http://www.few.vu.nl/~kgr700/sdd1.pdfIntroduction to a System for Distributed Databases SDD-1datastores/2017-09-11T23:06:15.5087839362017-09-11T23:06:15.508783936<EFBFBD>/^	
gs#GGYhttps://cs.uwaterloo.ca/~bernard/hyperdex.pdfHyperDex: A Distributed, Searchable Key-Value Storedatastores/2017-09-11T23:06:15.5087839362017-09-11T23:06:15.508783936<EFBFBD>L]
<01>	<09>#GGZhttp://www.ics.uci.edu/~yingyib/papers/HaLoop_camera_ready.pdfHaLoop: Efficient Iterative Data Processing on Large Clustersdatastores/2017-09-11T23:06:15.5087839362017-09-11T23:06:15.508783936<EFBFBD>T\

<01>Aa#GGXhttp://static.googleusercontent.com/media/research.google.com/en/us/pubs/archive/41344.pdfF1: A Distributed SQL Database That Scalesdatastores/2017-09-11T23:06:15.5087839362017-09-11T23:06:15.508783936<EFBFBD>\[

<01>Aq#GGUhttp://static.googleusercontent.com/media/research.google.com/en/us/pubs/archive/36632.pdfDremel: Interactive Analysis of Web-Scale Datasetsdatastores/2017-09-11T23:06:15.5087839362017-09-11T23:06:15.508783936<EFBFBD>[Z

s<>=#GGThttp://www.cs.cmu.edu/~dga/papers/cops-sosp2011.pdfDon’t Settle for Eventual: Scalable Causal Consistency for Wide-Area Storage with COPSdatastores/2017-09-11T23:06:15.5087839362017-09-11T23:06:15.508783936<EFBFBD>DY

g<>#GGShttp://www.ssrc.ucsc.edu/Papers/weil-sc06.pdfCRUSH: Controlled, Scalable, Decentralized Placement of Replicated Datadatastores/2017-09-11T23:06:15.5087839362017-09-11T23:06:15.508783936<EFBFBD>XX

<01>3w#GGVhttp://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.161.6751&rep=rep1&type=pdfCassandra - A Decentralized Structured Storage Systemdatastores/2017-09-11T23:06:15.5087839362017-09-11T23:06:15.508783936<EFBFBD><W	
u#GGRhttp://cs-www.cs.yale.edu/homes/dna/papers/vll-vldb13.pdfLightweight Locking for Main Memory Database Systemsdatastores/2017-09-11T23:06:15.5087839362017-09-11T23:06:15.508783936<EFBFBD>'V	
uU#GGWhttp://sites.computer.org/debull/A13june/calvin1.pdfModularity and Scalability in Calvindatastores/2017-09-11T23:06:15.5087839362017-09-11T23:06:15.508783936<EFBFBD>NU
<01><03>#GGQhttp://cs-www.cs.yale.edu/homes/dna/papers/abadi-pacelc.pdfConsistency Tradeoffs in Modern Distributed Database System Designdatastores/2017-09-11T23:06:15.5087839362017-09-11T23:06:15.508783936<EFBFBD>=T

<01>e#GGOhttp://cs-www.cs.yale.edu/homes/dna/papers/determinism-vldb10.pdfThe Case for Determinism in Database Systemsdatastores/2017-09-11T23:06:15.5087839362017-09-11T23:06:15.508783936<EFBFBD>-S	
w_#GGMhttp://www-bcf.usc.edu/~wyattllo/papers/f4-osdi14.pdff4: Facebook’s Warm BLOB Storage Systemdatastores/2017-09-11T23:06:15.5087839362017-09-11T23:06:15.508783936<EFBFBD>XR
<01><0F>#GGNhttp://cs.yale.edu/homes/thomson/publications/calvin-sigmod12.pdfCalvin: Fast Distributed Transactions for Partitioned Database Systemsdatastores/2017-09-11T23:06:15.5087839362017-09-11T23:06:15.508783936<EFBFBD>Q	
w/-GGKhttp://mcg.cs.tau.ac.il/papers/disc2008-hopscotch.pdfHopscotch Hashingdata_structures/2017-09-11T23:06:15.4833059082017-09-11T23:06:15.483305908<EFBFBD>P	
w)-GGJhttp://www.it-c.dk/people/pagh/papers/cuckoo-jour.pdfCuckoo Hashingdata_structures/2017-09-11T23:06:15.4833059082017-09-11T23:06:15.483305908

<01>/Dv
<0A><0C><0B>
<01>
Q	<09><08><07><06>(C<00>O/m<02><00>Is

o<>5GGnhttp://research.google.com/pubs/archive/41684.pdfOmega: flexible, scalable schedulers for large compute clustersdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>Wq
<01><05>5GGmhttp://people.cs.umass.edu/~emery/pubs/berger-asplos2000.pdfHoard: A Scalable Memory Allocator for Multithreaded Applicationsdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<02><00>e5GGhttp://www<77>/i	
}K5GGrhttp://www.eecs.harvard.edu/~waldo/Readings/waldo-94.pdfA Note on Distributed Computingdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109G<00>
<01>e5GGphttp://www.cs.utexas.edu/users/lorenzo/corsi/cs380d/papers/paper2-1.pdfPaxos Made Live - An Engineering Perspectivedistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>_t
<01>	<09>5GGohttp://research.microsoft.com/apps/pubs/default.aspx?id=210931Orleans: Distributed Virtual Actors for Programmability and Scalabilitydistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>qr
<01>A<EFBFBD>5GGkhttp://static.googleusercontent.com/media/research.google.com/en/us/pubs/archive/41378.pdfMillWheel: Fault-Tolerant Stream Processing at Internet Scaledistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>bp

}<7D>/5GGlhttps://www.cs.cornell.edu/fbs/publications/SMSurvey.pdfImplementing Fault-Tolerant Services Using the State Machine Approach: A Tutorialdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>Lo

u<>5GGjhttp://cs.brown.edu/~mph/HerlihyW90/p463-herlihy.pdfLinearizability: A Correctness Condition for Concurrent Objectsdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>en

<01>Aq5GGihttp://static.googleusercontent.com/media/research.google.com/en/us/pubs/archive/43438.pdfLarge-scale cluster management at Google with Borgdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>9m	
_}5GGghttp://notes.stephenholiday.com/Kafka.pdfKafka: a Distributed Messaging System for Log Processingdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>cl
<01><11>5GGhhttp://pdos.csail.mit.edu/papers/chord:sigcomm01/chord_sigcomm.pdfChord: A Scalable Peer-to-peer Lookup Service for Internet Applicationsdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>Mk

<01>
u5GGfhttp://www.eecs.berkeley.edu/Pubs/TechRpts/2009/EECS-2009-28.pdfAbove the Clouds: A Berkeley View of Cloud Computingdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>sj

<01>kc5GGehttp://diyhpl.us/~bryan/papers2/distributed/distributed-systems/zab.totally-ordered-broadcast-protocol.2008.pdfA simple totally ordered broadcast protocoldistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<00>}K5GGhttp://www.eecs.harvard.edu/~waldo/Readings/waldo-94.pdfA Note on Distributed Computingdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>0h

<01>
aGGchttp://scg.unibe.ch/archive/papers/Duca06bTOPLASTraits.pdfTraits: A Mechanism for Fine-Grained Reusedesign/2017-09-11T23:06:15.5506918952017-09-11T23:06:15.550691895<EFBFBD>bg
<01>3<EFBFBD>GGbhttp://faculty.salisbury.edu/~xswang/Research/Papers/SERelated/no-silver-bullet.pdfNo Silver Bullet — Essence and Accidents of Software Engineeringdesign/2017-09-11T23:06:15.5506918952017-09-11T23:06:15.550691895<EFBFBD>cf
<01><0B>3#GGahttp://research.microsoft.com/pubs/79348/presto27-greenberg.pdfTowards a Next Generation Data Center Architecture: Scalability and Commoditizationdatastores/2017-09-11T23:06:15.5087839362017-09-11T23:06:15.508783936<EFBFBD>Ke

<01>1_#GGdhttp://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.21.2707&rep=rep1&type=pdfThe Dangers of Replication and a Solutiondatastores/2017-09-11T23:06:15.5087839362017-09-11T23:06:15.508783936<EFBFBD>9d

<01>39#GG_http://pages.cs.wisc.edu/~remzi/Classes/739/Spring2004/Papers/optimistic-survey.pdfOptimistic replicationdatastores/2017-09-11T23:06:15.5087839362017-09-11T23:06:15.508783936
.<03><07><07>z<<06>i	<05>I<04><04><0F><0F><03>^f<0E><0E>g
<0A>
<0A>
U
#<0C><0C>^%<0B><0B>]
<EFBFBD>
<EFBFBD>
e
	<09>	o	'<08><03><08>_<02>q,
<01>
<01>
Y
<00>	<00><04>http://www.elizabete.com.br/site/Outros/Entradas/2012/11/19_Revisao_Sistematica_files/ConceitosRevisaoSistematica_Biolchini.pdf
<}
http://www.eecs.harvard.edu/~waldo/Readings/waldo-94.pdfiE<04>

http://www.eecs.berkeley.edu/Pubs/TechRpts/2009/EECS-2009-28.pdfkC<04>http://www.ee.columbia.edu/~dpwe/pubs/BarkCE05-sfd-spcomm.pdf
H<04>http://www.ece.cmu.edu/~ganger/712.fall02/papers/p761-thompson.pdf<00>D<04>
http://www.dna.caltech.edu/courses/cs191/paperscs191/turing.pdfH<04>http://www.diva-portal.org/smash/get/diva2:392243/FULLTEXT01.pdfOn<00>_<04>A
http://www.disneyresearch.com/project/high-quality-single-shot-capture-of-facial-geometry/7d<04>K
http://www.disneyresearch.com/project/coupled-3d-reconstruction-of-sparse-facial-hair-and-skin/6;yhttp://www.csl.mtu.edu/cs646=}http://web.cecs.pdx.edu/~mpj/pubs/composing-fractals.pdf
'>http://www.cs.ox.ac.uk/people/nicolas.wu/papers/Scope.pdf
"I<04>http://www.cs.ru.nl/~W.Swierstra/Publications/DataTypesALaCarte.pdf
!K<04>http://web.media.mit.edu/~minsky/papers/Why%20programming%20is--.html
6ohttp://trec.nist.gov/pubs/trec3/papers/city.ps.gz<00>_<04>A
http://static.googleusercontent.com/media/research.google.com/en/us/pubs/archive/43438.pdfn_<04>A
http://static.googleusercontent.com/media/research.google.com/en/us/pubs/archive/41378.pdfr_<04>A
http://static.googleusercontent.com/media/research.google.com/en/us/pubs/archive/41344.pdf\_<04>A
http://static.googleusercontent.com/media/research.google.com/en/us/pubs/archive/36632.pdf[b<04>G
http://static.googleusercontent.com/media/research.google.com/en/us/archive/chubby-osdi06.pdf}8u
http://sites.computer.org/debull/A13june/calvin1.pdfV6q
http://sigops.org/sosp/sosp13/papers/p33-david.pdf9=
http://sigops.org/sosp/sosp13/papers/p151-mashtizadeh.pdfx3k
http://shapegrammar.org/ifip/SGBestPapers72.pdf4=
http://shapegrammar.org/5?<04>

http://scg.unibe.ch/archive/papers/Duca06bTOPLASTraits.pdfhS<04>'http://researcher.watson.ibm.com/researcher/files/us-bacon/Bacon12AndThen.pdf<00>S<04>)
http://www.cs.rpi.edu/~cutler/classes/advancedgraphics/S08/lectures/kajiya.pdf&C<04>	
http://www.cs.rochester.edu/~scott/papers/1996_PODC_queues.pdfA/ahttp://www.cs.nyu.edu/~mohri/pub/csl01.pdf
G<04>
http://www.cs.northwestern.edu/~ago820/cs395/Papers/Phong_1975.pdf%@<04>
http://www.cs.jhu.edu/~misha/Code/PoissonRecon/Version5.71/(i<04>U
http://www.cs.duke.edu/courses/cps399.28/current/papers/sigmod07-YangDasdanEtAl-map_reduce_merge.pdfbJ<04>
http://www.cs.duke.edu/courses/cps296.4/spring04/papers/Adleman94.pdf=}http://www.cs.cornell.edu/~asdas/research/dsn02-swim.pdf<00>=}http://www.cs.cornell.edu/home/rvr/papers/flowgossip.pdf<00>7s
http://www.cs.cmu.edu/~dga/papers/cops-sosp2011.pdfZC<04>http://www.cs.berkeley.edu/~franklin/Papers/p315-franklin.pdf<00>B<04>
http://www.cs.bell-labs.com/who/dmr/pdfs/shannoncryptshrt.pdfJA<04>
http://www.crytek.com/download/Light_Propagation_Volumes.pdf-B<04>http://www.comp.lancs.ac.uk/~elkhatib//Docs/2014.06_Netw.pdf<00>8u
http://www.cl.cam.ac.uk/~pes20/weakmemory/popl09.pdf>H<04>http://www.cl.cam.ac.uk/research/srg/netos/papers/2003-xensosp.pdf<00>5mhttp://www.ccs.neu.edu/racket/pubs/icfp10-cf.pdf<00>E<04>http://www.cas.mcmaster.ca/~bill/best/algorithms/07Taxonomy.pdf

1g
http://www.bodden.de/pubs/far+14flowdroid.pdfO<04>http://www.berkkapicioglu.com/wp-content/uploads/2013/11/thesis_final.pdf<00>W<04>1
http://www.andrew.cmu.edu/course/15-749/READINGS/required/resilience/lamport82.pdf|i<04>U
http://www.ams.org/journals/tran/1965-117-00/S0002-9947-1965-0170805-7/S0002-9947-1965-0170805-7.pdf;{
http://www-ee.stanford.edu/~hellman/publications/24.pdfF9w
http://www-bcf.usc.edu/~wyattllo/papers/f4-osdi14.pdfS4khttp://winsh.me/papers/erlang_workshop_2013.pdf<00>K<04>http://webcem01.cem.itesm.mx:8005/erlang/cd/downloads/hopl_erlang.pdf<00>:y
http://web.cs.ucdavis.edu/~rogaway/papers/moral-fn.pdfH3ihttp://user.it.uu.se/~kostis/Papers/ismm04.pdf<00>2i
http://user.it.uu.se/~kostis/Papers/escape.pdf<
<00>.<03><0E>.
<01>T<02>
7<0C>
[<0B>
<EFBFBD>
 f	L9<00><00><>:w	
oo5GGshttp://kowshik.github.io/JPregel/pregel_paper.pdfPregel: A System for Large-Scale Graph Processingdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109iL<00>#<23>5GGhttps://www.usenix.org/system/files/conference/osdi14/osdi14-<2D>C{

<01>	e5GGvhttp://people.csail.mit.edu/matei/papers/2013/sosp_sparrow.pdfSparrow: Distributed, Low Latency Schedulingdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>Jx	
5GGuhttp://sigops.org/sosp/sosp13/papers/p151-mashtizadeh.pdfReplication, History, and Grafting in the Ori File Systemdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>Mz

q<>5GGthttp://www.mshah.org/papers/sosp_2007_aguilera.pdfSinfonia: A New Paradigm for Building Scalable Distributed Systemsdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>Lu

<01>e5GGphttp://www.cs.utexas.edu/users/lorenzo/corsi/cs380d/papers/paper2-1.pdfPaxos Made Live - An Engineering Perspectivedistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<06><00><00><0F>5GGhttp://www.cs.utexas.edu/~shmat/courses/cs395t_fall04/chaum81.pdfUntraceable Electronic Mail, Return Addresses, and Digital Pseudonymsdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11<31>a<EFBFBD><02><0F>5GG<00>http://www.cs.utexas.edu/~shmat/courses/cs395t_fall04/chaum81.pdfUntraceable Electronic Mail, Return Addresses, and Digital Pseudonymsdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>?<3F>	
us5GG~http://anil.recoil.org/papers/2013-asplos-mirage.pdfUnikernels: Library Operating Systems for the Clouddistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109
<01><00><07>#5GGhttp://www.cs.berkeley.edu/~franklin/Papers/p315-franklin.pdfTransactional Client-Server Cache Consistency: Alternatives and Performancedistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109
<01>	yq5GGhttps://www.cs.cmu.edu/~dga/papers/epaxos-sosp2013.pdfThere Is More Consensus in Egalitarian Parliamentsdistributed_systems/2017-09-11T23:06:15.583<EFBFBD>b<EFBFBD>

<01><07>#5GGhttp://www.cs.berkeley.edu/~franklin/Papers/p315-franklin.pdfTransactional Client-Server Cache Consistency: Alternatives and Performancedistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>P<EFBFBD>

<01>m5GG}http://db.disi.unitn.eu/pages/VLDBProgram/pdf/industry/p871-curtiss.pdfUnicorn: A System for Searching the Social Graphdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>@<40>	
yq5GG|https://www.cs.cmu.edu/~dga/papers/epaxos-sosp2013.pdfThere Is More Consensus in Egalitarian Parliamentsdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>=

<01>%=5GG{http://research.microsoft.com/en-us/um/people/lamport/pubs/lamport-paxos.pdfThe Part-Time Parliamentdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>h~
<01>)<29>
5GGzhttp://research.microsoft.com/en-us/um/people/fournet/papers/join-tutorial.pdfThe Join Calculus: a Language for Distributed Mobile Programmingdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>I|

<01>1I5GGyhttp://www.andrew.cmu.edu/course/15-749/READINGS/required/resilience/lamport82.pdfThe Byzantine Generals Problemdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>v}
<01>G<EFBFBD>5GGxhttp://static.googleusercontent.com/media/research.google.com/en/us/archive/chubby-osdi06.pdfThe Chubby Lock Service for Loosely-Coupled Distributed Systemsdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD> y	
iA5GGwhttp://nms.lcs.mit.edu/papers/ron-sosp2001.pdfResilient Overlay Networksdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>v
<01>q<EFBFBD>
5GGqhttp://www.itu.dk/stud/speciale/bepjea/xwebtex/litt/practical-byzantine-fault-tolerance-and-proactive-recovery.pdfPractical Byzantine Fault Tolerance and Proactive Recoverydistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109

r)<07>F!<06>a<0B><0C>W<08>r	r<04><03><02> 
8<00>d<EFBFBD><00><07>+3GGhttp://community.haskell.org/~simonmar/papers/parallel-gc.pdfParallel Generational-Copying Garbage Collection with a Block-Structured
  Heapgarbage_collection/2017-09-11T23:06:15.6538410642017-09-11T23:06:15.653841064<EFBFBD>K<EFBFBD>
o<>3GGhttp://home.pipeline.com/~hbaker1/NoMotionGC.htmlThe Treadmill: Real<61>a<EFBFBD><02>!<21>'GG<00>http://gamification-research.org/wp-content/uploads/2011/04/12-Gerling.pdfExploring the Potential of Gamification Among Frail Elderly Personsgamification/2017-09-11T23:06:15.6480180662017-09-11T23:06:15.648018066<EFBFBD>N<EFBFBD>
<02>{'GG<00>http://www.rolandhubscher.org/courses/hf765/readings/p17-huotari.pdfDefining Gamification - A Service Marketing Perspectivegamification/2017-09-11T23:06:15.6480180662017-09-11T23:06:15.648018066<EFBFBD>f<EFBFBD>
a<>Q5GG<00>http://www.pmg.csail.mit.edu/papers/vr.pdfViewstamped Replication: A New Primary Copy Method to Support Highly-Available Distributed Systemsdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<08><00>#<23>5G<>!<21><02>#<23>5GG<00>https://www.usenix.org/system/files/conference/osdi14/osdi14-paper-yuan.pdfSimple Testing Can Prevent Most Critical Failures:
An Analysis of Production Failures in Distributed
Data-Intensive Systemsdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>%<25>
<02>
#5GG<00>http://en.wikipedia.org/wiki/Moving_magnet_and_conductor_problemasymmetriesdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>P<EFBFBD>	
<02>	}5GG<00>http://research.microsoft.com/pubs/255833/IronFleet-twocol.pdfIronFleet: Proving Practical Distributed Systems Correctdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>J<EFBFBD>
<02>
m5GG<00>http://research.microsoft.com/pubs/80693/vl2-sigcomm09-final.pdfVL2: A Scalable and Flexible Data Center Networkdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109
<EFBFBD>
<00>q<EFBFBD>'<08>P<EFBFBD>
}<7D>'GG<00>http://www.katherineeveritt.com/papers/p457-consolvo.pdfDesign Requirements for Technologies that Encourage Physical Activitygamification/2017-09-11T23:06:15.6480180662017-09-11T23:06:15.648018066<EFBFBD><0B><02>q<EFBFBD>'GG<00>http://dl.dropboxusercontent.com/u/220532/MindTrek_Gamification_PrinterReady_110806_SDE_accepted_LEN_changes_1.pdfFrom Game Design Elements to Gamefulness: Defining “Gamification”gamification/2017-09-11T23:06:15.6480180662017-09-11T23:06:15.648018066#

}<7D>'GGhttp://www.katherineeveritt.com/papers/p457-consolvo.pdfDesign Requirements for Technologies that Encourage Physical Activitygamification/2017-09-11T23:06:15.6480180662017-09-11T23:06:15.648018066#0
<00>{'GGhttp://www.rolandhubscher.org/cour<75><1C>	
s#AGGhttp://en.wikipedia.org/wiki/Empirical_algorithmics(Wikipedia)experimental_algorithmics/2017-09-11T23:06:15.6239860842017-09-11T23:06:15.623986084
<0A><00>
i<>AGGhttp://davidsjohnson.net/papers/experguide.pdfA Theoretician's Guide to the Experimental Analysis of Algorithmsexperimental_algorithmics/2017-0<>O<EFBFBD>
i<>AGG<00>http://davidsjohnson.net/papers/experguide.pdfA Theoretician's Guide to the Experimental Analysis of Algorithmsexperimental_algorithmics/2017-09-11T23:06:15.6239860842017-09-11T23:06:15.623986084<00>
<00>GGGhttp://www.ece.cmu.edu/~ganger/712.fall02/papers/p761-thompson.pdfReflections on Trusting Trustethics/2017-09-11T23:06:15.6229060062017-09-11T23:06:15.622906006<00><00>I<EFBFBD>!GGhttp://www.sci.br<62>,<2C>
<02>GGG<00>http://www.ece.cmu.edu/~ganger/712.fall02/papers/p761-thompson.pdfReflections on Trusting Trustethics/2017-09-11T23:06:15.6229060062017-09-11T23:06:15.622906006<EFBFBD>k<EFBFBD>
<02>I<EFBFBD>!GG<00>http://www.sci.brooklyn.cuny.edu/~parsons/projects/mech-design/publications/bluffers-final.pdfAuctions and bidding: A guide for computer scientists (2011)economics/2017-09-11T23:06:15.6214260252017-09-11T23:06:15.621426025
<08><07>O
j
<0A><0C><0E>(	<09><08><06><05><04><03><02><00><16>"	q=GG<00>http://www.gsd.inesc-id.pt/~ler/reports/srds07.pdfEpidemic Broadcast Treesgossip/2017-09-11T23:06:15.6716430662017-09-11T23:06:15.671643066<EFBFBD>I<EFBFBD>!
}<7D>GG<00>http://www.cs.cornell.edu/home/rvr/papers/flowgossip.pdfEfficient Reconciliation and Flow Control for Anti-Entropy Protocolsgossip/2017-09-11T23:06:15.6716430662017-09-11T23:06:15.671643066<EFBFBD><13> 	y/GG<00>http://www.csl.mtu.edu/cs6461/www/Reading/Birman99.pdfBimodal Multicastgossip/2017-09-11T23:06:15.6716430662017-09-11T23:06:15.671643066<EFBFBD>3<EFBFBD>	}kGG<00>http://www.soc.napier.ac.uk/~benp/dream/dreampaper17.pdfLarge-Scale Newscast Computing on the Internet gossip/2017-09-11T23:06:15.6716430662017-09-11T23:06:15.671643066<EFBFBD>W<EFBFBD>
}<7D>1GG<00>http://www.cs.cornell.edu/~asdas/research/dsn02-swim.pdfSWIM: Scalable Weakly-consistent Infection-style Process Group Membership Protocolgossip/2017-09-11T23:06:15.6716430662017-09-11T23:06:15.671643066<EFBFBD>q<EFBFBD><02><15>KGG<00>http://infoscience.epfl.ch/record/83409/files/neg--1184036295all.pdfThe Peer Sampling Service: Experimental Evaluation of Unstructured Gossip-Based Implementationsgossip/2017-09-11T23:06:15.6716430662017-09-11T23:06:15.671643066<EFBFBD><10>
<02>%{GG<00>http://bitsavers.informatik.uni-stuttgart.de/pdf/xerox/parc/techReports/CSL-89-1_Epidemic_Algorithms_for_Replicated_Database_Maintenance.pdfEpidemic Algorithms for Replicated Database Maintenancegossip/2017-09-11T23:06:15.6716430662017-09-11T23:06:15.671643066<EFBFBD>o<EFBFBD><02><0B>E'GG<00>http://www.ic.unicamp.br/~oliveira/doc/Ubicomp2010_MoviPill.pdfMoviPill: Improving Medication Compliance for Elders - Using a Mobile Persuasive Social Gamegamification/2017-09-11T23:06:15.6480180662017-09-11T23:06:15.648018066<0B><00><>f<EFBFBD><02><07>+3GG<00>http://community.haskell.org/~simonmar/papers/parallel-gc.pdfParallel Generational-Copying Garbage Collection with a Block-Structured
  Heapgarbage_collection/2017-09-11T23:06:15.6538410642017-09-11T23:06:15.653841064<EFBFBD>M<EFBFBD>
o<>3GG<00>http://home.pipeline.com/~hbaker1/NoMotionGC.htmlThe Treadmill: Real-Time Garbage Collection Without Motion Sicknessgarbage_collection/2017-09-11T23:06:15.6538410642017-09-11T23:06:15.653841064<EFBFBD>:<3A>
<02>Y3GG<00>http://www.cs.virginia.edu/~cs415/reading/bacon-garbage.pdfA Unified Theory of Garbage Collectiongarbage_collection/2017-09-11T23:06:15.6538410642017-09-11T23:06:15.653841064<EFBFBD>Q<EFBFBD>
<02>s3GG<00>http://www.ssw.uni-linz.ac.at/General/Staff/TW/Wuerthinger05Train.pdfIncremental Garbage Collection: The Train Algorithmgarbage_collection/2017-09-11T23:06:15.6538410642017-09-11T23:06:15.653841064
<00>)]3GG<47>G<EFBFBD>
y<>GG<00>http://asc.di.fct.unl.pt/~jleitao/pdf/dsn07-leitao.pdfHyParView: a membership protocol for reliable gossip-based broadcastgossip/2017-09-11T23:06:15.6716430662017-09-11T23:06:15.671643066<EFBFBD>O<EFBFBD>
<02>)]3GG<00>http://pdf.aminer.org/000/465/194/incremental_collection_of_mature_objects.pdfIncremental Collection of Mature Objectsgarbage_collection/2017-09-11T23:06:15.6538410642017-09-11T23:06:15.653841064<EFBFBD>T<EFBFBD><02>	<09>3GG<00>https://www.cs.purdue.edu/homes/hosking/690M/p611-fenichel.pdfA LISP Garbage-Collector for Virtual-Memory Computer Systemsgarbage_collection/2017-09-11T23:06:15.6538410642017-09-11T23:06:15.653841064<EFBFBD>J<EFBFBD>
q<>3GG<00>https://www.sics.se/~seif/DatalogiII/Book/train.psIncremental Mature Garbage Collection Using the Train Algorithmgarbage_collection/2017-09-11T23:06:15.6538410642017-09-11T23:06:15.653841064<EFBFBD>-<2D>	ke'GG<00>http://www.jennthom.com/papers/gamification.pdfRemoving Gamification from an Enterprise SNSgamification/2017-09-11T23:06:15.6480180662017-09-11T23:06:15.648018066
13<0F>n(<0E><0E>G
<0A>
<0A>
q
/
<0C><0C>M<0B>y
<EFBFBD>
k
&	<09>	<09>	S	<08>R(<07><07>l(<06><06>0<05><05>h%<04>e<04>k'3<03>b2<02>1ehttp://www.people.hbs.edu/jlerner/simple.pdf
2m<04>[http://www.mit.edu/~dbertsim/papers/Revenue%20Management/Optimal%20Bidding%20in%20Online%20Auctions.pdf
1^<04>=http://www.pps.univ-paris-diderot.fr/~saurin/Enseignement/LMFI/articles/Martin-Lof83.pdf<00>/ahttp://www.pmg.csail.mit.edu/papers/vr.pdf<00>h<04>S
http://www.peterwonka.net/Publications/pdfs/2006.SG.Mueller.ProceduralModelingOfBuildings.final.pdf0[<04>9
http://www.peterwonka.net/Publications/pdfs/2003.SG.Wonka.InstantArchitecture.high.pdf1C<04>http://www.msr-waypoint.net/en-us/groups/ese/nagappan_tdd.pdf
5mhttp://www.msr-waypoint.com/pubs/64346/dwork.pdf<00>6q
http://www.mshah.org/papers/sosp_2007_aguilera.pdfzL<04>http://www.lix.polytechnique.fr/~rousseau/papers/rousseau-cikm2013.pdf<00>B<04>http://www.kdd.org/kdd2016/papers/files/rfp0573-ribeiroA.pdf<00>T<04>)http://www.kavrakilab.org/sites/default/files/kavraki1996prm-high-dim-conf.pdf<00>=}http://www.katherineeveritt.com/papers/p457-consolvo.pdf<00>4khttp://www.jennthom.com/papers/gamification.pdf<00>w<04>q
http://www.itu.dk/stud/speciale/bepjea/xwebtex/litt/practical-byzantine-fault-tolerance-and-proactive-recovery.pdfv9w
http://www.it-c.dk/people/pagh/papers/cuckoo-jour.pdfPE<04>http://www.inf.ed.ac.uk/teaching/courses/exc/reading/morris.pdf
C<04>	
http://www.ics.uci.edu/~yingyib/papers/HaLoop_camera_ready.pdf]=}http://www.icg.tugraz.at/Members/steinber/scatteralloc-1<00>E<04>http://www.ic.unicamp.br/~oliveira/doc/Ubicomp2010_MoviPill.pdf<00>7qhttp://www.gsd.inesc-id.pt/~ler/reports/srds07.pdf<00>)W
http://www.few.vu.nl/~kgr700/sdd1.pdf_<}
http://www.erlang.org/download/armstrong_thesis_2003.pdf`<60><04>http://www.elizabete.com.br/site/Outros/Entradas/2012/11/19_Revisao_Sistematica_files/ConceitosRevisaoSistematica_Biolchini.pdf
<}
http://www.eecs.harvard.edu/~waldo/Readings/waldo-94.pdfiE<04>

http://www.eecs.berkeley.edu/Pubs/TechRpts/2009/EECS-2009-28.pdfkC<04>http://www.ee.columbia.edu/~dpwe/pubs/BarkCE05-sfd-spcomm.pdf
H<04>http://www.ece.cmu.edu/~ganger/712.fall02/papers/p761-thompson.pdf<00>D<04>
http://www.dna.caltech.edu/courses/cs191/paperscs191/turing.pdfH<04>http://www.diva-portal.org/smash/get/diva2:392243/FULLTEXT01.pdfOn<00>_<04>A
http://www.disneyresearch.com/project/high-quality-single-shot-capture-of-facial-geometry/7d<04>K
http://www.disneyresearch.com/project/coupled-3d-reconstruction-of-sparse-facial-hair-and-skin/6;yhttp://www.csl.mtu.edu/cs6461/www/Reading/Birman99.pdf<00>\<04>9http://www.csee.umbc.edu/courses/undergraduate/CMSC331/resources/papers/sammet1972.pdf<00>:y
http://www.csee.umbc.edu/courses/471/papers/turing.pdf8u
http://www.cse.psu.edu/~duo114/pubs/octeau-sec13.pdfA<04>
http://www.csd.uoc.gr/~hy460/pdf/Dynamic%20Hash%20Tables.pdfM:whttp://www.cs.yale.edu/homes/zwan/papers/mcu/efrp.pdf<00>+Yhttp://www.cs.washington.edu/node/4749<00>A<04>http://www.cs.virginia.edu/~cs415/reading/bacon-garbage.pdf<00>@<04>
http://www.cs.uvm.edu/~icdm/algorithms/10Algorithms-08.pdf<00>G<04>http://www.cs.utexas.edu/~shmat/courses/cs395t_fall04/chaum81.pdf<00>L<04>
http://www.cs.utexas.edu/users/lorenzo/corsi/cs380d/papers/paper2-1.pdfuW<04>/http://www.cs.ucsb.edu/~veronika/MAE/spacecomplexityapproxfreqmoments_alon_99.pdf
	A<04>http://www.cs.ucf.edu/courses/cop4020/sum2009/CSP-hoare.pdf<00>F<04>
http://www.cs.tufts.edu/~nr/cs257/archive/luc-maranget/jun08.pdf<00>E<04>http://www.cs.tufts.edu/~nr/cs257/archive/john-hughes/quick.pdf<00>O<04>http://www.cs.tufts.edu/~nr/cs257/archive/chris-okasaki/breadth-first.pdf<00>A<04>
http://www.cs.tau.ac.il/~tromer/papers/acoustic-20131218.pdfG
<03>
&D<0E>
<0A>
)<0C><0B>)
\	<09>	5<06><05>
&
<01><02>=<00>P<EFBFBD>1

u<>/GG`http://erlang.org/download/armstrong_thesis_2003.pdfMaking reliable distributed systems in the presence of software errorslanguages/erlang/2017-09-11T23:06:15.7035358892017-09-11T23:06:15.703535889<EFBFBD>/<2F>2
<02>3/GG<00>http://webcem01.cem.itesm.mx:8005/erlang/cd/downloads/hopl_erlang.pdfA History of Erlanglanguages/erlang/2017-09-11T23:06:15.7035358892017-09-11T23:06:15.703535889<EFBFBD>]<5D>3<02><11>/GG<00>http://www.diva-portal.org/smash/get/diva2:392243/FULLTEXT01.pdfOnCharacterizing the Scalability of Erlang VM on Many-core Processorslanguages/erlang/2017-09-11T23:06:15.7035358892017-09-11T23:06:15.703535889<04><00>	kg/GGhttp://winsh.me/papers/erlang_workshop_2013.pdfOn the Scalability of the Erlang Term Storagelanguages/erlang/2017-09-11T23:06:15.7035358892017-09-11T23:06:15.7035<EFBFBD>2<EFBFBD>4	kg/GG<00>http://winsh.me/papers/erlang_workshop_2013.pdfOn the Scalability of the Erlang Term Storagelanguages/erlang/2017-09-11T23:06:15.7035358892017-09-11T23:06:15.703535889<00>
u<>/GGhttp://erlang.org/download/armstrong_thesis_2003.pdfMaking reliable distributed systems in the presence of software errorslanguages/erlang/2017-09-11T23:06:15.7035358892017-09-11T23:06:15.703535889<EFBFBD>><3E>0	KyUGG<00>http://arxiv.org/abs/1507.02988Programmatic and Direct Manipulation, Together at Lastlanguages/domain-specific-languages/2017-09-11T23:06:15.7029560552017-09-11T23:06:15.702956055<EFBFBD>)<29>/	gW1GG<00>http://people.inf.elte.hu/center/fulltext.pdfQuickCheck Testing for Fun and Profitlanguages/clojure/2017-09-11T23:06:15.6991608892017-09-11T23:06:15.699160889<EFBFBD>]<5D>.<02><0B>1GG<00>http://www.cs.tufts.edu/~nr/cs257/archive/john-hughes/quick.pdfQuickCheck: A Lightweight Tool for Random Testing of Haskell Programslanguages/clojure/2017-09-11T23:06:15.6991608892017-09-11T23:06:15.699160889<EFBFBD>l<EFBFBD>-<02><1F>!1GG<00>http://www.cs.tufts.edu/~nr/cs257/archive/chris-okasaki/breadth-first.pdfBreadth-First Numbering: Lessons from a Small Exercise in Algorithm Designlanguages/clojure/2017-09-11T23:06:15.6991608892017-09-11T23:06:15.699160889<EFBFBD><1A>,	g91GG<00>https://www.lri.fr/~filliatr/publis/enum2.pdfBacktracking Iteratorslanguages/clojure/2017-09-11T23:06:15.6991608892017-09-11T23:06:15.699160889<EFBFBD>4<EFBFBD>+	U1GG<00>http://frenchy64.github.io/papers/typed-clojure-draft.pdfPractical Optional Types for Clojurelanguages/clojure/2017-09-11T23:06:15.6991608892017-09-11T23:06:15.699160889<EFBFBD>I<EFBFBD>*
<02>
o1GG<00>http://www.cs.tufts.edu/~nr/cs257/archive/luc-maranget/jun08.pdfCompiling Pattern Matching to good Decision Treeslanguages/clojure/2017-09-11T23:06:15.6991608892017-09-11T23:06:15.699160889<EFBFBD><1C>)	m53GG<00>http://www.msr-waypoint.com/pubs/64346/dwork.pdfDifferential Privacyinformation_theory/2017-09-11T23:06:15.6969179692017-09-11T23:06:15.696917969<EFBFBD>><3E>(	oq9GG<00>https://www.cs.cornell.edu/home/kleinber/auth.pdfAuthoritative Sources in a Hyperlinked Environmentinformation_retrieval/2017-09-11T23:06:15.6729851072017-09-11T23:06:15.672985107<EFBFBD><1A>'	o)9GG<00>http://trec.nist.gov/pubs/trec3/papers/city.ps.gzOkapi at TREC3information_retrieval/2017-09-11T23:06:15.6729851072017-09-11T23:06:15.672985107<EFBFBD>D<EFBFBD>&	o}9GG<00>http://ilpubs.stanford.edu:8090/422/1/1999-66.pdfThe PageRank Citation Ranking: Bringing Order to the Webinformation_retrieval/2017-09-11T23:06:15.6729851072017-09-11T23:06:15.672985107<EFBFBD>:<3A>%
<02>=9GG<00>http://www.lix.polytechnique.fr/~rousseau/papers/rousseau-cikm2013.pdfGraph of Word and TW-IDFinformation_retrieval/2017-09-11T23:06:15.6729851072017-09-11T23:06:15.672985107<EFBFBD><11>$	WMGG<00>http://ddg.jaist.ac.jp/pub/HDY+04.pdfThe ϕ Accrual Failure Detector gossip/2017-09-11T23:06:15.6716430662017-09-11T23:06:15.671643066<EFBFBD>8<EFBFBD>#
<02>]GG<00>https://ecommons.cornell.edu/bitstream/handle/1813/7341/98-1687.pdfA Gossip-Style Failure Detection Servicegossip/2017-09-11T23:06:15.6716430662017-09-11T23:06:15.671643066

Y
(
 5r
<EFBFBD>	<09><08>?<07><06>5w
Y<04><03><00>/<2F>Q	ia1GG<00>http://plosworkshop.org/2013/preprint/kell.pdfThe operating system: should there be one?operating_systems/2017-09-11T23:06:15.8643869632017-09-11T23:06:15.864386963<EFBFBD>p<EFBFBD>U<02><1F>)1GG<00>https://us-east.manta.joyent.com/bcantrill/public/ppwl-cantrill-zones.pdfSolaris Zones: Operating System Support for Consolidating Commercial Workloadsoperating_systems/2017-09-11T23:06:15.8643869632017-09-11T23:06:15.864386963<EFBFBD>F<EFBFBD>T
<02>W1GG<00>https://us-east.manta.joyent.com/bcantrill/public/ppwl-cantrill-jails.pdfJails: Confining the omnipotent root.operating_systems/2017-09-11T23:06:15.8643869632017-09-11T23:06:15.864386963<EFBFBD>;<3B>S
<02>O1GG<00>http://www.cl.cam.ac.uk/research/srg/netos/papers/2003-xensosp.pdfXen and the Art of Virtualizationoperating_systems/2017-09-11T23:06:15.8643869632017-09-11T23:06:15.864386963<EFBFBD>j<EFBFBD>R<02><05>71GG<00>https://people.csail.mit.edu/nickolai/papers/clements-sc.pdfThe Scalable Commutativity Rule: Designing Scalable Software for Multicore Processorsoperating_systems/2017-09-11T23:06:15.8643869632017-09-11T23:06:15.864386963<EFBFBD>:<3A>P
<02>
Q=GG<00>http://orbit.dtu.dk/files/102419168/abstract_ELB_trees.pdfEfficient Lock-free B+trees (2014)non_blocking_algorithms/2017-09-11T23:06:15.8364030762017-09-11T23:06:15.836403076<EFBFBD>:<3A>O	eo=GG<00>http://chaoran.me/assets/pdf/wfq-ppopp16.pdfA Wait-free Queue as Fast as Fetch-and-Add (2016)non_blocking_algorithms/2017-09-11T23:06:15.8364030762017-09-11T23:06:15.836403076<EFBFBD><15>N	M==GG<00>https://arxiv.org/abs/1510.00116A Wait-Free Stack (2015)non_blocking_algorithms/2017-09-11T23:06:15.8364030762017-09-11T23:06:15.836403076<EFBFBD>/<2F>M
<02>UGG<00>http://www.comp.lancs.ac.uk/~elkhatib//Docs/2014.06_Netw.pdfCan SPDY Really Make the Web Faster?networks/2017-09-11T23:06:15.8355119632017-09-11T23:06:15.835511963<EFBFBD>%<25>L	qWGG<00>http://www.reed.com/dpr/locus/Papers/EndtoEnd.htmlEnd-to-End Arguments in System Designnetworks/2017-09-11T23:06:15.8355119632017-09-11T23:06:15.835511963<EFBFBD>c<EFBFBD>K
{<7B>51GG<00>http://www.rdrop.com/users/paulmck/RCU/hart_ipdps06.pdfMaking Lockless Synchronization Fast: Performance Implications of Memory Reclamationmemory_management/2017-09-11T23:06:15.8240930182017-09-11T23:06:15.824093018<EFBFBD>V<EFBFBD>J
}<7D>1GG<00>http://www.icg.tugraz.at/Members/steinber/scatteralloc-1ScatterAlloc: Massively Parallel Dynamic Memory Allocation for the GPUmemory_management/2017-09-11T23:06:15.8240930182017-09-11T23:06:15.824093018<EFBFBD>E<EFBFBD>I
<02>C11GG<00>https://www.usenix.org/legacy/publications/library/proceedings/bos94/full_papers/bonwick.psPOSTSCRIPT versionmemory_management/2017-09-11T23:06:15.8240930182017-09-11T23:06:15.824093018<EFBFBD>?<3F>H
<02>A'1GG<00>https://www.usenix.org/legacy/publications/library/proceedings/bos94/full_papers/bonwick.aASCII versionmemory_management/2017-09-11T23:06:15.8240930182017-09-11T23:06:15.824093018<EFBFBD>g<EFBFBD>G<02>/<2F>1GG<00>https://www.usenix.org/legacy/publications/library/proceedings/bos94/bonwick.htmlThe Slab Allocator: An Object-Caching Kernel Memory Allocatormemory_management/2017-09-11T23:06:15.8240930182017-09-11T23:06:15.824093018<EFBFBD><04>F<02>'<27>I1GG<00>http://researcher.watson.ibm.com/researcher/files/us-bacon/Bacon12AndThen.pdfAnd Then There Were None: A Stall-Free Real-Time Garbage Collector for Reconfigurable Hardwarememory_management/2017-09-11T23:06:15.8240930182017-09-11T23:06:15.824093018<EFBFBD>^<5E>E
i<>=1GG<00>http://user.it.uu.se/~kostis/Papers/ismm04.pdfMessage Analysis Guided Allocation and Low Pause Incremental GC in a Concurrent Languagememory_management/2017-09-11T23:06:15.8240930182017-09-11T23:06:15.824093018<EFBFBD>r<EFBFBD>D<02>+<2B>!1GG<00>https://cs.brown.edu/~sk/Publications/Papers/Published/cgkmf-teach-gc/paper.pdfTeaching Garbage Collection without Implementing Compilers or Interpretersmemory_management/2017-09-11T23:06:15.8240930182017-09-11T23:06:15.824093018

2
/<0B><0B><0B>e8
<EFBFBD>
<EFBFBD>
_
-	<09>
<01>	<09>	<09>2
<01>
me	><0C><08><08><07><08>
<06><02><06>?
<05><05>
/W<0C>1-<04><04>s><03>D<02>r<0F>%<0E>'
<0A>ww.msr-waypoint.C<04>http://www.msr-waypoint.net/en-us/groups/ese/nagappan_tdd.pdf

bhttp://www.gsd.inesc-id.pt/~ler/reports/srds07.pdf<00>)W
http://www.few.vu.nl/~kgr700/sdd1.pdf_O<04>https://en.wikipedia.org/wiki/Boyer%E2%80%93Moore_string_search_algorithm

ht>http://www.voelter.de/data/pub/projectingModuleFuture.pdf
J<04>http://www.techzoom.net/Papers/Browser_Silent_Updates_%282009%29.pdf
*"http://www.kavrakilab.org/sit2ghttp://www.vmware.com/pdf/asplos235_adams.pdf
5mhttp://www.roboticsproceedings.org/rss01/p36.pdf<00>/ahttps://arxiv.org/pdf/quant-ph/9605043.pdf<00>x<04>qhttps://github.com/papers-we-love/papers-we-love/blob/master/plt/fundamental-concepts-in-programming-languages.pdf<00>f<04>Mhttps://github.com/papers-we-love/papers-we-love/blob/master/mathematics/transcendence-of-pi.pdfÁ<04>%
https://github.com/papers-we-love/papers-we-love/blob/master/caching/a-constant-algorithm-for-implementing-the-lfu-cache-eviction-scheme.pdf<16><04>
https://github.com/papers-we-love/papers-we-love/blob/master/artificial_intelligence/3-bayesian-network-inference-algorithm.pdf9w
https://github.com/luanfujun/deep-photo-styletransfer,.a
https://github.com/ibab/tensorflow-wavenet)W
https://github.com/basveeling/wavenet(U
https://eprint.iacr.org/2016/461.pdfII<04>https://ecommons.cornell.edu/bitstream/handle/1813/7341/98-1687.pdf<00>B<04>
https://deepmind.com/blog/wavenet-generative-model-raw-audio/1g
https://cs.uwaterloo.ca/~bernard/hyperdex.pdf^U<04>+https://cs.brown.edu/~sk/Publications/Papers/Published/cgkmf-teach-gc/paper.pdf<00>;{
https://crypto.stanford.edu/~dabo/papers/RSA-survey.pdfE/ahttps://arxiv.org/pdf/quant-ph/9508027.pdf<00>(U
https://arxiv.org/pdf/1703.07511.pdf+8
ht@<04>
https://github.com/adamstark/Chord-Detector-and-Chromagram
&<04>https://github.com/papers-we-love/papers-we-love/blob/master/plt/on-understanding-types-data-abstraction-polymorphism.pdf<00>%Mhttps://arxiv.org/abs/1512.02900<00>L<04>http://www.thocp.net/biographies/papers/backus_turingaward_lecture.pdf<00>7qhttp://xlinux.nist.gov/dads//HTML/ahoCorasick.html<00>(U
https://arxiv.org/pdf/1609.03499.pdf%Mhttps://arxiv.org/abs/1510.00116<00>Q<04>%
https://amplab.cs.berkeley.edu/wp-content/uploads/2013/03/mdcc-eurosys13.pdfcF<04>
http://zoo.cs.yale.edu/classes/cs422/2013/bib/terry95managing.pdfa*Y
http://www.vldb.org/conf/1994/P439.PDF0e
http://www.turingarchive.org/browse.php/B/12K<04>http://www.ssw.uni-linz.ac.at/General/Staff/TW/Wuerthinger05Train.pdf<00>1g
http://www.ssrc.ucsc.edu/Papers/weil-sc06.pdfY=}http://www.soc.napier.ac.uk/~benp/dream/dreampaper17.pdf<00>5o
http://www.sci.utah.edu/~bsumma/projects/weaving/8d<04>Ihttp://www.sci.brooklyn.cuny.edu/~parsons/projects/mech-design/publications/bluffers-final.pdf<00>J<04>http://www.rolandhubscher.org/courses/hf765/readings/p17-huotari.pdf<00>?<04>

http://www.research.ibm.com/people/m/michael/podc-1996.pdfN7qhttp://www.reed.com/dpr/locus/Papers/EndtoEnd.html<00><{http://www.rdrop.com/users/paulmck/RCU/hart_ipdps06.pdf<00>;
http://www.proun-game.com/Oogst3D/CODING/InteriorMappi'Qhttps://github.com/marsyas/marsyas
)$Khttps://github.com/MTG/essentia
(<28>+<04>Whttps://ac.els-cdn.com/0890540191900524/1-s2.0-0890540191900524-main.pdf?_tid=45497e1c-b5c9-11e7-963f-00000aacb361&acdnat=1508526351_2f3bf288ce0f81ff89fb10ece92eeb9e
O<04>http://www3.alcatel-lucent.com/bstj/vol34-1955/articles/bstj34-5-1045.pdf
i<04>Shttps://github.com/papers-we-love/papers-we-love/blob/master/plt/theory-in-programming-practice.pdf<00>}<04>{https://github.com/papers-we-love/papers-we-love/blob/master/plt/the-derivative-of-a-regular-type-one-hole-contexts.pdf<00><04>https://github.com/papers-we-love/papers-we-love/blob/master/plt/programming-languages-application-and-interpretation.pdf<00>y<04>shttps://github.com/papers-we-love/papers-we-love/blob/master/plt/principal-type-schemes-for-functional-programs.pdf<00>`<04>Ahttps://github.com/papers-we-love/papers-we-love/blob/master/plt/predicate-dispatching.pdf<00>

!01
r0<03>eH
<0A>
	A<08>+/<02>
<01>
!
!<21>m<EFBFBD>X<02><0B>OGG<00>http://eprints.eemcs.utwente.nl/7281/01/db-utwente-40501F46.pdfFunctional Programming with Bananas, Lenses, Envelopes and Barbed Wireparadigms/functional_programming/2017-09-11T23:06:15.8949589842017-09-11T23:06:15.894958984<04>Q
<00>C7GGhttp://homepages.inf.ed.ac.uk/wadler/papers/propositions-as-types/p<>;<3B>W	qSOGG<00>http://cs.au.dk/~hosc/local/LaSC-4-3-pp223-242.pdfOrganizing Programs Without Classesparadigms/functional_programming/2017-09-11T23:06:15.8949589842017-09-11T23:06:15.894958984<EFBFBD>Q<EFBFBD>V
<02>mAGG<00>http://jeffreymbradshaw.net/publications/Common_Ground_Single.pdfCommon Ground and Coordination in Joint Activityorganizational_simulation/2017-09-11T23:06:15.8778430182017-09-11T23:06:15.877843018<EFBFBD>l<EFBFBD>Z
{<7B>)OGG<00>http://dig.cs.illinois.edu/papers/lambdaRefactoring.pdfCrossing the Gap from Imperative to Functional Programming through Refactoringparadigms/functional_programming/2017-09-11T23:06:15.8949589842017-09-11T23:06:15.894958984<EFBFBD>O<EFBFBD>Y
<02>UOGG<00>http://patrickthomson.ghost.io/an-introduction-to-recursion-schemes/An introduction to Recursion Schemesparadigms/functional_programming/2017-09-11T23:06:15.8949589842017-09-11T23:06:15.894958984f<00><19>[GGhttp://www.thocp.net/biographies/papers/backus_turingaward_lecture.pdfCan Programming Be Liberated from the von Neumann Style? A Functional Style and Its Algebra of Programsplt/2017-09-11T23:06:15.9704099122017-09-11T23:06:15.970409912h	q5/GGhttp://xlinux.nist.gov/dads//HTML/ahoCorasick.htmlAho–Corasick entrypattern_matching/2017-09-11T23:06:15.9460258792017-09-11T23:06:15.946025879j;/GGhttp://racket-lang.org/Racketpattern_matching/2017-09-11T23:06:15.9460258792017-09-11T23:06:15.946025879l
g<>
YGGhttp://cseweb.ucsd.edu/~vahdat/papers/mop.pdfMetaobject protocols: Why we wa<77>x<EFBFBD>e<02><19>[GG<00>http://www.thocp.net/biographies/papers/backus_turingaward_lecture.pdfCan Programming Be Liberated from the von Neumann Style? A Functional Style and Its Algebra of Programsplt/2017-09-11T23:06:15.9704099122017-09-11T23:06:15.970409912<EFBFBD><1C>d	q5/GG<00>http://xlinux.nist.gov/dads//HTML/ahoCorasick.htmlAho–Corasick entrypattern_matching/2017-09-11T23:06:15.9460258792017-09-11T23:06:15.946025879s<EFBFBD>c	;/GG<00>http://racket-lang.org/Racketpattern_matching/2017-09-11T23:06:15.9460258792017-09-11T23:06:15.946025879<EFBFBD>Y<EFBFBD>b
g<>
YGG<00>http://cseweb.ucsd.edu/~vahdat/papers/mop.pdfMetaobject protocols: Why we want them and what else they can doparadigms/object_oriented_programming/2017-09-11T23:06:15.9451201172017-09-11T23:06:15.945120117<EFBFBD>d<EFBFBD>a
<02>'[aGG<00>https://www.seas.harvard.edu/sites/default/files/files/archived/Czaplicki.pdfElm: Concurrent FRP for Functional GUIsparadigms/functional_reactive_programming/2017-09-11T23:06:15.9127919922017-09-11T23:06:15.912791992<EFBFBD>O<EFBFBD>_	{_aGG<00>http://conal.net/papers/push-pull-frp/push-pull-frp.pdfPush-Pull Functional Reactive Programmingparadigms/functional_reactive_programming/2017-09-11T23:06:15.9127919922017-09-11T23:06:15.912791992<EFBFBD>f<EFBFBD>`
<02>/WaGG<00>http://haskell.cs.yale.edu/wp-content/uploads/2012/08/Winograd-Cort-Wormholes.pdfWormholes: Introducing Effects to FRPparadigms/functional_reactive_programming/2017-09-11T23:06:15.9127919922017-09-11T23:06:15.912791992<EFBFBD>]<5D>^	waGG<00>http://people.seas.harvard.edu/~chong/pubs/pldi13-elm.pdfAsynchronous Functional Reactive Programming for GUIsparadigms/functional_reactive_programming/2017-09-11T23:06:15.9127919922017-09-11T23:06:15.912791992<EFBFBD>=<3D>]
<02>
'aGG<00>http://haskell.cs.yale.edu/wp-content/uploads/2011/02/rt-frp.pdfReal-Time FRPparadigms/functional_reactive_programming/2017-09-11T23:06:15.9127919922017-09-11T23:06:15.912791992<EFBFBD>_<EFBFBD>[
<02>aaGG<00>http://haskell.cs.yale.edu/wp-content/uploads/2011/02/workshop-02.pdfFunctional Reactive Programming, Continuedparadigms/functional_reactive_programming/2017-09-11T23:06:15.9127919922017-09-11T23:06:15.912791992<EFBFBD>4<EFBFBD>\	w-aGG<00>http://www.cs.yale.edu/homes/zwan/papers/mcu/efrp.pdfEvent-Driven FRPparadigms/functional_reactive_programming/2017-09-11T23:06:15.9127919922017-09-11T23:06:15.912791992
X
23<05><03>
2<02>
$(!
R<06><08>n<02>
<01><00><00>l<EFBFBD>|<00>)<29>-GGhttp://www.kavrakilab.org/sites/default/files/kavraki1996pr<70>i<EFBFBD>k
<02>qgGG<00>https://github.com/papers-we-love/papers-we-love/blob/master/plt/fundamental-concepts-in-programming-languages.pdfFundamental Concepts in Programming Languagesplt/2017-09-11T23:06:15.9704099122017-09-11T23:06:15.970409912<EFBFBD>C<EFBFBD>f
w<>GG<00>http://eb.host.cs.st-andrews.ac.uk/drafts/effects.pdfProgramming and Reasoning with Algebraic Effects and Dependent Typesplt/2017-09-11T23:06:15.9704099122017-09-11T23:06:15.970409912<EFBFBD>9<EFBFBD>m
<02>A7GG<00>https://github.com/papers-we-love/papers-we-love/blob/master/plt/predicate-dispatching.pdfPredicate Dispatchingplt/2017-09-11T23:06:15.9704099122017-09-11T23:06:15.970409912<EFBFBD>1<EFBFBD>i	wsGG<00>https://www.cs.utah.edu/plt/publications/macromod.pdfComposable and Compilable Macros: You Want it When?plt/2017-09-11T23:06:15.9704099122017-09-11T23:06:15.970409912p<00>
<00>C7GGhttp://homepages.inf.ed.ac.uk/wadler/papers/propositions-as-types/propositions-as-types.pdfPropositions as Typesplt/2017-09-11T23:06:15.9704099122017-09-11T23:06<30>:<3A>j
<02>C7GG<00>http://homepages.inf.ed.ac.uk/wadler/papers/propositions-as-types/propositions-as-types.pdfPropositions as Typesplt/2017-09-11T23:06:15.9704099122017-09-11T23:06:15.970409912<EFBFBD>'<27>h
<02>1#GG<00>http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.24.9333&rep=rep1&type=pdfSoft Typingplt/2017-09-11T23:06:15.9704099122017-09-11T23:06:15.970409912
<00>9_GGhttp<74>-<2D>r
<02>Q!GG<00>http://www.cs.ucf.edu/courses/cop4020/sum2009/CSP-hoare.pdfCommunicating Sequential Processesprocesses/2017-09-11T23:06:15.9906779792017-09-11T23:06:15.990677979<EFBFBD>I<EFBFBD>g
<02>9_GG<00>http://www.csee.umbc.edu/courses/undergraduate/CMSC331/resources/papers/sammet1972.pdfProgramming Languages: History and Futureplt/2017-09-11T23:06:15.9704099122017-09-11T23:06:15.970409912	<09><00>
<00>O!GGhttps://moodle.risc.jku.at/pluginfile.php/3407/mod_resource/content/1/A%20Calculus%20of%20Communicating%20Systems%5B1980%5D.pdfCalculus of Communicating System<65>p<EFBFBD>s
<02>O!GG<00>https://moodle.risc.jku.at/pluginfile.php/3407/mod_resource/content/1/A%20Calculus%20of%20Communicating%20Systems%5B1980%5D.pdfCalculus of Communicating Systemsprocesses/2017-09-11T23:06:15.9906779792017-09-11T23:06:15.990677979<00>
<00>SIGGhttps://github.com/papers-we-love/papers-we-love/blob/master/plt/theory-in-programming-practice.pdfTheory in Programming Practiceplt/2017-09-11T23:06:15.9704099122<EFBFBD>K<EFBFBD>q
<02>SIGG<00>https://github.com/papers-we-love/papers-we-love/blob/master/plt/theory-in-programming-practice.pdfTheory in Programming Practiceplt/2017-09-11T23:06:15.9704099122017-09-11T23:06:15.970409912<EFBFBD><03>p<02>{<7B>GG<00>https://github.com/papers-we-love/papers-we-love/blob/master/plt/the-derivative-of-a-regular-type-one-hole-contexts.pdfThe Derivative of a Regular Type is its Type of One-Hole Contextsplt/2017-09-11T23:06:15.9704099122017-09-11T23:06:15.970409912<EFBFBD>x<EFBFBD>o
<02>wGG<00>https://github.com/papers-we-love/papers-we-love/blob/master/plt/programming-languages-application-and-interpretation.pdfProgramming Languages: Application and Interpretationplt/2017-09-11T23:06:15.9704099122017-09-11T23:06:15.970409912<EFBFBD>k<EFBFBD>n
<02>siGG<00>https://github.com/papers-we-love/papers-we-love/blob/master/plt/principal-type-schemes-for-functional-programs.pdfPrincipal type-schemes for functional programsplt/2017-09-11T23:06:15.9704099122017-09-11T23:06:15.970409912<EFBFBD>~<7E>l<02><EFBFBD>
GG<00>https://github.com/papers-we-love/papers-we-love/blob/master/plt/on-understanding-types-data-abstraction-polymorphism.pdfOn Understanding Types,
Data Abstraction, and Polymorphismplt/2017-09-11T23:06:15.9704099122017-09-11T23:06:15.970409912<00>
<00>qgGGhttps://github.com/papers-we-love/papers-we-love/blob/master/plt/fundamental-concepts-in-programming-languages.pdfFundamental Concepts in Programming Languagesplt/2017-09-11T23:06:15.9704099122017-09-11T23:06:15.970409912
`@S
<0A><0C>
@
<EFBFBD>	<09><08>3cw<04>%h<02>
<01>`<00>,<2C><02>3<EFBFBD>7GG
https://github.com/papers-we-love/papers-we-love/blob/master/sublinear_algorithms/An-Elementary-Proof-of-a-Theorem-of-Johnson-and-Lindenstrauss.pdfAn Elementary Proof of a Theorem of Johnson and Lindenstrausssublinear_algorithms/2017-09-11T23:06:16.0939550782017-09-11T23:06:16.093955078<EFBFBD><10><02>
<01>
7GG
https://github.com/papers-we-love/papers-we-love/blob/master/sublinear_algorithms/1985-Flajolet-Probabilistic-counting.pdfProbablistic Counting Algorithms for Database Applicationssublinear_algorithms/2017-09-11T23:06:16.0939550782017-09-11T23:06:16.093955078<EFBFBD>@<40>
<02>W%GG
https://en.wikipedia.org/wiki/Boyer%E2%80%93Moore_string_search_algorithmBoyer–Moore string search algorithmstringology/2017-09-11T23:06:16.0714951172017-09-11T23:06:16.071495117<EFBFBD>9<EFBFBD>
<02>17%GG
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.13.9460&rep=rep1&type=pdfFast String Searchingstringology/2017-09-11T23:06:16.0714951172017-09-11T23:06:16.071495117<EFBFBD><07>	_'%GG<00>http://en.wikipedia.org/wiki/Suffix_arraysuffix arraysstringology/2017-09-11T23:06:16.0714951172017-09-11T23:06:16.071495117<EFBFBD>C<EFBFBD>

<02>q%GG

http://www.cas.mcmaster.ca/~bill/best/algorithms/07Taxonomy.pdfA Taxonomy of Suffix Array Construction Algorithmsstringology/2017-09-11T23:06:16.0714951172017-09-11T23:06:16.071495117<EFBFBD>h<EFBFBD>	<02>/<2F>7GG
http://www.cs.ucsb.edu/~veronika/MAE/spacecomplexityapproxfreqmoments_alon_99.pdfThe Space Complexity of Approximating the Frequency Momentsstreaming_algorithms/2017-09-11T23:06:16.0709570312017-09-11T23:06:16.070957031<EFBFBD>L<EFBFBD>
w<>7GG
http://algo.inria.fr/flajolet/Publications/FlMa85.pdfProbabilistic Counting Algorithms for Data Base Applicationsstreaming_algorithms/2017-09-11T23:06:16.0709570312017-09-11T23:06:16.070957031<EFBFBD>M<EFBFBD>
<02>s7GG
http://www.inf.ed.ac.uk/teaching/courses/exc/reading/morris.pdfCounting large numbers of events in small registersstreaming_algorithms/2017-09-11T23:06:16.0709570312017-09-11T23:06:16.070957031<EFBFBD>F<EFBFBD>
<02>m3GG<00>http://www.ee.columbia.edu/~dpwe/pubs/BarkCE05-sfd-spcomm.pdfDecoding speech in the presence of other sourcesspeech_recognition/2017-09-11T23:06:16.0620839842017-09-11T23:06:16.062083984<EFBFBD>9<EFBFBD>	a{3GG<00>http://www.cs.nyu.edu/~mohri/pub/csl01.pdfWeighted Finite-State Transducers in Speech Recognitionspeech_recognition/2017-09-11T23:06:16.0620839842017-09-11T23:06:16.062083984<EFBFBD>r<EFBFBD><02><19>13GG<00>http://luthuli.cs.uiuc.edu/~daf/courses/Signals%20AI/Papers/HMMs/0.pdfA tutorial on hidden Markov models and selected applications in speech recognitionspeech_recognition/2017-09-11T23:06:16.0620839842017-09-11T23:06:16.062083984<EFBFBD>;<3B>
<02>]GG<00>http://www.techzoom.net/Papers/Browser_Silent_Updates_%282009%29.pdfWhy Silent Updates Boost Security (2009)security/2017-09-11T23:06:16.0456398932017-09-11T23:06:16.045639893<EFBFBD>I<EFBFBD>
<02>1]GG<00>http://breachattack.com/resources/BREACH%20-%20SSL,%20gone%20in%2030%20seconds.pdfBreach: Reviving The Crime Attack (2013)security/2017-09-11T23:06:16.0456398932017-09-11T23:06:16.045639893<EFBFBD>U<EFBFBD>
<02><0F>GG<00>https://www.usenix.org/events/hotos11/tech/final_files/Kannan.pdfMaking Programs Forget: Enforcing Lifetime For Sensitive Data (2011)security/2017-09-11T23:06:16.0456398932017-09-11T23:06:16.045639893<EFBFBD>:<3A>
<02>UGG<00>https://www.usenix.org/system/files/conference/woot13/woot13-kholia.pdfLooking inside the (Drop) Box (2013)security/2017-09-11T23:06:16.0456398932017-09-11T23:06:16.045639893<EFBFBD>+<2B>	qcGG<00>https://internetcensus2012.bitbucket.io/paper.htmlInternet Census via Insecure Routers (2012)security/2017-09-11T23:06:16.0456398932017-09-11T23:06:16.045639893<EFBFBD>i<EFBFBD>~<02>!<21>+GG<00>https://rse-lab.cs.washington.edu/postscripts/3d-mapping-iser-10-final.pdfRGB-D Mapping: Using Depth Cameras for Dense 3D Modeling of Indoor Environmentsrobotics/2017-09-11T23:06:16.0445410162017-09-11T23:06:16.044541016<EFBFBD><<3C>}
o<>GG<00>http://msl.cs.uiuc.edu/~lavalle/papers/Lav98c.pdfRapidly-Exploring Random Trees: A New Tool for Path Planningrobotics/2017-09-11T23:06:16.0445410162017-09-11T23:06:16.044541016
i<0E>
<0A>
En<0B>
U	<09><08><07><06><04>6s
<01>
i<00>&<26>"	=1GGhttp://www.cs.ox.ac.uk/people/nicolas.wu/papers/Scope.pdfEffect Handlers in Scopelanguages/haskell/2017-10-21T05:25:06.0342170412017-10-21T05:25:06.034217041<EFBFBD>.<2E>!
<00>71GGhttp://www.cs.ru.nl/~W.Swierstra/Publications/DataTypesALaCarte.pdfData types a la cartelanguages/haskell/2017-10-21T05:25:06.0342170412017-10-21T05:25:06.034217041<EFBFBD>*<2A> 	mW1GGhttp://okmij.org/ftp/Haskell/extensible/more.pdfFreer Monads, More Extensible Effectslanguages/haskell/2017-10-21T05:25:06.0342170412017-10-21T05:25:06.034217041<EFBFBD>?<3F>	q}1GGhttp://okmij.org/ftp/Haskell/extensible/exteff.pdfExtensible Effects: An Alternative to Monad Transformerslanguages/haskell/2017-10-21T05:25:06.0342170412017-10-21T05:25:06.034217041<EFBFBD>V<EFBFBD>
<00>7c1GGhttp://haskell.cs.yale.edu/wp-content/uploads/2011/02/POPL96-Modular-interpreters.pdfMonad Transformers and Modular Interpreterslanguages/haskell/2017-10-21T05:25:06.0342170412017-10-21T05:25:06.034217041<EFBFBD>e<EFBFBD>
<00>aW1GGhttps://page.mi.fu-berlin.de/scravy/realworldhaskell/materialien/the-essence-of-functional-programming.pdfThe Essence of Functional Programminglanguages/haskell/2017-10-21T05:25:06.0342170412017-10-21T05:25:06.034217041<EFBFBD><1C>
<00>WO1GGhttps://ac.els-cdn.com/0890540191900524/1-s2.0-0890540191900524-main.pdf?_tid=45497e1c-b5c9-11e7-963f-00000aacb361&acdnat=1508526351_2f3bf288ce0f81ff89fb10ece92eeb9eNotions of Computation and Monadslanguages/haskell/2017-10-21T05:25:06.0342170412017-10-21T05:25:06.034217041<EFBFBD>3<EFBFBD>	iOOGGhttps://www.cs.cmu.edu/~rwh/theses/okasaki.pdfPurely Functional Data Structuresparadigms/functional_programming/2017-10-20T05:25:06.0079221192017-10-20T05:25:06.007922119<EFBFBD>:<3A>
c<>	'GGhttps://papers.mathyvanhoef.com/ccs2017.pdfKey Reinstallation Attacks: Forcing Nonce Reuse in WPA2 (2017)cryptography/2017-10-19T05:25:06.1591359862017-10-19T05:25:06.159135986<EFBFBD><0B><00><17>KQGGhttp://web.media.mit.edu/~minsky/papers/Why%20programming%20is--.htmlWhy Programming is a good medium for expressing poorly understood and sloppily-formulated ideascomp_sci_fundamentals_and_history/2017-10-04T05:25:05.8415810552017-10-04T05:25:05.841581055<EFBFBD>c<EFBFBD>
<00>uQGGhttp://www3.alcatel-lucent.com/bstj/vol34-1955/articles/bstj34-5-1045.pdfMealy, A Method for Synthesizing Sequential Circuitscomp_sci_fundamentals_and_history/2017-10-04T05:25:05.8415810552017-10-04T05:25:05.841581055<EFBFBD>M<EFBFBD>
g<>/GG

http://www.vmware.com/pdf/asplos235_adams.pdfA Comparison of Software and Hardware Techniques for x86
  Virtualizationvirtual_machines/2017-09-11T23:06:16.1364870612017-09-11T23:06:16.136487061<EFBFBD>6<EFBFBD>
<02>;/GG
http://lafo.ssw.uni-linz.ac.at/papers/2013_Onward_OneVMToRuleThemAll.pdfOne VM to Rule Them Allvirtual_machines/2017-09-11T23:06:16.1364870612017-09-11T23:06:16.136487061<EFBFBD>%<25>	C-CC
http://www.voelter.de/data/pub/projectingModuleFuture.pdfProjecting a modular futureuser_interfaces/2017-09-11T23:06:16.13565212017-09-11T23:06:16.1356521<EFBFBD>2<EFBFBD>	si-CC
	http://ordiecole.com/squeak/cardelli_squeak1985.pdfSqueak: a Language for Communicating with Miceuser_interfaces/2017-09-11T23:06:16.13565212017-09-11T23:06:16.1356521<EFBFBD>S<EFBFBD>
U<>G%GG
http://futuredata.stanford.edu/asap/ASAP: Automatic Smoothing for Attention Prioritization in Streaming Time Series Visualizationtime_series/2017-09-11T23:06:16.1183569342017-09-11T23:06:16.118356934<EFBFBD>0<EFBFBD>	Y%GG
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=208278Operators on Inhomogeneous Time Seriestime_series/2017-09-11T23:06:16.1183569342017-09-11T23:06:16.118356934<EFBFBD><EFBFBD><02><07>k%GG

http://www.msr-waypoint.net/en-us/groups/ese/nagappan_tdd.pdfRealizing quality improvement through test driven development: results and experiences of four industrial teamstesting/tdd/2017-09-11T23:06:16.1154199222017-09-11T23:06:16.115419922<EFBFBD><00>
<02>_1GG
http://www.elizabete.com.br/site/Outros/Entradas/2012/11/19_Revisao_Sistematica_files/ConceitosRevisaoSistematica_Biolchini.pdfSystematic Review in Software Engineeringsystematic_review/2017-09-11T23:06:16.0948500982017-09-11T23:06:16.094850098

Z,<00><0E>
l<0C>
8<0E><00>p<02><03><02><05><0C><00>E<0E>u%dZ'<0B><0B><07>_<04>
<EFBFBD>
<EFBFBD>
F
	<09><04>	`$7<07>	
<08><06>jf<03>D<04>	https://research.microsoft.com/en-us/um/people/nick/coqasm.pdf<00><><04>https://moodle.risc.jku.at/pluginfile.php/3407/mod_resource/content/1/A%20Calculus%20of%20Communicating%20Systems%5B1980%5D.pdf<00>#https://githu<68>I<04>https://github.com/tpn/pdfs/raw/master/Realizing%20Quality%20Improvement%20Through%20Test%20Driven%20Development%20-%20Results%20and%20Experiences%20of%20Four%20Industrial%20Teams%20(nagappan_tdd
*a<04>Chttps://www.tk.informatik.tu-darmstadt.de/fileadmin/user_upload/Group_TK/zhou2010survey.pdf
%O<04>https://people.cs.kuleuven.be/~tom.schrijvers/Research/papers/mpc2015.pdf
#p<04>ahttps://page.mi.fu-berlin.de/scravy/realworldhaskell/materialien/the-essence-of-functional-programming.pdf
3ihttps://www.cs.cmu.edu/~rwh/theses/okasaki.pdf
0chttps://papers.mathyvanhoef.com/ccs2017.pdf
M<04>https://www.usenix.org/system/files/conference/woot13/woot13-kholia.pdf
7qhttps://internetcensus2012.bitbucket.io/paper.html<00>P<04>!https://rse-lab.cs.washington.edu/postscripts/3d-mapping-iser-10-final.pdf<00>:whttps://www.cs.utah.edu/plt/publications/macromod.pdf<00>S<04>'https://www.seas.harvard.edu/sites/default/files/files/archived/Czaplicki.pdf<00>O<04>https://us-east.manta.joyent.com/bcantrill/public/ppwl-cantrill-zones.pdf<00>O<04>https://us-east.manta.joyent.com/bcantrill/public/ppwl-cantrill-jails.pdf<00>B<04>https://people.csail.mit.edu/nickolai/papers/clements-sc.pdf<00>a<04>Chttps://www.usenix.org/legacy/publications/library/proceedings/bos94/full_papers/bonwick.ps<00>`<04>Ahttps://www.usenix.org/legacy/publications/library/proceedings/bos94/full_papers/bonwick.a<00>W<04>/https://www.usenix.org/legacy/publications/library/proceedings/bos94/bonwick.html<00>
0https://cs.brown_<04>?https://irenelopatovska.files.wordpress.com/2012/10/lopatovska_arapakis_2011_theories.pdf
,G<04>https://www.usenix.org/events/hotos11/tech/final_files/Kannan.pdf

C<04>https://www.cs.princeton.edu/~chazelle/pubs/FJLT-sicomp09.pdf<00>A<04>https://www.stat.berkeley.edu/~breiman/randomforest2001.pdf<00>Q<04>#https://www.usenix.org/system/files/conference/osdi14/osdi14-paper-yuan.pdf<00>T<04>+
https://www.usenix.org/legacy/events/hotos03/tech/full_papers/candea/candea.pdfBR<04>'
https://www.usenix.org/legacy/event/osdi04/tech/full_papers/candea/candea.pdfC7qhttps://www.sics.se/~seif/DatalogiII/Book/train.ps<00>z<04>w
https://www.researchgate.net/publication/220080099_MEXICA_A_computer_model_of_a_cognitive_account_of_creative_writing2ghttps://www.lri.fr/~filliatr/publis/enum2.pdf<00>R<04>'
https://www.ics.uci.edu/~fielding/pubs/dissertation/fielding_dissertation.pdfD<04>
https://www.eecs.berkeley.edu/~daw/papers/intents-mobisys11.pdf=
https://www.cs.virginia.edu/~robins/Turing_Paper_1936.pdfB<04>
https://www.cs.unc.edu/~welch/kalman/media/pdf/Kalman1960.pdfKD<04>	https://www.cs.purdue.edu/homes/hosking/690M/p611-fenichel.pdf<00>K<04>
https://www.cs.drexel.edu/~david/Classes/CS586/Papers/p343-whitted.pdf 6ohttps://www.cs.cornell.edu/home/kleinber/auth.pdf<00><}
https://www.cs.cornell.edu/fbs/publications/SMSurvey.pdfp;yhttps://www.cs.cmu.edu/~dga/papers/epaxos-sosp2013.pdf<00>;{
https://people.eecs.berkeley.edu/~brewer/cs262/Mesa.pdf@S<04>)
https://homes.cs.washington.edu/~luisceze/publications/dnastorage-asplos16.pdf~
@%
https://github.com/papers-we-love/papers-we-love/blob/master/caching/a-constant-algorithm-for-implementing-the-lfu-cache-eviction-scheme.pdf<16><04>
https://github.com/papers-we-love/papers-we-love/blob/master/artificial_intelligence/3-bayesian-network-inference-algorithm.pdf9w
https://github.com/luanfujun/deep-p7https://osf.io/6qzxc/
0*Whttps://spectreattack.com/spectre.pdf
.,[https://meltdownattack.com/meltdown.pdf
-<2D><04>3https://github.com/papers-we-love/papers-we-love/blob/master/sublinear_algorithms/An-Elementary-Proof-of-a-Theorem-of-Johnson-and-Lindenstrauss.pdf
<00>
https://github.com/papers-we-love/papers-we-love/blob/master/sublinear_algorithms/1985-Flajolet-Probabilistic-counting.pdf

<00>
S8<00>
 In this work we thus present FlowDroid, a novel and highly precise static taint analysis for Android applications. A precise model of Android's lifecycle allows the analysis to properly handle callbacks invoked by the Android framework, while context, flow, field and object-sensitivity allows the analysis to reduce the number of false alarms. Novel on-demand algorithms help FlowDroid maintain high efficiency and precision at the same time.
 We also propose DroidBench, an open test suite for evaluating the effectiveness and accuracy of taint-analysis tools specifically for Android apps. As we show through a set of experiments using SecuriBench Micro, DroidBench, and a set of well-known Android test applications, FlowDroid finds a very high fraction of data leaks while keeping the rate of false positives low. On DroidBench, FlowDroid achieves 93% recall and 86% precision, greatly outperforming the commercial tools IBM AppScan Source and Fortify SCA. FlowDroid successfully finds leaks in a subset of 500 apps from Google Play and about 1,000 malware apps from the VirusShare project.PLDIandroid/2017-09-11T23:06:19.2972309572017-09-11T23:06:19.297230957<EFBFBD>*
<00><02>wUEEReverend Bayes on Inference Engines: A Distributed Hierarchical Approach<07>This paper presents generalizations of Bayes likelihood-ratio updating rule which facilitate an asynchronous propagation of the impacts of new beliefs and/or new evidence in hierarchically organized inference structures with multi-hypotheses variables. The computational scheme proposed specifies a set of belief parameters, communication messages and updating rules which guarantee that the diffusion of updated beliefs is accomplished in a single pass and complies with the tenets of Bayes calculus.AAAIartificial_intelligence/judea_pearl/2017-09-11T23:06:19.176239992017-09-11T23:06:19.17623999
<04>(<04><00>q
C<02>w=GGDirect and Indirect Effects<07>The direct effect of one event on another can be defined and measured by holding constant all intermediate variables between the two. Indirect effects present conceptual and prac­ tical difficulties (in nonlinear models), be­ cause they cannot be isolated by holding cer­ tain variables constant. This paper presents a new way of defining the effect transmit­ ted through a restricted set of paths, without controlling variables on the remaining paths. This permits the assessment of a more nat­ ural type of direct and indirect effects, one that is applicable in both linear and nonlinear models and that has broader policy-related interpretations. The paper establishes con­ ditions under which such assessments can be estimated consistently from experimen­ tal and nonexperimental data, and thus ex­ tends path-analytic techniques to nonlinear and nonparametric models. The distinction between total, direct, and indirect ef­ fects is deeply entrenched in causal conversations, and attains practical importance in many applications, in­ cluding policy decisions, legal definitions and health care analysis. Structural equation modeling (SEM) (Goldberger 1972), which provides a methodology of defining and estimating such effects, has been re­ stricted to linear analysis, and no comparable method­ ology has been devised to extend these capabilities to models involving nonlinear dependencies,1 as those 1 A notable exception is the counterfactual analysis of Robins and Greenland (1992) which is applicable to non­ linear models, but does not incorporate path-analytic tech­ niques. The causal relationship that is easiest to interpret, define and estimate is the total effect. Written as P(Y"' = y), the total effect measures the probability that response variable Y would take on the value y when X is set to x by external intervention.2 This probability function is what we normally assess in a controlled experiment in which X is randomized and in which the distribution of Y is estimated for each level x of X. In many cases, however, this quantity does not ade­ quately represent the target of investigation and at­ tention is focused instead on the direct effect of X on Y. The term "direct effect" is meant to quantify an influence that is not mediated by other variables in the model or, more accurately, the sensitivity of Y to changes in X while all other factors in the analysis are held fixed. Naturally, holding those factors fixed would sever all causal paths from X to Y with the exception of the direct link …UAIartificial_intelligence/2017-09-11T23:06:19.8314470212017-09-11T23:06:19.831447021<EFBFBD>U
<00>{

=GGAnalysis of Three Bayesian Network Inference Algorithms: Variable Elimination, Likelihood Weighting, and Gibbs Sampling<07>artificial_intelligence/2017-09-11T23:06:19.7328769532017-09-11T23:06:19.732876953

<EFBFBD><00>A
U<02>
=AAComputing Machinery and Intelligence<07>I propose to consider the question, "Can machines think?" This should begin with definitions of the meaning of the terms "machine" and "think." The definitions might be framed so as to reflect so far as possible the normal use of the words, but this attitude is dangerous, If the meaning of the words "machine" and "think" are to be found by examining how they are commonly used it is difficult to escape the conclusion that the meaning and the answer to the question, "Can machines think?" is to be sought in a statistical survey such as a Gallup poll. But this is absurd. Instead of attempting such a definition I shall replace the question by another, which is closely related to it and is expressed in relatively unambiguous words. The new form of the problem can be described in terms of a game which we call the 'imitation game." It is played with three people, a man (A), a woman (B), and an interrogator (C) who may be of either sex. The interrogator stays in a room apart front the other two. The object of the game for the interrogator is to determine which of the other two is the man and which is the woman. He knows them by labels X and Y, and at the end of the game he says either "X is A and Y is B" or "X is B and Y is A." The interrogator is allowed to put questions to A and B thus: C: Will X please tell me the length of his or her hair? Now suppose X is actually A, then A must answer. It is A's object in the game to try and cause C to make the wrong identification. His answer might therefore be: "My hair is shingled, and the longest strands are about nine inches long." In order that tones of voice may not help the interrogator the answers should be written, or better still, typewritten. The ideal arrangement is to have a teleprinter communicating between the two rooms. Alternatively the question and answers can be repeated by an intermediary. The object of the game for the third player (B) is to help the interrogator. The best strategy for her is probably to give truthful answers. She can add such things as "I am the woman, don't listen to him!" to her answers, but it will avail …artificial_intelligence/2017-09-11T23:06:19.9703752017-09-11T23:06:19.970375<EFBFBD>3
u<02>aGGAnalyzing inter-application communication in Android<07>Modern smartphone operating systems support the development of third-party applications with open system APIs. In addition to an open API, the Android operating system also provides a rich inter-application message passing system. This encourages inter-application collaboration and reduces developer burden by facilitating component reuse. Unfortunately, message passing is also an application attack surface. The content of messages can be sniffed, modified, stolen, or replaced, which can compromise user privacy. Also, a malicious application can inject forged or otherwise malicious messages, which can lead to breaches of user data and violate application security policies.
 We examine Android application interaction and identify security risks in application components. We provide a tool, ComDroid, that detects application communication vulnerabilities. ComDroid can be used by developers to analyze their own applications before release, by application reviewers to analyze applications in the Android Market, and by end users. We analyzed 20 applications with the help of ComDroid and found 34 exploitable vulnerabilities; 12 of the 20 applications have at least one vulnerability.MobiSysandroid/2017-09-11T23:06:19.8910729982017-09-11T23:06:19.891072998
<02>l<0B><06><02><00>!
I<02>;UGGA Theory of Inferred Causation<07>This paper concerns the empirical basis of causation, and addresses the following issues: 1. the clues that might prompt people to perceive causal relationships in uncontrolled observations. 2. the task of inferring causal models from these clues, and 3. whether the models inferred tell us anything useful about the causal mechanisms that underly the observations. We propose a minimal-model semantics of causation, and show that, contrary to common folklore, genuine causal innuences can be distinguished from spurious covariations following standard norms of inductive reasoning. We also establish a sound characterization of the conditions under which such a distinction is possible. We provide an effective algorithm for inferred causation and show that, for a large class of data the algorithm can uncover the direction of causal innuences as deened above. Finally, we address the issue of non-temporal causation.KRartificial_intelligence/judea_pearl/2017-09-11T23:06:20.4471569822017-09-11T23:06:20.447156982<EFBFBD>
<00><02>e=GGMastering the game of Go with deep neural networks and tree search<07>The game of Go has long been viewed as the most challenging of classic games for artificial intelligence owing to its enormous search space and the difficulty of evaluating board positions and moves. Here we introduce a new approach to computer Go that uses 'value networks' to evaluate board positions and 'policy networks' to select moves. These deep neural networks are trained by a novel combination of supervised learning from human expert games, and reinforcement learning from games of self-play. Without any lookahead search, the neural networks play Go at the level of state-of-the-art Monte Carlo tree search programs that simulate thousands of random games of self-play. We also introduce a new search algorithm that combines Monte Carlo simulation with value and policy networks. Using this search algorithm, our program AlphaGo achieved a 99.8% winning rate against other Go programs, and defeated the human European Go champion by 5 games to 0. This is the first time that a computer program has defeated a human professional player in the full-sized game of Go, a feat previously thought to be at least a decade away.Natureartificial_intelligence/2017-09-11T23:06:20.1121799322017-09-11T23:06:20.112179932<EFBFBD>	
<00>#

#GGArchitectural Styles and the Design of Network-based Software Architectures<07>api_design/2017-09-11T23:06:20.0495681152017-09-11T23:06:20.049568115<EFBFBD>
_<02>9GGSecurity Concerns in Android mHealth Apps<07>Mobile Health (mHealth) applications lie outside of regulatory protection such as HIPAA, which requires a baseline of privacy and security protections appropriate to sensitive medical data. However, mHealth apps, particularly those in the app stores for iOS and Android, are increasingly handling sensitive data for both professionals and patients. This paper presents a series of three studies of the mHealth apps in Google Play that show that mHealth apps make widespread use of unsecured Internet communications and third party servers. Both of these practices would be considered problematic under HIPAA, suggesting that increased use of mHealth apps could lead to less secure treatment of health data unless mHealth vendors make improvements in the way they communicate and store data.AMIAandroid/2017-09-11T23:06:20.0082419432017-09-11T23:06:20.008241943
<0C>	<09><04><00>[<00><02>/+GGThe BUDS Language for Distributed Bayesian Machine Learning<07>We describe BUDS, a declarative language for succinctly and simply specifying the implementation of large-scale machine learning algorithms on a distributed computing platform. The types supported in BUDS--vectors, arrays, etc.--are simply logical abstractions useful for programming, and do not correspond to the actual implementation. In fact, BUDS automatically chooses the physical realization of these abstractions in a distributed system, by taking into account the characteristics of the data. Likewise, there are many available implementations of the abstract operations offered by BUDS (matrix multiplies, transposes, Hadamard products, etc.). These are tightly coupled with the physical representation. In BUDS, these implementations are co-optimized along with the representation. All of this allows for the BUDS compiler to automatically perform deep optimizations of the user's program, and automatically generate efficient implementations.SIGMOD Conferenceaudio_comp_sci/2017-09-11T23:06:20.7854230962017-09-11T23:06:20.785423096<EFBFBD>E
m<02>

+GGEvaluating Generative Models for Text Generation<07>Generating human quality text is a challenging problem because of ambiguity of meaning and difficulty in modeling long term semantic connections. Recurrent Neural Networks (RNNs) have shown promising results in this problem domain, with the most common approach to its training being to maximize the log predictive likelihood of each true token in the training sequence given the previously observed tokens. Scheduled Sampling, proposed by Bengio et al. (2015), was proposed as an improvement to the maximum likelihood approach by stochastically introducing inference steps during training steps. More recently, Generative Adversarial Nets (GAN) that use a discriminative model to guide the training of the generative model have become popular in vision domain, and also reinterpreted as a reinforcement learning problem to adapt it to text generation by Yu et al. (2016). Here we test and compare these three approaches and thus hope to extend the evaluation presented for the SeqGAN model in Yu et al. (2016) using two additional datasets and an additional perplexity evaluation metric.audio_comp_sci/2017-09-11T23:06:20.7041730962017-09-11T23:06:20.704173096<EFBFBD>&
[<02>UoUGGThe algorithmization of counterfactuals<07>Recent advances in causal reasoning have given rise to a computation model that emulates the process by which humans generate, evaluate and distinguish counterfactual sentences. Though compatible with the “possible worlds” account, this model enjoys the advantages of representational economy, algorithmic simplicity and conceptual clarity. Using this model, the paper demonstrates the processing of counterfactual sentences on a classical example due to Ernest Adam. It then gives a panoramic view of several applications where counterfactual reasoning has benefited problem areas in the empirical sciences.Annals of Mathematics and Artificial Intelligenceartificial_intelligence/judea_pearl/2017-09-11T23:06:20.6384050292017-09-11T23:06:20.638405029<EFBFBD>/
Y<02>K
UGGCausal Diagrams for Empirical Research<07>The primary aim of this paper is to show how graphical models can be used as a mathematical language for integrating statistical and subject-matter information. In particular, the paper develops a principled, nonparametric framework for causal inference, in which diagrams are queried to determine if the assumptions available are suucient for identifying causal eeects from non-experimental data. If so the diagrams can be queried to produce mathematical expressions for causal eeects in terms of observed distributions; otherwise, the diagrams can be queried to suggest additional observations or auxiliary experiments from which the desired inferences can be obtained.artificial_intelligence/judea_pearl/2017-09-11T23:06:20.5518000492017-09-11T23:06:20.551800049
<03>
><03><00>*
g<02>['GGVEWS: A Wikipedia Vandal Early Warning System<07>We study the problem of detecting vandals on Wikipedia <i>before</i> any human or known vandalism detection system reports flagging potential vandals so that such users can be presented early to Wikipedia administrators. We leverage multiple classical ML approaches, but develop 3 novel sets of features. Our Wikipedia Vandal Behavior (WVB) approach uses a novel set of user editing patterns as features to classify some users as vandals. Our Wikipedia Transition Probability Matrix (WTPM) approach uses a set of features derived from a transition probability matrix and then reduces it via a neural net auto-encoder to classify some users as vandals. The VEWS approach merges the previous two approaches. Without using any information (e.g. reverts) provided by other users, these algorithms each have over 85% classification accuracy. Moreover, when temporal recency is considered, accuracy goes to almost 90%. We carry out detailed experiments on a new data set we have created consisting of about 33K Wikipedia users (including both a black list and a white list of editors) and containing 770K edits. We describe specific behaviors that distinguish between vandals and non-vandals. We show that VEWS beats ClueBot NG and STiki, the best known algorithms today for vandalism detection. Moreover, VEWS detects far more vandals than ClueBot NG and on average, detects them 2.39 edits before ClueBot NG when both detect the vandal. However, we show that the combination of VEWS and ClueBot NG can give a fully automated vandal early warning system with even higher accuracy.KDDbiocomputing/2017-09-11T23:06:20.9852609862017-09-11T23:06:20.985260986<EFBFBD>?
c<02>+GGSafety Verification of Deep Neural Networks<07>Deep neural networks have achieved impressive experimental results in image classification, but can surprisingly be unstable with respect to adver-sarial perturbations, that is, minimal changes to the input image that cause the network to misclassify it. With potential applications including perception modules and end-to-end controllers for self-driving cars, this raises concerns about their safety. We develop the first SMT-based automated verification framework for feed-forward multi-layer neural networks that works directly with the code of the network, exploring it layer by layer. We define safety for a region around a data point in a given layer by requiring that all points in the region are assigned the same class label. Working with a notion of a manipulation, a mapping between points that intuitively corresponds to a modification of an image, we employ discretisation to enable exhaustive search of the region. Our method can guarantee that adversarial examples are found for the given region and set of manipulations. If found, adversarial examples can be shown to human testers and/or used to fine-tune the network, and otherwise the network is declared safe for the given parameters. We implement the techniques using Z3 and evaluate them on state-of-the-art networks, including regularised and deep learning networks.CAVaudio_comp_sci/2017-09-11T23:06:20.8417080082017-09-11T23:06:20.841708008
<03>H
YZ<03><00>y]<02>q<EFBFBD>-GGBIG Cache Abstraction for Cache Networks<07>In this paper, we advocate the notion of &#x0022;BIG&#x0022; cache as an innovative abstraction for effectively utilizing the distributed storage and processing capacities of all servers in a cache network. The &#x0022;BIG&#x0022; cache abstraction is proposed to partly address the problem of (cascade) thrashing in a hierarchical network of cache servers, where it has been known that cache resources at intermediate servers are poorly utilized, especially under classical cache replacement policies such as LRU. We lay out the advantages of &#x0022;BIG&#x0022; cache abstraction and make a strong case both from a theoretical standpoint as well as through simulation analysis. We also develop the dCLIMB cache algorithm to minimize the overheads of moving objects across distributed cache boundaries and present a simple yet effective heuristic for addressing the cache allotment problem in the design of &#x0022;BIG&#x0022; cache abstraction.2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS)caching/2017-09-11T23:06:21.4933010252017-09-11T23:06:21.493301025<EFBFBD>|
S<02>
'GGThe chemical basis of morphogenesis<07>Concurrent algorithms and the memory bus have garnered improbable interest from both theorists and futurists in the last several years. In fact, few scholars would disagree with the refinement of multicast heuristics. In order to fulfill this objective, we present a framework for virtual technology (Puck), confirming that lambda calculus can be made wearable, self-learning, and unstable.biocomputing/2017-09-11T23:06:21.2694760742017-09-11T23:06:21.269476074<EFBFBD>l<00><02>5'GGMolecular computation of solutions to combinatorial problems.<07>The tools of molecular biology were used to solve an instance of the directed Hamiltonian path problem. A small graph was encoded in molecules of DNA, and the "operations" of the computation were performed with standard protocols and enzymes. This experiment demonstrates the feasibility of carrying out computations at the molecular level.Sciencebiocomputing/2017-09-11T23:06:21.2355869142017-09-11T23:06:21.235586914<EFBFBD>5
A<02>y-+GGInteractive topic modeling<07>Topic models are a useful and ubiquitous tool for understanding large corpora. However, topic models are not perfect, and for many users in computational social science, digital humanities, and information studies—who are not machine learning experts—existing models and frameworks are often a “take it or leave it” proposition. This paper presents a mechanism for giving users a voice by encoding users’ feedback to topic models as correlations between words into a topic model. This framework, interactive topic modeling (itm), allows untrained users to encode their feedback easily and iteratively into the topic models. Because latency in interactive systems is crucial, we develop more efficient inference algorithms for tree-based topic models. We validate the framework both with simulated and real users.Machine Learningaudio_comp_sci/2017-09-11T23:06:21.1205358892017-09-11T23:06:21.120535889

<01><0B>
<01><00>^<00>#<02>
GG2Q: A Low Overhead High Performance Buffer Management Replacement Algorithm<07>In a path-breaking paper last year Pat and Betty O'Neil and Gerhard Weikum proposed a self-tuning improvement to the Least Recently Used (LRU) buuer management algorithmm15]. Their improvement is called LRU/k and advocates giving priority to buuer pages based on the kth most recent access. (The standard LRU algorithm is denoted LRU/1 according to this terminology.) If P1's kth most recent access is more more recent than P2's, then P1 will be replaced after P2. Intuitively, LRU/k for k > 1 is a good strategy , because it gives low priority to pages that have been scanned or to pages that belong to a big randomly accessed le (e.g., the account le in TPC/A). They found that LRU/2 achieves most of the advantage of their method. The one problem of LRU/2 is the processor overhead to implement it. In contrast to LRU, each page access requires log N work to manipulate a priority queue where N is the number of pages in the buuer. Question: is there low overhead way (constant overhead per access as in LRU) to achieve similar page 0 replacement performance to LRU/2? Answer: Yes. Our \Two Queue" algorithm (hereafter 2Q) has constant time overhead, performs as well as LRU/2, and requires no tuning. These results hold for real (DB2 commercial, Swiss bank) traces as well as simulated ones. Based on these experiments, we estimate that 2Q will provide a few percent improvement over LRU without increasing the overhead by more than a constant additive factor. 1 Background Fetching data from disk requires at least a factor of 1000 more time than fetching data from a RAM buuer. For this reason, good use of the buuer can signii-cantly improve the throughput and response time of any data-intensive system. Until the early 80's, the least recently used buuer replacement algorithm (replace the page that was least recently accessed or used) was the algorithm of choice in nearly all cases. Indeed, the theoretical community blessed it by showing that LRU never replaces more than a factor B as many elements as an optimal clair-voyant algorithm (where B is the size of the buuer) 19]. 1 Factors this large can heavily innuence the behavior of a database system, however. Furthermore , database systems usually have access patterns in which LRU performs poorly, as noted by Stone-braker 21], Sacco and Schkolnick 18], and Chou and Dewitt 5]. As a result, there …VLDBcaching/2017-09-11T23:06:21.6556608892017-09-11T23:06:21.655660889<EFBFBD>q
S<02>w'GGA DNA-Based Archival Storage System<07>Demand for data storage is growing exponentially, but the capacity of existing storage media is not keeping up. Using DNA to archive data is an attractive possibility because it is extremely dense, with a raw limit of 1 exabyte/mm<sup>3</sup> (109 GB/mm<sup>3</sup>), and long-lasting, with observed half-life of over 500 years. This paper presents an architecture for a DNA-based archival storage system. It is structured as a key-value store, and leverages common biochemical techniques to provide random access. We also propose a new encoding scheme that offers controllable redundancy, trading off reliability for density. We demonstrate feasibility, random access, and robustness of the proposed encoding with wet lab experiments involving 151 kB of synthesized DNA and a 42 kB random-access subset, and simulation experiments of larger sets calibrated to the wet lab experiments. Finally, we highlight trends in biotechnology that indicate the impending practicality of DNA storage for much larger datasets.ASPLOSbiocomputing/2017-09-11T23:06:21.5554060062017-09-11T23:06:21.555406006
W<0C>	<09>5W<00>[<00><02>CG?GGMEXICA: A computer model of a cognitive account of creative writing<07>MEXICA is a computer model that produces frameworks for short stories based on the engagement-reflection cognitive account of writing. During engagement MEXICA generates material guided by content and rhetorical constraints, avoiding the use of explicit goals or story-structure information. During reflection the system breaks impasses, evaluates the novelty and interestingness of the story in progress and verifies that coherence requirements are satisfied. In this way, MEXICA complements and extends those models of computerised story-telling based on traditional problem-solving techniques where explicit goals drive the generation of stories. This paper describes the engagement-reflection account of writing, the general characteristics of MEXICA and reports an evaluation of the programJ. Exp. Theor. Artif. Intell.computational_creativity/2017-09-11T23:06:22.0232080082017-09-11T23:06:22.023208008<EFBFBD>&<00><02>;GGA program optimization for automatic database result caching<07>Most popular Web applications rely on persistent databases based on languages like SQL for declarative specification of data models and the operations that read and modify them. As applications scale up in user base, they often face challenges responding quickly enough to the high volume of requests. A common aid is caching of database results in the application&#039;s memory space, taking advantage of program-specific knowledge of which caching schemes are sound and useful, embodied in handwritten modifications that make the program less maintainable. These modifications also require nontrivial reasoning about the read-write dependencies across operations. In this paper, we present a compiler optimization that automatically adds sound SQL caching to Web applications coded in the Ur/Web domain-specific functional language, with no modifications required to source code. We use a custom cache implementation that supports concurrent operations without compromising the transactional semantics of the database abstraction. Through experiments with microbenchmarks and production Ur/Web applications, we show that our optimization in many cases enables an easy doubling or more of an application&#039;s throughput, requiring nothing more than passing an extra command-line flag to the compiler.POPLcaching/2017-09-11T23:06:21.9159089362017-09-11T23:06:21.915908936<EFBFBD>

k<02>
9GGOn the resemblance and containment of documents<07>Given two documents A and B we define two mathematical notions: their resemblance r(A, B) and their containment c(A, B) that seem to capture well the informal notions of " roughly the same " and " roughly contained. " The basic idea is to reduce these issues to set intersection problems that can be easily evaluated by a process of random sampling that can be done independently for each document. Furthermore, the resemblance can be evaluated using a fixed size sample for each document. This paper discusses the mathematical properties of these measures and the efficient implementation of the sampling process using Rabin fingerprints.clustering_algorithms/2017-09-11T23:06:21.8212780762017-09-11T23:06:21.821278076<EFBFBD><00><02>U
QGGOn computable numbers with an application to the Entscheidungsproblem<07>Many cyberneticists would agree that, had it not been for consistent hashing, the simulation of checksums might never have occurred. After years of essential research into replication, we prove the analysis of online algorithms, which embodies the confirmed principles of robotics. Our focus in our research is not on whether digital-to-analog converters and evolutionary programming can agree to accomplish this mission, but rather on constructing a novel framework for the construction of scatter/gather I/O (HOLLEE). while such a hypothesis is usually an intuitive objective, it is derived from known results.comp_sci_fundamentals_and_history/2017-09-11T23:06:21.7456589362017-09-11T23:06:21.745658936
<03>
<0A>4<03><00>#
<00>#

1GGDigital Video Stabilization and Rolling Shutter Correction using Gyroscopes<07>computer_graphics/2017-09-11T23:06:22.2824418952017-09-11T23:06:22.282441895<EFBFBD><00><02>q
9GGPiranha: A scalable architecture based on single-chip multiprocessing<07>The microprocessor industry is currently struggling with higher development costs and longer design times that arise from exceedingly complex processors that are pushing the limits of instruction-level parallelism. Meanwhile, such designs are especially ill suited for important commercial applications, such as on-line transaction processing (OLTP), which suffer from large memory stall times and exhibit little instruction-level parallelism. Given that commercial applications constitute by far the most important market for high-performance servers, the above trends emphasize the need to consider alternative processor designs that specifically target such workloads. The abundance of explicit thread-level parallelism in commercial workloads, along with advances in semiconductor integration density, identify chip multiprocessing (CMP) as potentially the most promising approach for designing processors targeted at commercial servers. This paper describes the Piranha system, a research prototype being developed at Compaq that aggressively exploits chip multi-processing by integrating eight simple Alpha processor cores along with a two-level cache hierarchy onto a single chip. Piranha also integrates further on-chip functionality to allow for scalable multiprocessor configurations to be built in a glueless and modular fashion. The use of simple processor cores combined with an industry-standard ASIC design methodology allow us to complete our prototype within a short time-frame, with a team size and investment that are an order of magnitude smaller than that of a commercial microprocessor. Our detailed simulation results show that while each Piranha processor core is substantially slower than an aggressive next-generation processor, the integration of eight cores onto a single chip allows Piranha to outperform next-generation processors by up to 2.9 times (on a per chip basis) on important workloads such as OLTP. This performance advantage can approach a factor of five by using full-custom instead of ASIC logic. In addition to exploiting chip multiprocessing, the Piranha prototype incorporates several other unique design choices including a shared second-level cache with no inclusion, a highly optimized cache coherence protocol, and a novel I/O architecture.computer_architecture/2017-09-11T23:06:22.1723798832017-09-11T23:06:22.172379883<EFBFBD>2
S
<0A>_
QGGObject Space Silhouette AlgorithimsIn computer graphics, silhouette extraction and rendering has a critical role in a growing number of applications. This paper examines five object space silhouette extraction algorithms for polygonal models. The algorithms are applied to a variety of models and compared in terms of code complexity and run time performance. The purpose of this paper is to inform programmers who must choose from among these five algorithms.comp_sci_fundamentals_and_history/2017-09-11T23:06:22.0886579592017-09-11T23:06:22.088657959

<01>	<09><05>
<01><00>j"
e<02>C#1GGIllumination for Computer Generated Pictures<07>The quality of computer generated images of three-dimensional scenes depends on the shading technique used to paint the objects on the cathode-ray tube screen. The shading algorithm itself depends in part on the method for modeling the object, which also determines the hidden surface algorithm. The various methods of object modeling, shading, and hidden surface removal are thus strongly interconnected. Several shading techniques corresponding to different methods of object modeling and the related hidden surface algorithms are presented here. Human visual perception and the fundamental laws of optics are considered in the development of a shading rule that provides better quality and increased realism in generated images.Commun. ACMcomputer_graphics/2017-09-11T23:06:23.0423911132017-09-11T23:06:23.042391113<EFBFBD>!	W
71GGContinuous Shading of Curved Surfaces<07>IEEE Trans. Computerscomputer_graphics/2017-09-11T23:06:22.9449960942017-09-11T23:06:22.944996094<EFBFBD> 
o<02>
-1GGAn improved illumination model for shaded display<07>To accurately render a scene, global illumination information that affects the intensity of each pixel of the image must be known at the time the intensity is calculated. In a simplified form, this information is stored in a tree of &#8220;rays&#8221; extending from the viewer to the first surface encountered and from there to other surfaces and to the light sources. The visible surface algorithm creates this tree for each pixel of the display and passes it to the shader. The shader then traverses the tree to determine the intensity of the light received by the viewer. Consideration of all of these factors allows the shader to accurately simulate true reflection, shadows, and refraction as well as the effects simulated by conventional shaders. Anti-aliasing is included as an integral part of the visibility calculations. Surfaces displayed include curved as well as polygonal surfaces.SIGGRAPH Coursescomputer_graphics/2017-09-11T23:06:22.6666889652017-09-11T23:06:22.666688965<EFBFBD>1<00>#<02>1GGGigaVoxels: ray-guided streaming for efficient and detailed voxel rendering<07>We propose a new approach to efficiently render large volumetric data sets. The system achieves interactive to real-time rendering performance for several billion voxels.
 Our solution is based on an adaptive data representation depending on the current view and occlusion information, coupled to an efficient ray-casting rendering algorithm. One key element of our method is to guide data production and streaming directly based on information extracted during rendering.
 Our data structure exploits the fact that in CG scenes, details are often concentrated on the interface between free space and clusters of density and shows that volumetric models might become a valuable alternative as a rendering primitive for real-time applications. In this spirit, we allow a quality/performance trade-off and exploit temporal coherence. We also introduce a mipmapping-like process that allows for an increased display rate and better quality through high quality filtering. To further enrich the data set, we create additional details through a variety of procedural methods.
 We demonstrate our approach in several scenarios, like the exploration of a 3D scan (8192<sup>3</sup> resolution), of hypertextured meshes (16384<sup>3</sup> virtual resolution), or of a fractal (theoretically infinite resolution). All examples are rendered on current generation hardware at 20--90 fps and respect the limited GPU memory budget.SI3Dcomputer_graphics/2017-09-11T23:06:22.5203469242017-09-11T23:06:22.520346924
<00>yT<00><00>5%/<02>+<2B>1GGDeep Colorization<07>This paper investigates into the colorization problem which converts a grayscale image to a colorful version. This is a very difficult problem and normally requires manual adjustment to achieve artifact-free quality. For instance, it normally requires human-labelled color scribbles on the grayscale target image or a careful selection of colorful reference images (e.g., capturing the same scene in the grayscale target image). Unlike the previous methods, this paper aims at a high-quality fully-automatic colorization method. With the assumption of a perfect patch matching technique, the use of an extremely large-scale reference database (that contains sufficient color images) is the most reliable solution to the colorization problem. However, patch matching noise will increase with respect to the size of the reference database in practice. Inspired by the recent success in deep learning techniques which provide amazing modeling of large-scale data, this paper re-formulates the colorization problem so that deep learning techniques can be directly employed. To ensure artifact-free quality, a joint bilateral filtering based post-processing step is proposed. Numerous experiments demonstrate that our method outperforms the state-of-art algorithms both in terms of quality and speed.2015 IEEE International Conference on Computer Vision (ICCV)computer_graphics/2017-09-11T23:06:24.3129270022017-09-11T23:06:24.312927002<EFBFBD>"$
}<02>/1GG3-Sweep: extracting editable objects from a single photo<07>We introduce an interactive technique for manipulating simple 3D shapes based on extracting them from a single photograph. Such extraction requires understanding of the components of the shape, their projections, and relations. These simple cognitive tasks for humans are particularly difficult for automatic algorithms. Thus, our approach combines the cognitive abilities of humans with the computational accuracy of the machine to solve this problem. Our technique provides the user the means to quickly create editable 3D parts---human assistance implicitly segments a complex object into its components, and positions them in space. In our interface, three strokes are used to generate a 3D component that snaps to the shape's outline in the photograph, where each stroke defines one dimension of the component. The computer reshapes the component to fit the image of the object in the photograph as well as to satisfy various inferred geometric constraints imposed by its global 3D structure. We show that with this intelligent interactive modeling tool, the daunting task of object extraction is made simple. Once the 3D object has been extracted, it can be quickly edited and placed back into photos or 3D scenes, permitting object-driven photo editing tasks which are impossible to perform in image-space. We show several examples and present a user study illustrating the usefulness of our technique.ACM Trans. Graph.computer_graphics/2017-09-11T23:06:24.1674741212017-09-11T23:06:24.167474121<EFBFBD>#
I<02>iM1GGPoisson surface reconstruction<07>We show that surface reconstruction from oriented points can be cast as a spatial Poisson problem. This Poisson formulation considers all the points at once, without resorting to heuristic spatial partitioning or blending, and is therefore highly resilient to data noise. Unlike radial basis function schemes, our Poisson approach allows a hierarchy of locally supported basis functions, and therefore the solution reduces to a well conditioned sparse linear system. We describe a spatially adaptive multiscale algorithm whose time and space complexities are proportional to the size of the reconstructed model. Experimenting with publicly available scan data, we demonstrate reconstruction of surfaces with greater detail than previously achievable.Symposium on Geometry Processingcomputer_graphics/2017-09-11T23:06:23.9461679692017-09-11T23:06:23.946167969
W<0B><08>}W<00>#)
/<02>a-1GGBlue native PAGE.<07>Blue native PAGE (BN-PAGE) can be used for one-step isolation of protein complexes from biological membranes and total cell and tissue homogenates. It can also be used to determine native protein masses and oligomeric states and to identify physiological protein-protein interactions. Native complexes are recovered from gels by electroelution or diffusion and are used for 2D crystallization and electron microscopy or analyzed by in-gel activity assays or by native electroblotting and immunodetection. In this protocol, we describe methodology to perform BN-PAGE followed by (i) native extraction or native electroblotting of separated proteins, or (ii) a second dimension of tricine-SDS-PAGE or modified BN-PAGE, or (iii) a second dimension of isoelectric focusing (IEF) followed by a third dimension of tricine-SDS-PAGE for the separation of subunits of complexes. These protocols for 2D and 3D PAGE can be completed in 2 and 3 days.Nature protocolscomputer_graphics/2017-09-11T23:06:24.5827900392017-09-11T23:06:24.582790039<EFBFBD>?(
9<02>1GGThe rendering equation<07>We present an integral equation which generalizes a variety of known rendering algorithms. In the course of discussing a monte carlo solution we also present a new form of variance reduction, called Hierarchical sampling and give a number of elaborations shows that it may be an efficient new technique for a wide variety of monte carlo procedures. The resulting rendering algorithm extends the range of optical phenomena which can be effectively simulated.SIGGRAPHcomputer_graphics/2017-09-11T23:06:24.5243210452017-09-11T23:06:24.524321045<EFBFBD>'
m<02>/1GGWeb page classification: Features and algorithms<07>Classification of Web page content is essential to many tasks in Web information retrieval such as maintaining Web directories and focused crawling. The uncontrolled nature of Web content presents additional challenges to Web page classification as compared to traditional text classification, but the interconnected nature of hypertext also provides features that can assist the process.
 As we review work in Web page classification, we note the importance of these Web-specific features and algorithms, describe state-of-the-art practices, and track the underlying assumptions behind the use of information from neighboring pages.ACM Comput. Surv.computer_graphics/2017-09-11T23:06:24.4608410642017-09-11T23:06:24.460841064<EFBFBD>)&<00>7<02>{1GGKinectFusion: real-time 3D reconstruction and interaction using a moving depth camera<07>KinectFusion enables a user holding and moving a standard Kinect camera to rapidly create detailed 3D reconstructions of an indoor scene. Only the depth data from Kinect is used to track the 3D pose of the sensor and reconstruct, geometrically precise, 3D models of the physical scene in real-time. The capabilities of KinectFusion, as well as the novel GPU-based pipeline are described in full. Uses of the core system for low-cost handheld scanning, and geometry-aware augmented reality and physics-based interactions are shown. Novel extensions to the core GPU pipeline demonstrate object segmentation and user interaction directly in front of the sensor, without degrading camera tracking or reconstruction. These extensions are used to enable real-time multi-touch interactions anywhere, allowing any planar or non-planar reconstructed physical surface to be appropriated for touch.UISTcomputer_graphics/2017-09-11T23:06:24.3660039062017-09-11T23:06:24.366003906
p<00><0F><0F><0F>tW0<0E><0E><0E>{`D
<0A>
<0A>
<0A>
o
R
-
<0C><0C><0C>qX0<0B><0B><0B>b-
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
e
7
	<09>	<09>	<09>	<09>	_	>	<08><08><08><08>n@)<07><07><07><07>W0<06><06><06><06>{X5<05><05><05><05>jD)<04><04><04>sT7<03><03><03><03>uR+<02><02><02>vQ2
<01>
<01>
<01>
<01>
e
L
+
<00>!p)
Otmar HilligesOtmarHilligeso
David KimDavidKimn'
Shahram IzadiShahramIzadim
Bin ShengBinSheng!l)
Qingxiong YangQingxiongYangk%
Zezhou ChengZezhouCheng#j+
Daniel Cohen-OrDanielCohen-Ori!
Shi-Min HuShi-MinHuh%
Ariel ShamirArielShamirg
Zhe ZhuZheZhuf
Tao ChenTaoChene%
Hugues HoppeHuguesHoppe#d+
Matthew BolithoMatthewBolitho(c1Michael M. KazhdanMichaelM.Kazhdan"b+Bui Tuong PhongBuiTuongPhonga'
Henri GouraudHenriGouraud!`)
Turner WhittedTurnerWhitted!_)
Elmar EisemannElmarEisemann%^-
Sylvain LefebvreSylvainLefebvre!])
Fabrice NeyretFabriceNeyret\'
Cyril CrassinCyrilCrassin[#
Salim VirjiSalimVirjiZ!
Marc LevoyMarcLevoyY%
Jongmin BaekJongminBaekX%
David JacobsDavidJacobs)W1
Alexandre KarpenkoAlexandreKarpenkoV#
Bruce GoochBruceGoochU%
Elaine CohenElaineCohenT%
Mark HartnerMarkHartner!S)
Ashley HartnerAshleyHartnerR'
Mike SharplesMikeSharples0Q9Rafael Pérez Y PérezRafaelPérez YPérezP'
Adam ChlipalaAdamChlipalaO!
Ziv ScullyZivScully$N-Andrei Z. BroderAndreiZ.BroderM'
Dennis ShashaDennisShasha%L-
Theodore JohnsonTheodoreJohnsonK'
Karin StraussKarinStraussJ%
Georg SeeligGeorgSeeligI
Luis CezeLuisCeze(H1Douglas M. CarmeanDouglasM.Carmean!G)
Randolph LopezRandolphLopez!F)
James BornholtJamesBornholtE!
Gong ZhangGongZhangD
Runhui LiRunhuiLiC%
Zhi-Li ZhangZhi-LiZhang%B-
Arvind NarayananArvindNarayananA%
Eman RamadanEmanRamadan@#L M AdlemanLMAdleman%?-
Brianna SatinoffBriannaSatinoff.>7#Jordan L. Boyd-GraberJordanL.Boyd-Graber=!
Yuening HuYueningHu(<1%V. S. SubrahmanianV.S.Subrahmanian);1
Francesca SpezzanoFrancescaSpezzano:%
Srijan KumarSrijanKumar9
Min WuMinWu8
Sen WangSenWang,75#Marta Z. KwiatkowskaMartaZ.Kwiatkowska6'
Xiaowei HuangXiaoweiHuang!5)
Chris JermaineChrisJermaine*43Luis Leopoldo PerezLuisLeopoldoPerez3#
Shangyu LuoShangyuLuo2%Zekai J. GaoZekaiJ.Gao#1+
Suvrat BhooshanSuvratBhooshan0'
Raunaq RewariRaunaqRewari%/-
Prasad KawthekarPrasadKawthekar.%
Thomas VermaThomasVerma!-)
Demis HassabisDemisHassabis,'
Thore GraepelThoreGraepel'+/
#Koray KavukcuogluKorayKavukcuoglu#*+
Madeleine LeachMadeleineLeach,)5Timothy P. LillicrapTimothyP.Lillicrap!()
Ilya SutskeverIlyaSutskever%'-
%Nal KalchbrennerNalKalchbrenner&
John NhamJohnNham%'
Dominik GreweDominikGrewe#$+
Sander DielemanSanderDieleman#%
Marc LanctotMarcLanctot3";
)Vedavyas PanneershelvamVedavyasPanneershelvam)!1
!Ioannis AntonoglouIoannisAntonoglou- 5
'Julian SchrittwieserJulianSchrittwieser4=George Van Den DriesscheGeorgeVan DenDriessche'
Laurent SifreLaurentSifre#
Arthur GuezArthurGuez&/Chris J. MaddisonChrisJ.Maddison
Aja HuangAjaHuang%
David SilverDavidSilver(1David S. RosenblumDavidS.Rosenblum*3Roy Thomas FieldingRoyThomasFielding#+
Klara NahrstedtKlaraNahrstedt )Carl A. GunterCarlA.Gunter#+
Muhammad NaveedMuhammadNaveed#
Dongjing HeDongjingHe%A. M. TuringA.M.Turing"+David A. WagnerDavidA.Wagner!)
Kate GreenwoodKateGreenwood,5Adrienne Porter FeltAdriennePorterFelt!
Erika ChinErikaChin%-
Rusmin SoetjiptoRusminSoetjipto
#Rose F. LiuRoseF.Liu!
Somesh JhaSomeshJha%-
Patrick McdanielPatrickMcdaniel*
3Patrick D. McdanielPatrickD.Mcdaniel	'
Damien OcteauDamienOcteau'Yves Le TraonYvesLeTraon'
Jacques KleinJacquesKlein%-
Alexandre BartelAlexandreBartel#
Eric BoddenEricBodden#+
Christian FritzChristianFritz+3
Siegfried RasthoferSiegfriedRasthofer#
Steven ArztStevenArzt
#
Judea PearlJudeaPearl
j<00><0F><0F><0F>kL)
<0E><0E><0E>jM&
<0A>
<0A>
<0A>
<0A>
l
E
'
	<0C><0C><0C><0C>a2
<0B><0B><0B>{\<
<EFBFBD>
<EFBFBD>
<EFBFBD>
~
Y
=
	<09>	<09>	<09>	<09>	_	;	<08><08><08>lN,<07><07><07>vX><06><06><06><06>gK"<05><05><05><05>mO+<04><04><04>oU3<03><03><03>q5<02><02><02>|^@

<01>
<01>
<01>
<01>
O
1

<00><17>Z
Cory HillCoryHill!<21>Y)!
Sabyasachi RoySabyasachiRoy<1B>X#
Wyatt LloydWyattLloyd1<64>W9!
#Muralidhar SubramanianMuralidharSubramanian#<23>V+
Per-Åke LarsonPer-ÅkeLarson<1F>U'
Moran TzafrirMoranTzafrir<19>T!
Nir ShavitNirShavit#<23>S+
Maurice HerlihyMauriceHerlihy0<79>R9Flemming Friche RodlerFlemmingFricheRodler<1B>Q#
Rasmus PaghRasmusPagh<1B>P#
Tiark RompfTiarkRompf<1D>O%
Phil BagwellPhilBagwell<1B>N#
Pat HellandPatHelland#<23>M+
Matti PitkänenMattiPitkänen4<6E>L=!Christine Van VredendaalChristineVanVredendaal<1B>K#
Tanja LangeTanjaLange9<65>JA!
+Chitchanok ChuengsatiansupChitchanokChuengsatiansup*<2A>I3Daniel J. BernsteinDanielJ.Bernstein&<26>H/Martin E. HellmanMartinE.Hellman%<25>G-
Whitfield DiffieWhitfieldDiffie#<23>F+
Phillip RogawayPhillipRogaway<1B>E#
Eran TromerEranTromer<1F>D'
Daniel GenkinDanielGenkin<17>C
Erik TewsErikTews$<24>B-Michael L. ScottMichaelL.Scott$<24>A-Maged M. MichaelMagedM.Michael(<28>@1Leonard M. AdlemanLeonardM.Adleman<19>?!
Adi ShamirAdiShamir$<24>>-Ronald L. RivestRonaldL.Rivest!<21>=)
Leslie LamportLeslieLamport<1B><#
Armando FoxArmandoFox<1F>;'
Greg FriedmanGregFriedman<1F>:'
Yuichi FujikiYuichiFujiki'<27>9/
Shinichi KawamotoShinichiKawamoto<1F>8'
George CandeaGeorgeCandea"<22>7+David D. RedellDavidD.Redell&<26>6/Butler W. LampsonButlerW.Lampson<19>5!
Rob ArthanRobArthan<1D>4%
Konrad SlindKonradSlind<1F>3'
John HarrisonJohnHarrison%<25>2-
Richard CarlssonRichardCarlsson<1D>1%
Jade AlglaveJadeAlglave$<24>0-Magnus O. MyreenMagnusO.Myreen#<23>/+
Thomas BraibantThomasBraibant<17>.
Tom RidgeTomRidge<1B>-#
Scott OwensScottOwens4<73>,=Francesco Zappa NardelliFrancescoZappaNardelli<1D>+%
Peter SewellPeterSewell<1F>*'
Susmit SarkarSusmitSarkar<1C>)%Ulf T. WigerUlfT.Wiger<1B>(#
Thomas ArtsThomasArts<1F>''
Hans SvenssonHansSvensson<1B>&#
John HughesJohnHughes)<29>%1
Nicholas SmallboneNicholasSmallbone"<22>$+Michal H. PalkaMichalH.Palka<1F>#'
Koen ClaessenKoenClaessen)<29>"1
#Jesper WilhelmssonJesperWilhelmsson-<2D>!5%
Konstantinos SagonasKonstantinosSagonas!<21> )
Erik JohanssonErikJohansson-<2D>5
!Vasileios TrigonakisVasileiosTrigonakis%<25>-
Rachid GuerraouiRachidGuerraoui<1B>#
Tudor DavidTudorDavid%<25>-
Valerio PascucciValerioPascucci<1F>'
Julien TiernyJulienTierny<1B>#
Brian SummaBrianSumma<19>!
Bob SumnerBobSumner"<22>+Markus H. GrossMarkusH.Gross$<24>-Robert W. SumnerRobertW.Sumner#<23>+
Steve MarschnerSteveMarschner&<26>/Paul A. BeardsleyPaulA.Beardsley%<25>-!
Gioacchino NorisGioacchinoNoris<1D>%
Bernd BickelBerndBickel<1D>%
Thabo BeelerThaboBeeler<1C>%Luc Van GoolLucVanGool<1F>'
Andreas UlmerAndreasUlmer<1F>'
Simon HaeglerSimonHaegler(<28>1Leith Casey LeedomLeithCaseyLeedom<1D>
%
Brian CabralBrianCabral%<25>-
William RibarskyWilliamRibarsky,<2C>5François X. SillionFrançoisX.Sillion!<21>
)
Michael WimmerMichaelWimmer<19>	!
James GipsJamesGips<1D>%
George StinyGeorgeStiny!<21>)
Sanni SiltanenSanniSiltanen!<21>)
Pascal MüllerPascalMüller<1B>#
Peter WonkaPeterWonka<1B>#
Markus LippMarkusLipp$<24>-Michael F. CohenMichaelF.Cohen*<2A>3!Peter-Pike J. SloanPeter-PikeJ.Sloan#<23>
+
Anton KaplanyanAntonKaplanyan<1B>#
Helmut SiesHelmutSies'Dean P. JonesDeanP.Jones'~/
Hermann SchäggerHermannSchägger%}-!
Hans-Peter BraunHans-PeterBraun|#
Ilka WittigIlkaWittig"{+James T. KajiyaJamesT.Kajiya$z-Brian D. DavisonBrianD.Davisony%
Xiaoguang QiXiaoguangQi,x5!Andrew W. FitzgibbonAndrewW.Fitzgibbon&w/Andrew J. DavisonAndrewJ.Davison!v)
Dustin FreemanDustinFreemanu%
Steve HodgesSteveHodgest'
Jamie ShottonJamieShotton!s)
Pushmeet KohliPushmeetKohli*r3Richard A. NewcombeRichardA.Newcombe#q+
David MolyneauxDavidMolyneaux
\
)	<09>g\<00>-
!<02>7/1GGPushPull++<07>PushPull tools are implemented in most commercial 3D modeling suites. Their purpose is to intuitively transform a face, edge, or vertex, and then to adapt the polygonal mesh locally. However, previous approaches have limitations: Some allow adjustments only when adjacent faces are orthogonal; others support slanted surfaces but never create new details. Moreover, self-intersections and edge-collapses during editing are either ignored or work only partially for solid geometry. To overcome these limitations, we introduce the PushPull++ tool for rapid polygonal modeling. In our solution, we contribute novel methods for adaptive face insertion, adjacent face updates, edge collapse handling, and an intuitive user interface that automatically proposes useful drag directions. We show that PushPull++ reduces the complexity of common modeling tasks by up to an order of magnitude when compared with existing tools.ACM Trans. Graph.computer_graphics/2017-09-11T23:06:25.0919938962017-09-11T23:06:25.091993896<EFBFBD>>,
C<02>#
1GGInteractive Horizon Mapping<07>Shadows play an important role in perceiving the shape and texture of an object. While some previous interactive shadowing methods are appropriate for casting shadows on other geometry they can not be applied to bump maps (which contain no explicit geometry.) Horizon Mapping is a technique used to compute shadows for bump-mapped surfaces. We map the technique into modern graphics API's and extend it to account more accurately for the geometry of the underlying surface. We also use it to represent limited self-shadowing for pure geometry. In mapping the algorithm to hardware, we use a novel method to interpolate orientation in tangent space over the surface. We show results of self-shadowing at frame rates.computer_graphics/2017-09-11T23:06:24.7205668952017-09-11T23:06:24.720566895+	]

1GGLight Propagation Volumes in Cryengine 3<07>computer_graphics/2017-09-11T23:06:24.6665859382017-09-11T23:06:24.666585938<EFBFBD>T*
)<02>-I1GGThe Redox Code<07>SIGNIFICANCE
The redox code is a set of principles that defines the positioning of the nicotinamide adenine dinucleotide (NAD, NADP) and thiol/disulfide and other redox systems as well as the thiol redox proteome in space and time in biological systems. The code is richly elaborated in an oxygen-dependent life, where activation/deactivation cycles involving O₂ and H₂O₂ contribute to spatiotemporal organization for differentiation, development, and adaptation to the environment. Disruption of this organizational structure during oxidative stress represents a fundamental mechanism in system failure and disease.


RECENT ADVANCES
Methodology in assessing components of the redox code under physiological conditions has progressed, permitting insight into spatiotemporal organization and allowing for identification of redox partners in redox proteomics and redox metabolomics.


CRITICAL ISSUES
Complexity of redox networks and redox regulation is being revealed step by step, yet much still needs to be learned.


FUTURE DIRECTIONS
Detailed knowledge of the molecular patterns generated from the principles of the redox code under defined physiological or pathological conditions in cells and organs will contribute to understanding the redox component in health and disease. Ultimately, there will be a scientific basis to a modern redox medicine.Antioxidants & redox signalingcomputer_graphics/2017-09-11T23:06:24.6271999512017-09-11T23:06:24.627199951

M<0C><0B>	&
M<00>V1
w<02>1GGImaging vector fields using line integral convolution<07>Imaging vector fields has applications in science, art, image processing and special effects. An effective new approach is to use linear and curvilinear filtering techniques to locally blur textures along a vector field. This approach builds on several previous tex-It is, however, unique because it is local, one-dimensional and independent of any predefined geometry or texture. The technique is general and capable of imaging arbitrary two-and three-dimensional vector fields. The local one-dimensional nature of the algorithm lends itself to highly parallel and efficient implementations. Furthermore, the curvilinear filter is capable of rendering detail on very intricate vector fields. Combining this technique with other rendering and image processing techniques — like periodic motion filtering — results in richly informative and striking images. The technique can also produce novel special effects. 1. INTRODUCTION Upon first inspection, imaging vector fields appears to have limited application — confined primarily to scientific visualization. However, much of the form and shape in our environment is a function of not only image intensity and color, but also of directional information such as edges. Painters, sculptors, photographers , image processors[16] and computer graphics researchers[9] have recognized the importance of direction in the process of image creation and form. Hence, algorithms that can image such directional information have wide application across both scientific and artistic domains. Such algorithms should possess a number of desirable and sometimes conflicting properties including: accuracy, locality of calculation, simplicity, controllability and generality. Line Integral Convolution (LIC) is a new technique that possesses many of these properties. Its generality allows for the introduction of a comSIGGRAPHcomputer_graphics/2017-09-11T23:06:25.4613239752017-09-11T23:06:25.461323975<EFBFBD>H0
5<02>#/1GGInstant architecture<07>This paper presents a new method for the automatic modeling of architecture. Building designs are derived using split grammars, a new type of parametric set grammar based on the concept of shape. The paper also introduces an attribute matching system and a separate control grammar, which offer the flexibility required to model buildings using a large variety of different styles and design ideas. Through the adaptive nature of the design grammar used, the created building designs can either be generic or adhere closely to a specified goal, depending on the amount of data available.ACM Trans. Graph.computer_graphics/2017-09-11T23:06:25.3904060062017-09-11T23:06:25.390406006<EFBFBD>./
<00>
'1GGShape Grammars and the Generative Specification of Painting and Sculpture<07>IFIP Congresscomputer_graphics/2017-09-11T23:06:25.2005490722017-09-11T23:06:25.200549072<EFBFBD>[.
}<02>31CCDiminished reality for augmented reality interior design<07>A modular real-time diminished reality pipeline for indoor applications is presented. The pipeline includes a novel inpainting method which requires no prior information of the textures behind the object to be diminished. The inpainting method operates on rectified images and adapts to scene illumination. In typically challenging illumination situations, the method produces more realistic results in indoor scenes than previous approaches. Modularity enables using alternative implementations in different stages and adapting the pipeline for different applications. Finally, practical solutions to problems occurring in diminished reality applications, for example interior design, are discussed.The Visual Computercomputer_graphics/2017-09-11T23:06:25.16040212017-09-11T23:06:25.1604021

k<0C>f
k<00>x4
s<02>I/-GGHigh-quality single-shot capture of facial geometry<07>This paper describes a passive stereo system for capturing the 3D geometry of a face in a single-shot under standard light sources. The system is low-cost and easy to deploy. Results are submillimeter accurate and commensurate with those from state-of-the-art systems based on active lighting, and the models meet the quality requirements of a demanding domain like the movie industry. Recovered models are shown for captures from both high-end cameras in a studio setting and from a consumer binocular-stereo camera, demonstrating scalability across a spectrum of camera deployments, and showing the potential for 3D face modeling to move beyond the professional arena and into the emerging consumer market in stereoscopic photography.
 Our primary technical contribution is a modification of standard stereo refinement methods to capture pore-scale geometry, using a qualitative approach that produces visually realistic results. The second technical contribution is a calibration method suited to face capture systems. The systemic contribution includes multiple demonstrations of system robustness and quality. These include capture in a studio setup, capture off a consumer binocular-stereo camera, scanning of faces of varying gender and ethnicity and age, capture of highly-transient facial expression, and scanning a physical mask to provide ground-truth validation.ACM Trans. Graph.computer_vision/2017-09-11T23:06:25.7520791022017-09-11T23:06:25.752079102<EFBFBD>(3
}<02>/-GGCoupled 3D reconstruction of sparse facial hair and skin<07>Although facial hair plays an important role in individual expression, facial-hair reconstruction is not addressed by current face-capture systems. Our research addresses this limitation with an algorithm that treats hair and skin surface capture together in a coupled fashion so that a high-quality representation of hair fibers as well as the underlying skin surface can be reconstructed. We propose a passive, camera-based system that is robust against arbitrary motion since all data is acquired within the time period of a single exposure. Our reconstruction algorithm detects and traces hairs in the captured images and reconstructs them in 3D using a multiview stereo approach. Our coupled skin-reconstruction algorithm uses information about the detected hairs to deliver a skin surface that lies underneath all hairs irrespective of occlusions. In dense regions like eyebrows, we employ a hair-synthesis method to create hair fibers that plausibly match the image data. We demonstrate our scanning system on a number of individuals and show that it can successfully reconstruct a variety of facial-hair styles together with the underlying skin surface.ACM Trans. Graph.computer_vision/2017-09-11T23:06:25.6421398932017-09-11T23:06:25.642139893<EFBFBD>l2
M<02>S/1GGProcedural modeling of buildings<07><i>CGA shape</i>, a novel shape grammar for the procedural modeling of CG architecture, produces building shells with high visual quality and geometric detail. It produces extensive architectural models for computer games and movies, at low cost. Context sensitive shape rules allow the user to specify interactions between the entities of the hierarchical shape descriptions. Selected examples demonstrate solutions to previously unsolved modeling problems, especially to consistent mass modeling with volumetric shapes of arbitrary orientation. <i>CGA shape</i> is shown to efficiently generate massive urban models with unprecedented level of detail, with the virtual rebuilding of the archaeological site of Pompeii as a case in point.ACM Trans. Graph.computer_graphics/2017-09-11T23:06:25.5835639652017-09-11T23:06:25.583563965
<00>
<07><04><00><00>a8<00><02>+%GGFinding race conditions in Erlang with QuickCheck and PULSE<07>We address the problem of testing and debugging concurrent, distributed Erlang applications. In concurrent programs, race conditions are a common class of bugs and are very hard to find in practice. Traditional unit testing is normally unable to help finding all race conditions, because their occurrence depends so much on timing. Therefore, race conditions are often found during system testing, where due to the vast amount of code under test, it is often hard to diagnose the error resulting from race conditions. We present three tools (QuickCheck, PULSE, and a visualizer) that in combination can be used to test and debug concurrent programs in unit testing with a much better possibility of detecting race conditions. We evaluate our method on an industrial concurrent case study and illustrate how we find and analyze the race conditions.ICFPconcurrency/2017-09-11T23:06:26.3465319822017-09-11T23:06:26.346531982<EFBFBD>R7<00><02>y%GGHeap architectures for concurrent languages using message passing<07>We discuss alternative heap architectures for languages that rely on automatic memory management and implement concurrency through asynchronous message passing. We describe how interprocess communication and garbage collection happens in each architecture, and extensively discuss the tradeoffs that are involved. In an implementation setting (the Erlang/OTP system) where the rest of the runtime system is unchanged, we present a detailed experimental comparison between these architectures using both synthetic programs and large commercial products as benchmarks.MSP/ISMMconcurrency/2017-09-11T23:06:26.1239641112017-09-11T23:06:26.123964111<EFBFBD>}6<00>/<02>7%GGEverything you always wanted to know about synchronization but were afraid to ask<07>This paper presents the most exhaustive study of synchronization to date. We span multiple layers, from hardware cache-coherence protocols up to high-level concurrent software. We do so on different types of architectures, from single-socket -- uniform and non-uniform -- to multi-socket -- directory and broadcast-based -- many-cores. We draw a set of observations that, roughly speaking, imply that scalability of synchronization is mainly a property of the hardware.SOSPconcurrency/2017-09-11T23:06:25.9857990722017-09-11T23:06:25.985799072<EFBFBD>g5
s<02>'/-GGPanorama weaving: fast and flexible seam processing<07>A fundamental step in stitching several pictures to form a larger mosaic is the computation of boundary seams that minimize the visual artifacts in the transition between images. Current seam computation algorithms use optimization methods that may be slow, sequential, memory intensive, and prone to finding suboptimal solutions related to local minima of the chosen energy function. Moreover, even when these techniques perform well, their solution may not be perceptually ideal (or even good). Such an inflexible approach does not allow the possibility of user-based improvement. This paper introduces the <i>Panorama Weaving</i> technique for seam creation and editing in an image mosaic. First, <i>Panorama Weaving</i> provides a procedure to create boundaries for panoramas that is fast, has low memory requirements and is easy to parallelize. This technique often produces seams with lower energy than the competing global technique. Second, it provides the first interactive technique for the exploration of the seam solution space. This powerful editing capability allows the user to automatically extract energy minimizing seams given a sparse set of constraints. With a variety of empirical results, we show how <i>Panorama Weaving</i> allows the computation and editing of a wide range of digital panoramas including unstructured configurations.ACM Trans. Graph.computer_vision/2017-09-11T23:06:25.8137419432017-09-11T23:06:25.813741943
<02><0B><06><<02><00>A<
i<02>y#%GGExperience with Processes and Monitors in Mesa<07>The use of monitors for describing concurrency has been much discussed in the literature. When monitors are used in real systems of any size, however, a number of problems arise which have not been adequately dealt with: the semantics of nested monitor calls; the various ways of defining the meaning of WAIT; priority scheduling; handling of timeouts, aborts and other exceptional conditions; interactions with process creation and destruction; monitoring large numbers of small objects. These problems are addressed by the facilities described here for concurrent programming in Mesa. Experience with several substantial applications gives us some confidence in the validity of our solutions.Commun. ACMconcurrency/2017-09-11T23:06:26.8242260742017-09-11T23:06:26.824226074v;	
Q%GGHol<07>The Seventeen Provers of the Worldconcurrency/2017-09-11T23:06:26.6592819822017-09-11T23:06:26.659281982<EFBFBD>M:
_<02>+%GGMessage Analysis for Concurrent Languages<07>We describe an analysis-driven storage allocation scheme for concurrent languages that use message passing with copying semantics. The basic principle is that in such a language, data which is not part of any message does not need to be allocated in a shared data area. This allows for deallocation of thread-specific data without requiring global synchronization and often without even triggering garbage collection. On the other hand, data that is part of a message should preferably be allocated on a shared area, which allows for fast (O(1)) interprocess communication that does not require actual copying. In the context of a dynamically typed, higher-order, concurrent functional language, we present a static message analysis which guides the allocation. As shown by our performance evaluation, conducted using an industrial-strength language implementation , the analysis is effective enough to discover most data which is to be used as a message, and to allow the allocation scheme to combine the best performance characteristics of both a process-centric and a shared-heap memory architecture.SASconcurrency/2017-09-11T23:06:26.5853669432017-09-11T23:06:26.585366943<EFBFBD>y9
s<02>m%GGThe semantics of x86-CC multiprocessor machine code<07>Multiprocessors are now dominant, but real multiprocessors do not provide the sequentially consistent memory that is assumed by most work on semantics and verification. Instead, they have subtle relaxed (or weak) memory models, usually described only in ambiguous prose, leading to widespread confusion.
 We develop a rigorous and accurate semantics for x86 multiprocessor programs, from instruction decoding to relaxed memory model, mechanised in HOL. We test the semantics against actual processors and the vendor litmus-test examples, and give an equivalent abstract-machine characterisation of our axiomatic memory model. For programs that are (in some precise sense) data-race free, we prove in HOL that their behaviour is sequentially consistent. We also contrast the x86 model with some aspects of Power and ARM behaviour.
 This provides a solid intuition for low-level programming, and a sound foundation for future work on verification, static analysis, and compilation of low-level concurrent code.POPLconcurrency/2017-09-11T23:06:26.4369990232017-09-11T23:06:26.436999023
<02>
<EFBFBD>b<02><00>F?<00><02>S#'EEA Method for Obtaining Digital Signatures and Public-Key Cryptosystems<07>An encryption method is presented with the novel property that publicly revealing an encryption key does not thereby reveal the corresponding decryption key. This has two important consequences: (1) Couriers or other secure means are not needed to transmit keys, since a message can be enciphered using an encryption key publicly revealed by the intented recipient. Only he can decipher the message, since only he knows the corresponding decryption key. (2) A message can be &#8220;signed&#8221; using a privately held decryption key. Anyone can verify this signature using the corresponding publicly revealed encryption key. Signatures cannot be forged, and a signer cannot later deny the validity of his signature. This has obvious applications in &#8220;electronic mail&#8221; and &#8220;electronic funds transfer&#8221; systems. A message is encrypted by representing it as a number M, raising M to a publicly specified power e, and then taking the remainder when the result is divided by the publicly specified product, <italic>n</italic>, of two large secret primer numbers p and q. Decryption is similar; only a different, secret, power d is used, where e * d &#8801; 1(mod (p - 1) * (q - 1)). The security of the system rests in part on the difficulty of factoring the published divisor, <italic>n</italic>.Commun. ACMcryptography/2017-09-11T23:06:27.178482912017-09-11T23:06:27.17848291<EFBFBD>><00>
<02>#%GGTime, Clocks, and the Ordering of Events in a Distributed System<07>The concept of one event happening before another in a distributed system is examined, and is shown to define a partial ordering of the events. A distributed algorithm is given for synchronizing a system of logical clocks which can be used to totally order the events. The use of the total ordering is illustrated with a method for solving synchronization problems. The algorithm is then specialized for synchronizing physical clocks, and a bound is derived on how far out of synchrony the clocks can become.Commun. ACMconcurrency/2017-09-11T23:06:27.1089179692017-09-11T23:06:27.108917969<EFBFBD>~=
e<02>#GGMicroreboot - A Technique for Cheap Recovery<07>A significant fraction of software failures in large-scale Internet systems are cured by rebooting, even when the exact failure causes are unknown. However, rebooting can be expensive, causing nontrivial service disruption or downtime even when clusters and failover are employed. In this work we separate process recovery from data recovery to enable microrebooting – a fine-grain technique for surgically recovering faulty application components, without disturbing the rest of the application. We evaluate microrebooting in an Internet auction system running on an application server. Microreboots recover most of the same failures as full reboots, but do so an order of magnitude faster and result in an order of magnitude savings in lost work. This cheap form of recovery engenders a new approach to high availability: microreboots can be employed at the slightest hint of failure, prior to node failover in multi-node clusters, even when mistakes in failure detection are likely; failure and recovery can be masked from end users through transparent call-level re-tries; and systems can be rejuvenated by parts, without ever being shut down.OSDIcrash_only/2017-09-11T23:06:26.9153740232017-09-11T23:06:26.915374023

<01><00>
<01><0F><0F><0F><0F><0F><0F>dR?+<0E><0E><0E><0E><0E><0E><0E>yl[H4$
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
k
\
P
=
.

<0C><0C><0C><0C><0C><0C>nqcRA-<0B>#<0B><0B><0B><0B><02><0B><0B>oXC,	
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>?
<EFBFBD><02>
<01>
yQ
f
O
<
)

	<09>	<09>	<09>	<09>	<09>	<09>	s	^	I	6	#	
<08><08><08><08><08><08>zfO:$<02><07><07>
<01><07><07><07><07>{iXE5"<06><06><06><06><06><06><02><06>p`P:(<05><05><05><05><05><05><05>|oaSE4"
<04><02><04><04><04><04><04><04>pZG/<03><03><03><03><03><02><03><03><03><02><02>{dL6"

<01>
<01>
<01>
<01>
<01>+Anthony Liguori<05>
<01>1Amit Rahul Baishya<05><00>C. Borradori-Tolsa
<01>
C. Bocca<03>%C. Agostinho})C. A. R. Hoare<02>+Béla Bollobás<02>)Byung-Gon Chun<02>-By C. E. Shannon1Butler W. Larnpson/Butler W. Lampson<00>+
Bui Tuong Phongb#Bryan Par'Barmak Modrek#Binbin Chen<05>5Amir Hossein Gandomi<05>%Asim Shankar<05>!Ankur Taly<05>%Alex Monràs<05>+Albert Einstein<05>9Alejandro A. Schäffer<05>%Amihood Amir<05>;Andoni Lombide Carreton<05>'Adriaan Moors<05>'Boon Thau Loo<03>!Bob Sumner<00>
Bing Liu"

Bin ShengmBill Howe
!Bernd Kolb<02>%Bernd Bickel<00>%Bernard Wong
+Bernard MetzlerL/Benoît Garbinato\1Benjamin Schneider<05>'Benjamin Reed
/-Benjamin Hindman<03>5Benjamin H. Sigelmany-Benjamin C. Reed<03>#Ben Moseley`Ben Handy<00>'Bay-Wei Changr+Baruch Awerbuch<03>#Bart Samwel<00>)Barbara Liskov
e+Bapi ChatterjeeT%Balraj Singh
<01>#B. Öztürk<03>
B. ZhongB
B. Weber<04>
B. Veldt4B. Song<05>B. Sonk-B. Mohar Vitezic<03>1B. M. Santos Peixe\
B. KainzA#B. HolzmannB. Hansen-#B. GrahovacB. Foglia<03>B. Dreher<04>+B. ArrizabalagaP%B. Angermayrf-Avinash Lakshman7!Avi Kivity<05>!Avery Wang<02>1Austin T. ClementsW/Austin I. Eliazar<02>)
Ashley HartnerS+Ashish Motivala
<01>!Asaf Cidons-
Arvind NarayananB#
Arthur Guez+Arnar Birgisson<03>#Armando Fox<00>'Arjun Narayan<03>!Arjun Guha2'Arif Merchant
r%
Ariel Shamirh%Ariel Rabkin
8%Anupam Gupta<02>+Antony Rowstron<03>+Antony Courtneyz+Anton Kaplanyan<00>+Antoine Bossard<02>/Anthony D. Joseph
35Anne-Marie Kermarrec
<01>%Ann Wollrath
h-Anirban Dasgupta<05>+Animesh TrivediJ/Anil Madhavapeddy
<01>)Angus F. M. Ng!%Angelo Prado<02>1Angela Demke BrownF)Andy Konwinski
<)Andrey KhorlinO)Andrey Gubarev<00>+Andrew Warfield`+Andrew W. LeungV5
Andrew W. Fitzgibbonx'Andrew Turpin<02>'Andrew Tuckerb+Andrew P. Black
,+Andrew Mccallum)1Andrew Lookingbill<02>-Andrew Konwinski
5)Andrew Kennedy<02>/
Andrew J. Davisonw#Andrew Hume<02>)Andrew Handoko<02>%Andrew Fikes1%Andrej Bauer<02>-
Andrei Z. BroderN'Andreas Wöß<02>'Andreas Ulmer<00>/Andreas Haeberlen<03>'Andrea Bittau
w;Ana Candida Cruz Natali<02>#Amin Vahdat<02>?Ambrose Bonnaire-Sergeant1Alistair C. Veitch
t7Ali José Mashtizadeh
v!Ali Ghodsi<03>!Ali Dasdan
'Alfred Tarski<03>1
Alexandre KarpenkoW-
Alexandre Bartel/Alexander Thomson<00>3Alexander ReinefeldX+Alexander LloydS%Alex Pilchin8Alex Ho]!Alex Gyorif%Alex De Jong<02>%Alex Balikov
M-Alberto Dainotti<02>3Albert G. Greenberg
"
Alan Kay)Alan J. Demers
<01>#Alan Geller
^#Alan C. Kay<05>

Aja Huang5
Adrienne Porter Felt!Adi Shamir<00>'
Adam ChlipalaP;Achilleas L. D. Buisman<03>/Abraham Bernstein<03>)Abhishek Verma
E)Abhinandan Das
<01>)Aart J. C. Bik
l%A. YamaguchiOA. Yamadas'A. WinstanleybA. VazXA. Titova!+A. T. Abdelmoez<04>%A. SydorchukA. SuzukiA. Stepan<03>
A. Silva<04>+A. Shafigullina"%A. S. Hanafy<04>#A. Rizvanov)
A. Prete
!A. Popescu<03>!A. Pession!A. Peixoto<04>)A. P. Oliveira]'A. P. Kiyasov*#A. Oliveira
A. Morid!A. Martins<04>!A. Mansour<04>%
A. M. Turing%A. L. Simão<03>#A. Kourikou<04>%A. Koukofiki<04>'A. Galyavieva<05>-A. G. G. AntunesV#A. Floreani&%A. Ferlitschh)A. Facciorusso<04>'A. Eshraghian+%A. Colecchia<04>7A. Castiella EguzkizaH)A. Castanheira<04>
A. Alves[)A. Albuquerque<04>
A. AktasE)A. Abou Rached<04>+A. Abdulkhakova<05>)A. A. Gumerova'

<01><00>
<01>S?-<04><04><04><04><04><04><04>t]E/<03><03><03><03><03>
<01>
<01><0F><0F><0F><0F><0F><0F>o_K<.!<0E><0E><0E><0E><0E><0E><0E><0E>kZ@+
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
u
U
E
/

<0C><0C><0C><0C><0C>n
<01><0C>nW<02>=#<0B><0B><0B><0B><0B><0B>q]G4"
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>

o
b
V
G
7
'

	<09>	<09>	<09>	<09>	<09>	<09>	<09>	t	`	J	7	!	<08><08><08><08><08><08>*y_P<$<03><07><07><07><07><07><07><07>sbT<,
<06><06><06><06><06><06>s]F0Z<05><02><05><05><05>@<05><05>x<03>f
<02><02><02><02><02><02><02>tcP?*
<01>
<01>
<01>/Christian Limpach<05>#C. ErdoğduC. Choi<05>
Eric A. Brewer<03>#Eran Tromer<00>5Emmanuel Dellandréa,Emma Fulu<03>+Emin Gün Sirer
	+Emery D. Berger
W%
Eman RamadanA)
Elmar Eisemann_%
Elaine CohenU#Edwin Brady<02>-Edward J. Rykiel1Edsger W. Dijkstra<03>7Edmund B. Nightingale<!E. Zehnter<04>1Christopher J. Lee1Dawn Xiaodong Song<05>7Christopher M. Dawson<05>-Daniel S. Marcus<05>5Denise E. M. Penrose<05>)David W. Corne<05>+Christian Jacob<05>)David B. Fogel<05>)Dennis Ritchie<05>C. Bowlus"1C. Borradori-Tolsa
<01>
C. Bocca<03>%C. Agostinho})C. A. R. Hoare<02>+Béla Bollobás<02>)Byung-Gon Chun<02>-By C. E. Shannon1Butler W. Larnpson/Butler W. Lampson<00>+
Bui Tuong Phongb#Bryan Parno
<01>#
Bruce GoochV-
Brianna Satinoff?!Brian Zill
<01>#Brian Summa<00>%Brian M. Oki
<01>%Brian Hempel
+Brian F. Cooper]-
Brian D. Davisonz%Brian Cabral<00>)Brannon Batson<03>'Brandon WileyC'
Dennis ShashaM)Deniz Hastorun41Deniz Altınbükenq/Deniz Altinbüken<03>)
Demis Hassabis-1Deborah A. Wallach/'
Dean P. Jones-David W. Shipman
#David Ungarq%
David Silver-David S. Wishart:1
David S. Rosenblum-David S. Johnson
<01>+David R. Millen
<01>+David R. Karger
B#David Peleg<03>+David Patterson
='David P. Reedk/David Oppenheimer
H+
David Molyneauxq-David Menestrina

+David Mazières
y!David Lieb<02>1David Klaftenegger

David Kimo%
David JacobsX)David J. Scott
<01>'David J. Hand&#David Gregg<05>/David G. Andersen<00>)David F. Bacon
<01>+David D. Redell<00>)David D. Clarkl#David Chaum
<01>+
David A. Wagner1David A. Patterson
7)David A. Maltz
$Danny Digh5Daniel Winograd-Cort~'Daniel Sunday<02>%Daniel Pricea#Daniel Peng<03>1Daniel P. W. Ellis<02>%Daniel Mills
S3Daniel J. Bernstein<00>+Daniel J. Abadi<00>5Daniel H. H. Ingalls<05>-Daniel H. Greene
<01>'Daniel Genkin<00>-Daniel G. Bobrow<02>+
Daniel Cohen-Orj3Daniel C. Swinehart
<01>'Dan Steinberg'#Dan Ingalls!Dan Geiger%Dan Dumitriu
<01>Dan Dixon
<01>'
Damien Octeau	D. Stimac<03>!D. Shapiro0)D. SchmalstiegB!D. Orlandi<04>!D. Martins<04>D. Kovač<03>D. KimmD. Kang<05>!D. K. JangZ#D. Hartmann!D. H. Sinn<04>D. H. KohM
D. Gomes{D. G. Kim<05>
D. Festi'D. Branquinho!D. Bonazza<03>!D. Akiyamav+Cédric Fournet
'
Cyril Crassin\'Cynthia Dwork-Cristian Martín<03>)Craig ChamberspCory Hill<00>)Corinna Cortes/'Conor Mcbride<02>'Conal Elliott/Claude E. Shannon<03>-Chung-Chieh Shan;Christos T. Karamanolis
u?Christos H. Papadimitriou'5Christopher Strachey<02>5Christopher L. Reeve
/Christopher Clark<05>=Christine Van Vredendaal<00>-Christian Wimmer<02>+Christian Humer<02>+
Christian Fritz-Christian Franck<03>%Chris Thomas
<01>'Chris Okasaki)
Chris Jermaine5/
Chris J. Maddison-Chris Hawblitzel
<01>!Chris BondLAChitchanok Chuengsatiansup<00>-Chien-Chin HuangEChi Hon1Charalampos Rotsos
<01>%Chaoran YangRChao Yang
<01>'Changhoon Kim
<01>AChandra Shekhar Chandrakar-Chandan Shanbhag<03>%Chad Whipkey<00>+Carlos Maltzahn<00>5Carlos Delgado Kloos<03>#Carl Hewittd)Carl H. Hauser
<01>)
Carl A. Gunter-C.m.p. Rodrigues<03>#C. Τsoulas<04>
C. Yu7
C. Yaghi<04>
C. Xu6!C. Vincent,#C. Triantos<04>%C. Tiribelli<03>#C. TeixeiraWC. Tang<05>
C. SofiaC. Pavlov<04>)C. MeyenbergerG!C. Messina<04>!C. MartinsYC. Madl5C. M. Chackelevicius<03>!C. Lériasy3C. Ivascu-Siegfried<04>#C. Illiasch
C. Iancu<04>%C. Gregório
y
<EFBFBD>O<07>y<00>iC
9<02>c7'GGAcoustic Cryptanalysis<07>Many computers emit a high-pitched noise during operation, due to vibration in some of their electronic components. These acoustic emanations are more than a nuisance: They can convey information about the software running on the computer and, in particular, leak sensitive information about security-related computations. In a preliminary presentation (Eurocrypt’04 rump session), we have shown that different RSA keys induce different sound patterns, but it was not clear how to extract individual key bits. The main problem was the very low bandwidth of the acoustic side channel (under 20  kHz using common microphones, and a few hundred kHz using ultrasound microphones), and several orders of magnitude below the GHz-scale clock rates of the attacked computers. In this paper, we describe a new acoustic cryptanalysis key extraction attack, applicable to GnuPG’s implementation of RSA. The attack can extract full 4096-bit RSA decryption keys from laptop computers (of various models), within an hour, using the sound generated by the computer during the decryption of some chosen ciphertexts. We experimentally demonstrate such attacks, using a plain mobile phone placed next to the computer, or a more sensitive microphone placed 10 meters away.Journal of Cryptologycryptography/2017-09-11T23:06:27.4722089842017-09-11T23:06:27.472208984hB	3
#GGCrash-Only Software<07>HotOScrash_only/2017-09-11T23:06:27.3641020512017-09-11T23:06:27.364102051<EFBFBD>A
C<02>-I'GGAttacks on the WEP protocol<07>WEP is a protocol for securing wireless networks. In the past years, many attacks on WEP have been published, totally breaking WEP's security. This thesis summarizes all major attacks on WEP. Additionally a new attack, the PTW attack, is introduced, which was partially developed by the author of this document. Some advanced versions of the PTW attack which are more suiteable in certain environments are described as well. Currently, the PTW attack is fastest publicly known key recovery attack against WEP protected networks.IACR Cryptology ePrint Archivecryptography/2017-09-11T23:06:27.3485729982017-09-11T23:06:27.348572998<EFBFBD>@<00>/<02>[%GGSimple, Fast, and Practical Non-Blocking and Blocking Concurrent Queue Algorithms<07>Drawing ideas from previous authors, we present a new non-blocking concurrent queue algorithm and a new two-lock queue algorithm in which one enqueue and one de-queue can proceed concurrently. Both algorithms are simple , fast, and practical; we were surprised not to find them in the literature. Experiments on a 12-node SGI Challenge multiprocessor indicate that the new non-blocking queue consistently outperforms the best known alternatives; it is the clear algorithm of choice for machines that provide a universal atomic primitive (e.g. compare and swap or load linked/store conditional). The two-lock concurrent queue outperforms a single lock when several processes are competing simultaneously for access; it appears to be the algorithm of choice for busy queues on machines with non-universal atomic primitives (e.g. test and set). Since much of the motivation for non-blocking algorithms is rooted in their immunity to large, unpredictable delays in process execution, we report experimental results both for systems with dedicated processors and for systems with several processes multiprogrammed on each processor.PODCconcurrency/2017-09-11T23:06:27.3051669922017-09-11T23:06:27.305166992
0c0<00>0E
I<02>OI'GGNew directions in cryptography<07>Two kinds of contemporary developments in cryp-communications over an insecure channel order to use cryptog-tography are examined. Widening applications of teleprocess-raphy to insure privacy, however, it currently necessary for the ing have given rise to a need for new types of cryptographic communicating parties to share a key which is known to no systems, which minimize the need for secure key distribution one else. This is done by sending the key in advance over some channels and supply the equivalent of a written signature. This secure channel such a private courier or registered mail. A paper suggests ways to solve these currently open problems. private conversation between two people with no prior acquain-It also discusses how the theories of communication and compu-tance is a common occurrence in business, however, and it is tation are beginning to provide the tools to solve cryptographic unrealistic to expect initial business contacts to be postponed problems of long standing. long enough for keys to be transmitted by some physical means. The cost and delay imposed by this key distribution problem is a major barrier to the transfer of business communicationsIEEE Trans. Information Theorycryptography/2017-09-11T23:06:27.5887280272017-09-11T23:06:27.588728027<EFBFBD>D
_<02>
I'GGThe Moral Character of Cryptographic Work<07>Cryptography rearranges power: it configures who can do what, from what. This makes cryptography an inherently political tool, and it confers on the field an intrinsically moral dimension. The Snowden revelations motivate a reassessment of the political and moral positioning of cryptography. They lead one to ask if our inability to effectively address mass surveillance constitutes a failure of our field. I believe that it does. I call for a community-wide effort to develop more effective means to resist mass surveillance. I plead for a reinvention of our disciplinary culture to attend not only to puzzles and math, but, also, to the societal implications of our work. Preamble. Most academic cryptographers seem to think that our field is a fun, deep, and politically neutral game—a set of puzzles involving communicating parties and notional adversaries. This vision of who we are animates a field whose work is intellectually impressive and rapidly produced, but also quite inbred and divorced from real-world concerns. Is this what cryptography should be like? Is it how we should expend the bulk of our intellectual capital? For me, these questions came to a head with the Snowden disclosures of 2013. If cryptography's most basic aim is to enable secure communications, how could it not be a colossal failure of our field when ordinary people lack even a modicum of communication privacy when interacting electronically? Yet I soon realized that most cryptographers didn't see it this way. Most seemed to feel that the disclosures didn't even implicate us cryptographers. I think that they do. So I want to talk about the moral obligations of cryptographers , and my community as a whole. This is not a topic cryptographers routinely discuss. In this post-Snowden era, I think it needs to be. The essay and talk are addressed to the cryptographic community—my community— and the words " we " and " our " should be so interpreted. I apologize in advance if I offend anyone with any of my comments; nothing of the sort is my intent.IACR Cryptology ePrint Archivecryptography/2017-09-11T23:06:27.5243620612017-09-11T23:06:27.524362061

d	<09>	6H<00>)J
)<02>-GGCuckoo Hashing<07>We present a simple and efficient dictionary with worst case constant lookup time, equaling the theoretical performance of the classic dynamic perfect hashing scheme of Dietzfelbinger et al. The space usage is similar to that of binary search trees, i.e., three words per key on average. The practicality of the scheme is backed by extensive experiments and comparisons with known methods, showing it to be quite competitive also in the average case.ESAdata_structures/2017-09-11T23:06:28.2831799322017-09-11T23:06:28.283179932<EFBFBD>kI
Y<02>o
-EERRB-Trees: Efficient Immutable Vectors<07>Immutable vectors are a convenient data structure for functional programming and part of the standard library of modern languages like Clojure and Scala. The common implementation is based on wide trees with a fixed number of children per node, which allows fast indexed lookup and update operations. In this paper we extend the vector data type with a new underlying data structure, Relaxed Radix Balanced Trees (RRB-Trees), and show how this structure allows immutable vector concatenation, insert-at and splits in O(logN) time while maintaining the index, update and iteration speeds of the original vector data structure.data_structures/2017-09-11T23:06:28.082377932017-09-11T23:06:28.08237793<EFBFBD>+H	Kq/GGImmutability Changes Everything<07>We need it, we can afford it, and the time is now.CIDRdata_replication/2017-09-11T23:06:27.9392070312017-09-11T23:06:27.939207031~G	e

'GGMathematical Aspects of Consciousness Theory<07>cryptography/2017-09-11T23:06:27.7440400392017-09-11T23:06:27.744040039<EFBFBD>F
!<02>II'GGNTRU Prime<07>Focus of this talk: motivation. 2 Can we predict future attacks? 1996 Dobbertin–Bosselaers– Preneel " RIPEMD-160: a strengthened version of RIPEMD " : " It is anticipated that these techniques can be used to produce collisions for MD5 and perhaps also for RIPEMD. This will probably require an additional effort, but it no longer seems as far away as it was a year ago. " 1996 Robshaw: Collisions " should be expected " ; upgrade " when practical and convenient ". 1 rime. Bernstein y of Illinois at Chicago & he Universiteit Eindhoven o/papers.html ime is joint work with: ok Chuengsatiansup nge van Vredendaal he Universiteit Eindhoven this talk: motivation. 2 Can we predict future attacks? 1996 Dobbertin–Bosselaers– Preneel " RIPEMD-160: a strengthened version of RIPEMD " : " It is anticipated that these techniques can be used to produce collisions for MD5 and perhaps also for RIPEMD. This will probably require an additional effort, but it no longer seems as far away as it was a year ago. " 1996 Robshaw: Collisions " should be expected " ; upgrade " when practical and convenient ". Imagine " This is The atta not brea MD5, so point of speculati is contro and crea state of alternati the very 1 is at Chicago & iteit Eindhoven .html t work with: gsatiansup endaal iteit Eindhoven motivation.IACR Cryptology ePrint Archivecryptography/2017-09-11T23:06:27.6524519042017-09-11T23:06:27.652451904
<00>;<00><0F>r6
<0E><0E>G 
<0A>
<0A>
z
7<0C><0C><0C>b<0B><0B>A
<EFBFBD>
<EFBFBD>
z
B	<09>	<09>	<09>	<09>	G	<08><08><00><08>@<07><07>PG,<06><06>s/<05><05>q<04><04>V<03><03>`%<02><02><02>C
<01>
<01>
<01>
L
<00><00><00>%MA survey on reactive programming
<01>
Blue native PAGE.)Bitcoin
4/Bimodal Multicast<00>@<04>
Bigtable: A Distributed Storage System for Structured Data
$a<04>CBeehive: O(1) Lookup Performance for Power-Law Query Distributions in Peer-to-Peer Overlays
:!EBayesian Network Classifiers
9Backtracking iterators<00>V<04>-Back to the future: the story of Squeak, a practical Smalltalk written in itself
,]
BIG Cache6oASAP: the Alternative Splicing Annotation Project
<01>-]Axiomatic Basis for Computer Programming
7qAutomatic prediction of emotions induced by movies<00>7qAuthoritative Sources in a Hyperlinked Environment<00>:wAuctions and bidding: A guide for computer scientists<00>C
Attacks on the WEP protocolA:wAsynchronous functional reactive programming for GUIs<00>P<04>#
Architectural Styles and the Design of Network-based Software Architectures	I<04>Applications of Machine Learning in Cancer Prediction and Prognosis<00>d<04>IAnd then there were none: a stall-free real-time garbage collector for reconfigurable hardware<00>8u
Analyzing inter-application communication in Android|<04>{
Analysis of Three Bayesian Network Inference Algorithms: Variable Elimination, Likelihood Weighting, and Gibbs Sampling/aAn introduction to argumentation semantics<00>5o
An improved illumination model for shaded display W<04>/An implementation and semantics for transactional memory introspection in Haskell
nC<04>An elementary proof of a theorem of Johnson and Lindenstrauss
2gAn Industrial Strength Audio Search Algorithm
/aAn Analysis of the Cryptocurrency Industry
3U<04>+Adaptive Road Following using Self-Supervised Learning and Reverse Optical Flow<00>9
Acoustic CryptanalysisC8u
Above the Clouds: A Berkeley View of Cloud Computingfc<04>GASAP: Automatic Smoothing for Attention Prioritization in Streaming Time Series Visualization
/aA wait-free queue as fast as fetch-and-add<00>+YA unified theory of garbage collection<00>G<04>A theoretician's guide to the experimental analysis of algorithms<00>7qA taxonomy of suffix array construction algorithms

'QA survey of network virtualization
<01>._A sparse Johnson: Lindenstrauss transform
u/c
A simple totally ordered broadcast protocoleA<04>
A program optimization for automatic database result caching+YA mathematical theory of communication
o0cA history of Haskell: being lazy with class<00>3A history of Erlang<00>B<04>A file undelete with Aho-Corasick algorithm in file recovery<00>7qA few useful things to know about machine learning<00>M<04>A comparison of software and hardware techniques for x86 virtualization

/A Wait-Free Stack
ya<04>CA Versatile Scheme for Routing Highly Variable Traffic in Service Overlays and IP Backbones
9E<04>A Universal Modular ACTOR Formalism for Artificial Intelligence
7X<04>1A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition<00>"I
A Theory of Inferred Causation^<04>=A Response to Cheriton and Skeen's Criticism of Causal and Totally Ordered Communication
6#IA Poor Man's Concurrency Monad
m#K
A Note on Distributed Computingr@<04>
A New Approach to Linear Filtering and Prediction Problems1PK<04>
A Method for Obtaining Digital Signatures and Public-Key Cryptosystems?B<04>A LISP garbage-collector for virtual-memory computer systems<00>=}A Hundred Impossibility Proofs for Distributed Computing
89uA History of the Virtual Synchrony Replication Model
5-]A Gossip-Style Failure Detection Service<00>&OA Fast String Searching Algorithm
<{A Fast Quantum Mechanical Algorithm for Database Search<00>`<04>AA Data-driven Method for the Detection of Close Submitters in Online Learning Environments
j'S
A DNA-Based Archival Storage System(SA Calculus of Communicating Systems<00>;yA Byzantine Fault Tolerant Distributed Commit Protocol
=<}
3-Sweep: extracting editable objects from a single photo$P<04>#
2Q: A Low Overhead High Performance Buffer Management Replacement Algorithm
<04>B<00>?<07><07>v52<06>n<03><06><03>n"<02><0F><0F>ol<05>"<06>
!<0E><0E><0E>Y
<0A>
<0A>
j
6<0C><0C>
<01>v1<0B><0B>w"
<EFBFBD>
<EFBFBD>(
:
	<00>	<09>	<09><05>	<09><00><00>	5	<08><08>
^m<05>
<01><04><04><00>I<04>F<04>%MDeprecating the Observer Pattern
<01>'QDesign Principles Behind Smalltalk
r8sDavis's Poetic Dialogue with Leiris's Autobiography
q<{Comments on a problem in concurrent programming control
c(SDining Cryptographers are Practical
^M<04>Distributed Snapshots: Determining Global States of Distributed Systems
FZ<04>5Consistent Global States of Distributed Systems: Fundamental Concepts and Mechanisms
E<04>Bitcoin
4,]
BIG Cache Abstraction for Cache NetworksG<04>Chain Replication for Supporting High Throughput and Availability
Bm<04>[Can Programming Be Liberated From the von Neumann Style? A Functional Style and its Algebra of Programs<00>K<04>
Calvin: fast distributed transactions for partitioned database systemsNL<04>
CRUSH: controlled, scalable, decentralized placement of replicated dataS CByzantine Chain Replication
<@<04>
Building global and scalable systems with atomic multicast
-P<04>!Breadth-first numbering: lessons from a small exercise in algorithm design<00>&OBreach: Reviving the Crime Attack<00>
"
Everything you always wanted to know about synchronization but were afraid to ask6-Event-Driven FRP<00>4m
Evaluating Generative Models for Text Generation=Epidemic Broadcast Trees<00><{Epidemic Algorithms for Replicated Database Maintenance<00>*WEnd-To-End Arguments in System De7Chaotic bat algorithm
<01>*WDefending against network IDS evasion
<01>*WDistributed Authorization in Vanadium
<01>c<04>GDai-depur: an Integrated Supervisory Multi-level Architecture for Wastewater Treatment Plants
<01>7Buridan’s Principle
<01>F<04>
Cognitive Computing: A Brief Survey and Open Research Challenges
<01>5Bouvier's Conjecture
;/
Blue native PAGE.)/Bimodal Multicast<00>@<04>
Bigtable: A Distributed Storage System for Structured Data
$a<04>CBeehive: O(1) Lookup Performance for Power-Law Query Distributions in Peer-to-Peer Overlays
:!EBayesian Network Classifiers
9Backtracking iterators<00>V<04>-Back to the future: the story of Squeak, a practical Smalltalk written in itself
C
Direct and Indirect Effects<}
Diminished reality for augmented reality interior design.P<04>#
Digital Video Stabilization and Rolling Shutter Correction using Gyroscopes5Differential Privacy<00>K<04>Design requirements for technologies that encourage physical activity<00>;yDefining gamification: a service marketing perspective<00>/
Deep Colorization%5mDecoding speech in the presence of other sources<00>0cDatabase metatheory: asking the big queries
"F<04>
Dapper, a Large-Scale Distributed Systems Tracing Infrastructure
Aa<04>CDP-SLAM: Fast, Robust Simultaneous Localization and Mapping Without Predetermined Landmarks<00>+YD-Expressions: Lisp Power, Dylan Style<00>)
Cuckoo HashingJT<04>)Crossing the gap from imperative to functional programming through refactoring<00>3
Crash-Only SoftwareB<}
Coupled 3D reconstruction of sparse facial hair and skin38sCounting Large Numbers of Events in Small Registers
+YCoq: the world's best macro assembler?<00>D<04>	Copysets: Reducing the Frequency of Data Loss in Cloud Storage
@)W
Continuous Shading of Curved Surfaces!A<04>
Consistency in Non-Transactional Distributed Storage SystemsQS<04>'Consistency and fault tolerance for erasure-coded distributed storage systems
,3iConsensus in the presence of partial synchrony
?_<04>?Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data<00>(U
Computing Machinery and Intelligence*WCompressors with Vanes-Based Diffuser
:wComposable and compilable macros: : you want it when?<00>6oCompiling pattern matching to good decision trees<00>,[Communication Theory of Secrecy Systems
'QCommunicating Sequential Processes<00><{Commodifying Replicated State Machines with OpenReplica
>L<04>
Chord: A scalable peer-to-peer lookup service for internet applicationsh*Y
Causal Diagrams for Empirical Research;{
Cassandra – A Decentralized Structured Storage SystemV)UCan SPDY really make the web faster?<00>

<01><00>
<01><0F><0F><0F><0F><0F><0F><0F>tk[Q<02>H?2<0E><0E><0E><0E><0E>N<0E><0E><0E>w_PG8"/

<0A>
<0A>
<0A>
<01>
<0A>
<0A>
<0A>
<0A>D
<0A>
r
i
Z
O
=
<0C><0C><0C><0C><0C><0C><0C><0C><0C>}h]P:1	<0B><0B><0B><0B><0B><0B><0B>ylbdXG;1<02>(
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
w
j
a
U
I
@
4
$

	<09><02>	<09>	<09>	<09>	<09>	<09>	<09>	{%	i	^	R	:	,			<08><08><08><08><08><08><08><08><08>}j_rTH<1&p	<07><07><07><02><07><07><07><07><07><03><07>{h<02>Q<2#
<06><06><06><06><06><06>wj\K7!<05><02><05><05><05><05><02><05>yhX@$?<02><04><04>W<04><04><04>o`P>-<03> 
<03><03><03>6L<03><03><03><03><03>
<01>
<01>3area of mathematics<03>)data loss<03>data item


data flasd<04>	asap<04>#cardinality<04>
counting|	aslry-analysis threadsw
blessingt#choi matrixo5computational effecticonductorf
co-actorK/cleanup operation@1computing hardware+bms$agenda/byzantine failurecensors;anonymous communicationconduct
cover
3considerable amount!ciphertext+cloud computing
cop<03>'crash failure<03>
crash<00>	cpus{cpu
_cpl<02>)
counterfactual:counter+correct process<03>'correct model<00>copying
<01>#coordinator
<01>%continuation<02>!contention<00>containern9construction algorithm'constant timei1consistent hashing
7consistency semantics
1consensus protocol<03>!Econsensus in an asynchronous<03>3consensus algorithm<03>9concurrent programming<00>1concurrent program<00>!concurrent<00>#concurrency<00>!conceptnetQcon-computer systems\1computer scientist
<01>)
computer modelY/computer hardware
C5computation resource
computa
&!compromise -complex problems<03>)complex objectQ#compilation
commuterbcommuteh'commutativityf;communication subsystem<03>command<02>9
comfort and confidence;
comdroid;combinatorial algorithm<03>%
colorization~3collision avoidance<02>collector
<01>	coin<03>+code inspection'/co-representation~'cluster state
k/cluster computing<03>!cloud user
Pclojure
clock<00>clo<02>clique<03>
clinicalK
classifi3classic]#class-based<02>clarityG!cityengine<00>
cient
chunkFchubby
mchrome<02>
chord
Z
chessS'checkpointing
n!checkpoint<03>
checking<02>
check<02>)chandy-lamport<03>/chain replication<03>cga<00>#certificate<03>cep%
cent
cde#ccs and csp<02>
cbrZ

causation2

causality51causal consistency<03>causal<00>

cation*%catamorphismtcarbon<00>/cancer predictionJ'
camera motion^-call-time choice-
calculus
<01>caching
<01>/byzantine general
<01>3byzantine agreement
<01>	byte<02>bwt	!burstinessbullet
Dbug<00>bufferRbucket<00>bst`browser<02>
brdfr'bracket types<02>%
bp algorithm7boyer-moore algorithm#boyer-moore!7boyer moore algorithm
bot"border<03>
boosting8bollob-!
board game0bncL	blog

blockinI#block layer
<01>	blob<00>	blem<00>bitcoin<03>3bisection bandwidth
<01>'
biotechnologyL#binary tree<00>3binary search trees_#binary code<03>
billions
<01>
bigtable<03>
big data
bidding
<01>bid
<01>%bft protocol
rbft
<01>1	belief propagationbeehive<03>
bcube
<01>-
bayesian network6bationbad<02>backend<03>+authority score
auction
<01>atomicity
-atomic multicast<03>atomic<03>
ation !Easynchronous message passing&=asynchronous environment<03>%asynchronous
<01>
async<02>asymmetry
<01>ast9assembler<02>asr<02>!
artificial-
arrow<02>;argumentation semantics<02>;argumentation framework<02>
archivalK
arcO5approximate counting
app
api)%anti-entropy
<01>ant<02>anonymity
<01>annLanimation<02>3
android application#
android app

ancestorh
analytic
U'
analysis tool7analysis of algorithm
<01>ams!amazon.comw
alphago1allocator
h/allocation scheme<00>/algebraic effects<02>algebraqalg<02>aicy	afrp<02>!affordance
<01>adl<02>
adaboost6+actual hardware<00>)activity level
<01>
acmN	acid
!accidental
>9abstract argumentation<02>/3d reconstruction<00>
<00>
<01><05>xmbN;(
<04><04><04><04><04><04><04><04><04>k<02>`J9 <03><03><03>
<01><0F><0F><0F><0F><0F><0F><0F>wk`WN{@1	<0E><0E>Q<0E><0E>k<0E><0E><0E>k\SXA0
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>x
<0A>
i
R
0

#
<0C><0C><0C><03><0C><0C><0C><0C><0C>lcZ<02>RE;.#<02><0B><02><0B><0B><0B><0B>n<0B><0B><0B><0B><0B>wm
<01><02><02>cE7*!

<EFBFBD>
<EFBFBD><02>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
p
e
[
K
?
1
%
<03>

	<09>	<09>^	<09>	<09>	<09>	<09>	<09>	<09>	r	i	]	Q	@	1		<08><08><08><08><08><08><08>r_UK:&<07><07><07><07><07><07><03><07><07><07>qgZD;1(<02><06><06><06><06><06>rZC.A<05><05>D<05><05><05><03><05><02><02>{riaXMD2  
educator<03>)data operation
}!data space0impala
%immutability<00>%illumination<00>genomic<04>defense{evasionu!delegationp1de finetti theoremkeffhdak_dsl^3functional languageV
eeectT	dyadL
downtimeD3employee engagement;
facet:+dominant thread9=dimensionality reduction4/general principle)-design principle(	ebay/different cluster1global informationdisruptor
forensic<03>!data model<03>
essay<03>+data management<03>data loss<03>data item


data flow3data center network
<01>#data center
:-data aggregation
darpa<02>-daily medication
<01>
dag4
cylinder}cut<03>customb
curse2
curit
R)cuckoo hashing<00>cuckoo<00>+Ycsp communicating sequential processes<02>csf
<01>%cryptography<00>'cryptographic
<01>'cryptographer<00>)cryptocurrency<03>
crush

crowd
<01>crisis<03>#crazy stoneE9global serializability<03>ghc
<01>gfstgeometric<02>/generic technique<02>3generic programming)generator;generational collection
<01>+general pattern<03>/garbage collector
<01>1garbage collection<00>garbage
<01>%gamification
<01>game treeA%game element
<01>)future attacks<00>3fundamental concept<03>,[functional programming language haskell'9functional programming<02>fun<02>	full<00>frp<02>-frequency momentfreenet
X	free
f'fragmentation
i	fpgaP+formal semantic(formal<02>
footnoteR#fm sketches

flowdroid	%flow control
<01>flavor<02>fixs
fittingy/first-order logic<02>)fingerprinting=#fingerprint>	fine<00>	fifo<03>'fetch-and-add^-feature engineer5fds~=fault-tolerant consensus
<01>)fault-tolerant
p+fault tolerance
b	fast)famous example<02>
familiar
@-failure detector/failure detection
<01>factoring<02>%
factor graphfacial<00>facade<00>faa\-expression graph<03>7experimental analysis
<01>expensive<00>exp
executor
<01>5eventual consistencyx
eventual
7ets,)
essential stepessential
?ers4erlang<00>
epidemic
<01>epaxos
<01>!enumerator	enum

enigma75end-to-end principle|/encryption method<00>)encryption key<00>!encryptione
encodingJ	ence
encembedding&elocity<02>+electronic mail<00>
elder
<01>eld<00>elastic
N
eighties*=efficient implementation<02>	effi
(	edsl+editor;editing<00>
edit=5economics literature
<01>ecc<00>ebrV%eavesdropperf'
early warning>e.g0dynamoydwa<02>	dual
<01>dsg`dsa<00>
dryad
1dropbox<02>	
droiddp-slam<02>
doxdos<03>dof<02>'documentationK;document classification<00>dns<03>'
dna computingFdlp<00>%dissertationedissent<03>	disk<02>!disclosure<00>dis<00>directorycdilemma|%digital game
<01>!Ediffie-hellman key agreement<00>/different systems<03>/different results<03>7different consistency
	7different application
\dif<00>!dictionary<00>dht	dhmm<02>-development team(developed_detour
<01>;deterministic execution
#determinism
%design space
<01>des<00>depth map<00>7dependent type theory<02>)dependent type<02>denalil#demographic
<01>degreaser<02>%definition 1)defect density);deep learning technique<00>)decryption key<00>)decision treesdebuggingE
deadlock
Ldcs
$dcn
;
dcell
<01>dc-net<03>
dbmss<03>datastore<03>!datacenter
x+database theoryl-database systems<00>data type<02>)data structure%
data storageM
<00>
<01><0F><0F><0F><0F><0F><0F><0F><0F>sj^L<$<0E><0E><0E><0E><0E><0E><0E><0E>{ogZPB9 
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
t
c
Q
B
6
(
 

<0C><0C><0C><0C><0C><0C><0C><0C>s[K80(
<0B><0B><0B><0B><0B><0B><0B><0B><0B><0B>|tl\PH4(	

<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
}
q
h
\
N
C
7
'


	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	q	b	M	@	/	<08><08><08><08><08><08><08>k\?6+<07><07><07><07><07><07><07><07><07><07><07>q_@7'<06><06><06><06><06><06><06><06><06><06>\L-$<05><05><05><05><05><05><05>{eN6<04><04><04><04><04><04><04><04>ypg\PG:1(<03><03><03><03><03><03>|laOE<0
<02><02><02><02><02><02><02><02><02><02>^TG3'
<01>
<0A>q!hash table<0F>p%immutability<07>orime	<09>nripemd<11>m)future attacks
<EFBFBD>lupgrade<07>kblem<1F>jEdiffie-hellman key agreement<06>idlp
<0A>h!public-key<0B>gknapsack
<0A>f!disclosure<07>etalk	<09>dpuzzle<0F>c%cryptography<10>b'cryptographer	<09>areboot<0C>`expensive<08>_crash<15>^1persistent storage	<09>]uptime<06>\wep<07>[read<0F>Z%plementation<08>Yqueue
<0A>X!concurrent<0F>W%non-blocking<1A>V;public-key cryptosystem<11>U)decryption key<06>Tecc<12>S+electronic mail<11>R)encryption key<14>Q/key cryptosystems<06>Pdsa<14>O/encryption method<06>Ntes<06>Mdes
<EFBFBD>Llogical<06>Kdis	<09>Jcausal<08>Iclock<06>Hpen<06>Grus<07>Ffine<0E>E#microreboot<06>Dbug<15>C1priority inversion<0C>Boperating<08>Ainter<14>@/personal computer<0B>?handling<19>>9concurrent programming
<EFBFBD>=monitor<16><3memory architecture<15>;1garbage collection<14>:/allocation scheme<13>9-machine language<12>8+actual hardware<0F>7%memory model<06>6hol<10>5'correct model	<09>4erlang<15>31concurrent program<0F>2%unit testing<11>1)race condition<08>0pulse<0E>/#concurrency<06>.mcs<1C>-?synchronization primitive
<0A>,!contention$<24>+Operformance and energy efficiency<07>*lock	<09>)mosaic<0B>(panorama<07>'seam
<EFBFBD>&editing	<09>%stereo<06>$dif	<09>#facial<1B>"=reconstruction algorithm<0F>!%skin surface<0B> scanning<07>hair
<0A>!cityengine<06>cga<1C>?line integral convolution<0F>%vector field
<0A>!streamline<06>eld<06>odt
<EFBFBD>grammar<08>split<06>mar	<09>street	<09>facade	<09>carbon<07>nadp<11>)ros production<07>nadh<08>nadph<0B>
radiance<0F>%illumination<08>tance<06>
ray<1A>	;document classification<0C>hypertext<1A>;web page classification<16>3text classification<0B>relevant<07>tsdf<0C>depth map<14>/3d reconstruction<19>
9kinectfusion algorithm<1A>;deep learning technique1reference database~%colorization}cylinder|-simple 3d shapes
{!photographz%single photo
yfittingxpmvwrbfvureu9poisson reconstructiontmvsslightingrbrdfqspecular
pshadingo#reflectancenture	mshadow	lviewerk#ray tracing
jgraphic	ishaderhrendering
grealismfgpus
eoctreesdstreamingcgpubvoxelamate`gyroscope
_shutter^'camera motion]3video stabilization
\writing	[mexicaZcbrY)computer model
Xtension
WminhashV+minwise hashingUlsh
TshingleS#resemblanceRlfuQlirPlrfuOarcNacmM%data storageL'biotechnologyKarchivalJencoding
IblockinH-hamiltonian pathGhppF'dna computing
Egraph g
D!same topicCldaBitmA)topic modeling@#topic model?3vandalism detection>'early warning=edit	<vandal;9comfort and confidence:)counterfactual9-little knowledge8swiftness	7enigma6-bayesian network5causality4dag3sgs2causation
1alphago
0!board game/'reinforcement.%intelligence
-!artificial,soap+=rest architectural style	*cation)api(soa
'mhealth&)sensitive data%hipaa$5security and privacy#judge"bot!los 5machine intelligencecentprivilegedroidcomdroidcde
naturalndedoxmediationdata flow
!smartphone)essential step3market applications7n.a. n.a. pc analysis	intenticc/security analysis3android application
#android app'analysis tool
malware
leak	flowdroidappowslifecycle%bp algorithm+message passing+graphical model%factor graph
1belief propagation
<00>
<01><0F><0F><0F><0F><0F><0F><0F><0F>sbKA+<0E><0E><0E><0E><0E><0E><0E><0E><0E>seP5+"
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
e
Z
A
6
'

<0C><0C><0C><0C><0C><0C><0C><0C><0C><0C>}nbXOD4)
<0B><0B><0B><0B><0B><0B><0B><0B>{k\NE<%

<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
q
h
]
O
A
3


	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	~	i	Z	C	,	"		<08><08><08><08><08><08><08>sjXE8&
<07><07><07><07><07><07>|i[J>5	<06><06><06><06><06><06><06><06>yk]K-<05><05><05><05><05><05><05><05><05>vdWM8'<04><04><04><04><04><04><04><04>i^E:+<03><03><03><03><03><03><03><03><03>ypaQG="	<02><02><02><02><02><02><02><02>ri^C-


<01>
<01>
<EFBFBD>Zcopying
<EFBFBD>Ygarbage<06>Xsns<10>W'user activity
<0A>V!reputation<13>U-daily medication<18>T7medication compliance<08>Selder<06>Roch<0B>Qmechanic<06>Phar<14>O/non-game contexts	<09>Nsenior<0F>M%game element<0F>L%digital game<0E>K#demographic
<EFBFBD>Jpitfall<18>I7experimental analysis<16>H3theoretical results<18>G7analysis of algorithm<07>Fment<07>Espel
<0A>D!affordance<0C>Cmarketing<06>Bsom<0F>A%gamification<06>@sts<0C>?temporale<0C>>asymmetry
<EFBFBD>=preterm<06><csf<17>;5economics literature
<EFBFBD>:auction
<EFBFBD>9bidding<06>8bid<15>71computer scientist<0B>6liveness<0C>5ironfleet<08>4dcell<16>33data center network<08>2bcube<16>13bisection bandwidth<1A>0;viewstamped replication
<EFBFBD>/primary
<0A>.!leadership	<09>-mixnet<0C>,anonymity<10>+'cryptographic<08>*crowd<0E>)#mix network	<09>(sender<08>'mixes<07>&http<0E>%#coordinator<12>$+serializability<07>#push
<EFBFBD>"caching<0F>!%design space
<EFBFBD> virtual
<0A>!unikernels<06>vms	<09>mirage<0F>%social graph
<EFBFBD>unicorn<0B>billions<0E>#millisecond<0F>%life science	<09>leader	<09>epaxos<06>bft<11>)paxos protocol<1B>=fault-tolerant consensus<0F>%asynchronous<0B>calculus<0B>multiset	<09>jocaml<08>ocaml<16>
3byzantine agreement<08>repli<06>lie<14>
/byzantine general<0E>	#synchronous<0C>zookeeper<12>+google's chubby	<09>detour<1D>Aresilient overlay networks<06>qos	<09>ticast<0E>#low latency<0B>
executor<10>'task duration<17>5computation resource<13>~-multiple devices<11>})data operation<0B>|sinfonia<0B>{gnutella
<0A>z!powergraph<12>y+google's pregel
<0A>x!datacenter<06>wgps	<09>vgraphx<0F>u%transparency
<EFBFBD>tmasking<10>s'memory access<0F>r%bft protocol<06>qsmr<11>p)fault-tolerant<1C>o?state machine replication<10>n'checkpointing	<09>mchubby
<EFBFBD>lschedul<10>k'cluster state<0C>jscheduler<10>i'fragmentation<0C>hallocator	<09>gmalloc<07>ffree<14>e/stream processing<14>d/programming model<0C>cmillwheel<12>b+fault tolerance
<0A>a!invocation<12>`+linearisability<06>_cpu<07>^yarn<07>]meso<18>\7different application<08>[ologn<08>Zchord<0C>Ymulticast
<EFBFBD>Xfreenet<0C>Wmessaging<14>V/messaging systems<0B>Uanalytic<0B>Tlinkedin<0B>Slog data<08>Rcurit<06>Qsaa
<0A>P!cloud user	<09>Otechni
<EFBFBD>Nelastic<07>Msync<0B>Ldeadlock<1A>K;synchronous replication<07>Jstat<08>Iplaid<0E>H#inheritance<08>Gmixin
<EFBFBD>Fsch rli	<09>Esilver	<09>Dbullet<14>C/computer hardware<06>Bput<06>Anfr<0B>@familiar<0C>?essential
<0A>>!accidental<07>=ject<11><)load balancing<06>;dcn<0E>:#data center<17>95network architecture
<EFBFBD>8monsoon<0B>7eventual<13>6-weak consistency<0C>5timestamp<19>49optimistic replication<08>3merge
<0A>2!map-reduce<08>1dryad<06>0mod<07>/mdcc	<09>.master<0C>-megastore<0C>,wide-area<13>+-query processing<08>*sdd-1<06>)int<07>(effi<08>'rithm
<EFBFBD>&computa<06>%lem<06>$dcs<07>#pace
<0A>"!hyperspace<0B>!hyperdex<12> +key-value store<0C>data item<08>nosql<16>3relational database<08>paxos<1A>;deterministic execution
<EFBFBD>h-store	<09>tation<06>sql<0E>#interactive	<09>impala<0B>big data<0C>mapreduce<07>rush<08>crush<15>1consistent hashing<06>osd<0B>metadata<06>vll<07>
weak<18>7consistency semantics<12>+linearizability<0B>
semantic<18>	7different consistency<0E>#determinism<06>svm<0C>atomicity	<09>recent
<EFBFBD>replica<07>acid<0F>%small subset<08>
tpc-c<16>3multiple partitions<18>7transactional support<13>~-database systems<07>}blob<14>|/number of records<0E>{#binary tree<11>z)linear hashing	<09>ybucket<07>xfull<0C>whopscotch	<09>vcuckoo<0E>u#theoretical<10>t'hash function
<0A>s!dictionary<11>r)cuckoo hashing

e
<EFBFBD>F
e<00>^M
[<02>Q#GGf4: Facebook's Warm BLOB Storage System<07>Facebook's corpus of photos, videos, and other Binary Large OBjects (BLOBs) that need to be reliably stored and quickly accessible is massive and continues to grow. As the footprint of BLOBs increases, storing them in our traditional storage system, Haystack, is becoming increasingly inefficient. To increase our storage efficiency, measured in the effective-replication-factor of BLOBs, we examine the underlying access patterns of BLOBs and identify temperature zones that include hot BLOBs that are accessed frequently and warm BLOBs that are accessed far less often. Our overall BLOB storage system is designed to isolate warm BLOBs and enable us to use a specialized warm BLOB storage system, f4. f4 is a new system that lowers the effective-replication-factor of warm BLOBs while remaining fault tolerant and able to support the lower throughput demands. f4 currently stores over 65PBs of logical BLOBs and reduces their effective-replication-factor from 3.6 to either 2.8 or 2.1. f4 provides low latency; is resilient to disk, host, rack, and datacenter failures; and provides sufficient throughput for warm BLOBs.OSDIdatastores/2017-09-11T23:06:28.5157250982017-09-11T23:06:28.515725098<EFBFBD>cL
3<02>k#-GGDynamic Hash Tables<07>Linear hashing and spiral storage are two dynamic hashing schemes originally designed for external files. This paper shows how to adapt these two methods for hash tables stored in main memory. The necessary data structures and algorithms are described, the expected performance is analyzed mathematically, and actual execution times are obtained and compared with alternative techniques. Linear hashing is found to be both faster and easier to implement than spiral storage. Two alternative techniques are considered: a simple unbalanced binary tree and double hashing with periodic rehashing into a larger table. The retrieval time of linear hashing is similar to double hashing and substantially faster than a binary tree, except for very small trees. The loading times of double hashing (with periodic reorganization), a binary tree, and linear hashing are similar. Overall, linear hashing is a simple and efficient technique for applications where the cardinality of the key set is not known in advance.Commun. ACMdata_structures/2017-09-11T23:06:28.4560610352017-09-11T23:06:28.456061035<EFBFBD>QK
/<02>Y-GGHopscotch Hashing<07>We present a new resizable sequential and concurrent hash map algorithm directed at both uni-processor and multicore machines. The algorithm is based on a novel hopscotch multi-phased probing and displacement technique that has the flavors of chaining, cuckoo hashing, and linear probing, all put together, yet avoids the limitations and overheads of these former approaches. The resulting algorithm provides a table with very low synchronization overheads and high cache hit ratios. In a series of benchmarks on a state-of-the-art 64-way Niagara II multicore machine, a concurrent version of the new algorithm proves to be highly scalable, delivering in some cases 2 or even 3 times the throughput of today's most efficient concurrent hash algorithm, Lea's ConcurrentHashMap from java.concurr.util. Moreover, in tests on both Intel and Sun uni-processor machines, a sequential version of the algorithm consistently outperforms the most effective sequential hash table algorithms including cuckoo hashing and bounded linear probing. The most interesting feature of the new hopscotch algorithm is that it continues to deliver good performance when the table is more than 90% full, increasing its advantage over other algorithms as the table density grows.DISCdata_structures/2017-09-11T23:06:28.3564519042017-09-11T23:06:28.356451904
m<00><0F><0F><0F><0F>V6<0E><0E><0E><0E>lG'
<0A>
<0A>
<0A>
v
I
!<0C><0C><0C><0C>kC%<0B><0B><0B><0B>x^>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
b
L
$
	<09>	<09>	<09>	<09>	i	9	<08><08><08>|X1<07><07><07><07>Z8<06><06><06><06>a?<05><05><05>R(<04><04><04>{R0<03><03><03>oG-<02><02><02><02>d>$
<01>
<01>
<01>
|
R
.
<00>'<27>G/
Madhukar KorupoluMadhukarKorupolu<1D>F%
Luis PedrosaLuisPedrosa!<21>E)
Abhishek VermaAbhishekVerma'<27>D/
%Hari BalakrishnanHariBalakrishnan&<26>C/M. Frans KaashoekM.FransKaashoek"<22>B+David R. KargerDavidR.Karger<1F>A'
Robert MorrisRobertMorris<13>@
Jun RaoJunRao<1F>?'
Neha NarkhedeNehaNarkhede<17>>
Jay KrepsJayKreps#<23>=+
David PattersonDavidPatterson!<21><)
Andy KonwinskiAndyKonwinski<19>;!
Randy KatzRandyKatz<1F>:'
Matei ZahariaMateiZaharia<19>9!
Ion StoicaIonStoica<1D>8%
Ariel RabkinArielRabkin(<28>71David A. PattersonDavidA.Patterson<17>6
Gunho LeeGunhoLee%<25>5-
Andrew KonwinskiAndrewKonwinski<1E>4'Randy H. KatzRandyH.Katz&<26>3/Anthony D. JosephAnthonyD.Joseph<1F>2'
Rean GriffithReanGriffith%<25>1-
Michael ArmbrustMichaelArmbrust*<2A>03Flavio P. JunqueiraFlavioP.Junqueira<1F>/'
Benjamin ReedBenjaminReed&<26>./Patrick E. O'neilPatrickE.O'neil<15>-
Jim GrayJimGray"<22>,+Andrew P. BlackAndrewP.Black<19>+!
Roel WuytsRoelWuyts)<29>*1
Nathanael SchärliNathanaelSchärli%<25>)-
!Oscar NierstraszOscarNierstrasz'<27>(/
Stéphane DucasseStéphaneDucasse*<2A>'3Frederick P. BrooksFrederickP.Brooks%<25>&-
Sudipta SenguptaSudiptaSengupta<1F>%'
Parveen PatelParveenPatel <20>$)David A. MaltzDavidA.Maltz#<23>#+
Parantap LahiriParantapLahiri*<2A>"3Albert G. GreenbergAlbertG.Greenberg<1F>!'
Joe ArmstrongJoeArmstrong<1D> %
Marc ShapiroMarcShapiro<1F>'
Yasushi SaitoYasushiSaito,<2C>5Douglas Stott ParkerDouglasStottParker#<23>+
Ruey-Lung HsiaoRuey-LungHsiao<19>!
Ali DasdanAliDasdan!<21>)
Hung-Chih YangHung-ChihYang<1F>'
Samuel MaddenSamuelMadden*<2A>3Michael J. FranklinMichaelJ.Franklin<17>
Gene PangGenePang<19>!
Tim KraskaTimKraska<1B>#
Eugene WongEugeneWong$<24>-David W. ShipmanDavidW.Shipman,<2C>5#Christopher L. ReeveChristopherL.Reeve$<24>-Terry A. LandersTerryA.Landers!<21>)
Michael HammerMichaelHammer!<21>)
Nathan GoodmanNathanGoodman<1B>#
Stephen FoxStephenFox*<2A>3Philip A. BernsteinPhilipA.Bernstein$<24>-James B. RothnieJamesB.Rothnie$<24>
-Michael D. ErnstMichaelD.Ernst-<2D>5
!Magdalena BalazinskaMagdalenaBalazinska<17>
Bill HoweBillHowe<17>

Yingyi BuYingyiBu"<22>	+Emin Gün SirerEminGünSirer<1D>%
Bernard WongBernardWong!<21>)
Robert EscrivaRobertEscriva<1B>#
Himani ApteHimaniApte%<25>-
Traian StancescuTraianStancescu<13>
Ian RaeIanRae#<23>+
!John CieslewiczJohnCieslewicz!<21>)
Stephan EllnerStephanEllner%<25>
-
!David MenestrinaDavidMenestrina%<25>-
#Kyle LittlefieldKyleLittlefield<1F>'
Mircea OanceaMirceaOancea<1D>~%
Eric RollinsEricRollins<1D>}%
Chad WhipkeyChadWhipkey<17>|
Ben HandyBenHandy<1B>{#
Bart SamwelBartSamwel#<23>z+
Radek VingralekRadekVingralek<19>y!
Jeff ShuteJeffShute$<24>x-Naga Rekha MalaeNagaRekhaMalae#<23>w+
!Theo VassilakisTheoVassilakis<1B>v#
Matt ToltonMattTolton%<25>u-
!Shiva ShivakumarShivaShivakumar!<21>t)
Geoffrey RomerGeoffreyRomer <20>s)Jing Jing LongJingJingLong!<21>r)
Andrey GubarevAndreyGubarev<1F>q'
Sergey MelnikSergeyMelnik&<26>p/David G. AndersenDavidG.Andersen%<25>o-
Michael KaminskyMichaelKaminsky*<2A>n3Michael J. FreedmanMichaelJ.Freedman#<23>m+
Carlos MaltzahnCarlosMaltzahn"<22>l+Ethan L. MillerEthanL.Miller"<22>k+Scott A. BrandtScottA.Brandt<1C>j%Sage A. WeilSageA.Weil<1F>i'
Marko VukolicMarkoVukolic<1D>h%
Paolo ViottiPaoloViotti"<22>g+Daniel J. AbadiDanielJ.Abadi<1B>f#
Philip ShaoPhilipShao<13>e
Kun RenKunRen<1F>d'
Shu-Chun WengShu-ChunWeng%<25>c-
Thaddeus DiamondThaddeusDiamond'<27>b/
Alexander ThomsonAlexanderThomson<1F>a'
Sanjeev KumarSanjeevKumar<1D>`%
Linpeng TangLinpengTang/<2F>_7
#Sivakumar ViswanathanSivakumarViswanathan<1F>^'
Shiva ShankarShivaShankar<1B>]#
Satadru PanSatadruPan<19>\!
Weiwen LiuWeiwenLiu<19>[!
Ernest LinErnestLin
<05><0B><06><05><00>
P
<00>

%GGA New Approach to Linear Filtering and Prediction Problems1<07>data_fusion/2017-09-11T23:06:28.9414199222017-09-11T23:06:28.941419922<EFBFBD>O
e<02>#GGThe Case for Determinism in Database Systems<07>Replication is a widely used method for achieving high availability in database systems. Due to the nondeterminism inherent in traditional concurrency control schemes, however, special care must be taken to ensure that replicas don't diverge. Log shipping, eager commit protocols, and lazy synchronization protocols are well-understood methods for safely replicating databases, but each comes with its own cost in availability, performance, or consistency. In this paper, we propose a distributed database system which combines a simple deadlock avoidance technique with concurrency control schemes that guarantee equivalence to a predetermined serial ordering of transactions. This effectively removes all nondeterminism from typical OLTP workloads, allowing active replication with no synchronization overhead whatsoever. Further, our system eliminates the requirement for two-phase commit for any kind of distributed transaction, even across multiple nodes within the same replica. By eschewing deadlock detection and two-phase commit, our system under many workloads outper-forms traditional systems that allow nondeterministic transaction reordering.PVLDBdatastores/2017-09-11T23:06:28.8998020022017-09-11T23:06:28.899802002<EFBFBD>tN<00><02>'/#EECalvin: fast distributed transactions for partitioned database systems<07>Many distributed storage systems achieve high data access throughput via partitioning and replication, each system with its own advantages and tradeoffs. In order to achieve high scalability, however, today's systems generally reduce transactional support, disallowing single transactions from spanning multiple partitions. Calvin is a practical transaction scheduling and data replication layer that uses a deterministic ordering guarantee to significantly reduce the normally prohibitive contention costs associated with distributed transactions. Unlike previous deterministic database system prototypes, Calvin supports disk-based storage, scales near-linearly on a cluster of commodity machines, and has no single point of failure. By replicating transaction inputs rather than effects, Calvin is also able to support multiple consistency levels---including Paxos-based strong consistency across geographically distant replicas---at no cost to transactional throughput.SIGMOD Conferencedatastores/2017-09-11T23:06:28.742867922017-09-11T23:06:28.74286792
<00>	<09><00><00>NS<00><02>k#GGCRUSH: controlled, scalable, decentralized placement of replicated data<07>Emerging large-scale distributed storage systems are faced with the task of distributing petabytes of data among tens or hundreds of thousands of storage devices. Such systems must evenly distribute data and workload to efficiently utilize available resources and maximize system performance, while facilitating system growth and managing hardware failures. We have developed CRUSH, a scalable pseudorandom data distribution function designed for distributed object-based storage systems that efficiently maps data objects to storage devices without relying on a central directory. Because large systems are inherently dynamic, CRUSH is designed to facilitate the addition and removal of storage while minimizing unnecessary data movement. The algorithm accommodates a wide variety of data replication and reliability mechanisms and distributes data in terms of user-defined policies that enforce separation of replicas across failure domains.SC '06datastores/2017-09-11T23:06:29.1919130862017-09-11T23:06:29.191913086<EFBFBD>R
u<02>+#GGLightweight Locking for Main Memory Database Systems<07>Locking is widely used as a concurrency control mechanism in database systems. As more OLTP databases are stored mostly or entirely in memory, transactional throughput is less and less limited by disk IO, and lock managers increasingly become performance bottlenecks. In this paper, we introduce very lightweight locking (VLL), an alternative approach to pessimistic concurrency control for main-memory database systems that avoids almost all overhead associated with traditional lock manager operations. We also propose a protocol called selective contention analysis (SCA), which enables systems implementing VLL to achieve high transactional throughput under high contention workloads. We implement these protocols both in a traditional single-machine multi-core database server setting and in a distributed database where data is partitioned across many commodity machines in a shared-nothing cluster. Our experiments show that VLL dramatically reduces locking overhead and thereby increases transactional through-put in both settings.PVLDBdatastores/2017-09-11T23:06:29.1268439942017-09-11T23:06:29.126843994<EFBFBD>HQ<00><02>_/#GGConsistency in Non-Transactional Distributed Storage Systems<07>Over the years, different meanings have been associated with the word <i>consistency</i> in the distributed systems community. While in the &#8217;80s &#8220;consistency&#8221; typically meant <i>strong consistency</i>, later defined also as <i>linearizability</i>, in recent years, with the advent of highly available and scalable systems, the notion of &#8220;consistency&#8221; has been at the same time both weakened and blurred.
 In this article, we aim to fill the void in the literature by providing a structured and comprehensive overview of different consistency notions that appeared in distributed systems, and in particular <i>storage</i> systems research, in the last four decades. We overview more than 50 different consistency notions, ranging from linearizability to eventual and weak consistency, defining precisely many of these, in particular where the previous definitions were ambiguous. We further provide a partial order among different consistency predicates, ordering them by their semantic &#8220;strength,&#8221; which we believe will be useful in future research. Finally, we map the consistency semantics to different practical systems and research prototypes.
 The scope of this article is restricted to non-transactional semantics, that is, those that apply to single storage object operations. As such, our article complements the existing surveys done in the context of transactional, database consistency semantics.ACM Comput. Surv.datastores/2017-09-11T23:06:28.9988210452017-09-11T23:06:28.998821045
<03>	x<06><03><00>cV
{<02>C
#GGCassandra – A Decentralized Structured Storage System<07>Cassandra is a distributed database bringing together Dynamo's fully distributed design and Bigtable's ColumnFamily-based data model. It is highly scalable both in terms of storage volume and request throughput while not being subject to any single point of failure. This paper presents an architectural overview of Cassandra and also discusses how its design is founded in fundamental principles of distributed systems. Some practical applications that use Cassandra are also listed. This paper also presents why Cassandra may not be a good choice for some applications by highlighting its limitations.datastores/2017-09-11T23:06:29.5156398932017-09-11T23:06:29.515639893<EFBFBD>lU
q<02>U#GGDremel: Interactive Analysis of Web-Scale Datasets<07>Dremel is a scalable, interactive ad hoc query system for analysis of read-only nested data. By combining multilevel execution trees and columnar data layout, it is capable of running aggregation queries over trillion-row tables in seconds. The system scales to thousands of CPUs and petabytes of data, and has thousands of users at Google. In this paper, we describe the architecture and implementation of Dremel, and explain how it complements MapReduce-based computing. We present a novel columnar storage representation for nested records and discuss experiments on few-thousand node instances of the system.PVLDBdatastores/2017-09-11T23:06:29.3549560552017-09-11T23:06:29.354956055<EFBFBD>T<00>9<02>?#GGDon't settle for eventual: scalable causal consistency for wide-area storage with COPS<07>Geo-replicated, distributed data stores that support complex online applications, such as social networks, must provide an "always-on" experience where operations always complete with low latency. Today's systems often sacrifice strong consistency to achieve these goals, exposing inconsistencies to their clients and necessitating complex application logic. In this paper, we identify and define a consistency model---causal consistency with convergent conflict handling, or <i>causal</i>+---that is the strongest achieved under these constraints.
 We present the design and implementation of COPS, a key-value store that delivers this consistency model across the wide-area. A key contribution of COPS is its scalability, which can enforce causal dependencies between keys stored across an entire cluster, rather than a single server like previous systems. The central approach in COPS is tracking and explicitly checking whether causal dependencies between keys are satisfied in the local cluster before exposing writes. Further, in COPS-GT, we introduce get transactions in order to obtain a consistent view of multiple keys without locking or blocking. Our evaluation shows that COPS completes operations in less than a millisecond, provides throughput similar to previous systems when using one server per cluster, and scales well as we increase the number of servers in each cluster. It also shows that COPS-GT provides similar latency, throughput, and scaling to COPS for common workloads.SOSPdatastores/2017-09-11T23:06:29.2762561042017-09-11T23:06:29.276256104
W<0B><08>W<00>Y
s<02>u#GGHyperDex: a distributed, searchable key-value store<07>Distributed key-value stores are now a standard component of high-performance web services and cloud computing applications. While key-value stores offer significant performance and scalability advantages compared to traditional databases, they achieve these properties through a restricted API that limits object retrieval---an object can only be retrieved by the (primary and only) key under which it was inserted. This paper presents HyperDex, a novel distributed key-value store that provides a unique <b>search</b> primitive that enables queries on secondary attributes. The key insight behind HyperDex is the concept of <i>hyperspace hashing</i> in which objects with multiple attributes are mapped into a multidimensional hyperspace. This mapping leads to efficient implementations not only for retrieval by primary key, but also for partially-specified secondary attribute searches and range queries. A novel chaining protocol enables the system to achieve strong consistency, maintain availability and guarantee fault tolerance. An evaluation of the full system shows that HyperDex is 12-13x faster than Cassandra and MongoDB for finding partially specified objects. Additionally, HyperDex achieves 2-4x higher throughput for <b>get</b>/<b>put</b> operations.SIGCOMMdatastores/2017-09-11T23:06:29.9417070312017-09-11T23:06:29.941707031<EFBFBD>X
a<02>E#GGF1: A Distributed SQL Database That Scales<07>F1 is a distributed relational database system built at Google to support the AdWords business. F1 is a hybrid database that combines high availability, the scalability of NoSQL systems like Bigtable, and the consistency and us-ability of traditional SQL databases. F1 is built on Spanner , which provides synchronous cross-datacenter replica-tion and strong consistency. Synchronous replication implies higher commit latency, but we mitigate that latency by using a hierarchical schema model with structured data types and through smart application design. F1 also includes a fully functional distributed SQL query engine and automatic change tracking and publishing.PVLDBdatastores/2017-09-11T23:06:29.7776999512017-09-11T23:06:29.777699951<EFBFBD>W
U<02>5#GGModularity and Scalability in Calvin<07>Calvin is a transaction scheduling and replication management layer for distributed storage systems. By first writing transaction requests to a durable, replicated log, and then using a concurrency control mechanism that emulates a deterministic serial execution of the log's transaction requests, Calvin supports strongly consistent replication and fully ACID distributed transactions while incurring significantly lower inter-partition transaction coordination costs than traditional distributed database systems. Furthermore, Calvin's declarative specification of target concurrency-control behavior allows system components to avoid interacting with actual transaction scheduling mechanisms—whereas in traditional DBMSs, the analogous components often have to explicitly observe concurrency control modules' (highly nondeterministic) procedural behaviors in order to function correctly.IEEE Data Eng. Bull.datastores/2017-09-11T23:06:29.6923540042017-09-11T23:06:29.692354004
d<00>t\<00>
<02>+?#GGIntroduction to a System for Distributed Databases (SDD-1)<07>The declining cost of computer hardware and the increasing data processing needs of geographically dispersed organizations have led to substantial interest in distributed data management. SDD-1 is a distributed database management system currently being developed by Computer Corporation of America. Users interact with SDD-1 precisely as if it were a nondistributed database system because SDD-1 handles all issues arising from the distribution of data. These issues include distributed concurrency control, distributed query processing, resiliency to component failure, and distributed directory management. This paper presents an overview of the SDD-1 design and its solutions to the above problems.
This paper is the first of a series of companion papers on SDD-1 (Bernstein and Shipman [2], Bernstein et al. [4], and Hammer and Shipman [14]).ACM Trans. Database Syst.datastores/2017-09-11T23:06:30.2030329592017-09-11T23:06:30.203032959<EFBFBD>L[<00>-<02>a
#GGManaging Update Conflicts in Bayou, a Weakly Connected Replicated Storage System<07>Bayou is a replicated, weakly consistent storage system designed for a mobile computing environment that includes portable machines with less than ideal network connectivity. To maximize availability, users can read and write any accessible replica. Bayou's design has focused on supporting application-specific mechanisms to detect and resolve the update conflicts that naturally arise in such a system, ensuring that replicas move towards eventual consistency, and defining a protocol by which the resolution of update conflicts stabilizes. It includes novel methods for conflict detection, called dependency checks, and per-write conflict resolution based on client-provided merge procedures. To guarantee eventual consistency, Bayou servers must be able to roll-back the effects of previously executed writes and redo them according to a global serialization order. Furthermore, Bayou permits clients to observe the results of all writes received by a server, including tentative writes whose conflicts have not been ultimately resolved. This paper presents the motivation for and design of these mechanisms and describes the experiences gained with an initial implementation of the system.datastores/2017-09-11T23:06:30.1378879392017-09-11T23:06:30.137887939<EFBFBD>Z<00><02>#GGHaLoop: Efficient Iterative Data Processing on Large Clusters<07>The growing demand for large-scale data mining and data analysis applications has led both industry and academia to design new types of highly scalable data-intensive computing platforms. MapReduce and Dryad are two popular platforms in which the dataflow takes the form of a directed acyclic graph of operators. These platforms lack built-in support for iterative programs, which arise naturally in many applications including data mining, web ranking, graph analysis, model fitting, and so on. This paper presents HaLoop, a modified version of the Hadoop MapReduce framework that is designed to serve these applications. HaLoop not only extends MapReduce with programming support for iterative applications, it also dramatically improves their efficiency by making the task scheduler loop-aware and by adding various caching mechanisms. We evaluated HaLoop on real queries and real datasets. Compared with Hadoop, on average, HaLoop reduces query runtimes by 1.85, and shuffles only 4% of the data between mappers and reducers.PVLDBdatastores/2017-09-11T23:06:30.0497849122017-09-11T23:06:30.049784912
<0B>v<02><00>`
<00>

#CCMaking reliable distributed systems in the presence of software errors<07>datastores/2017-09-11T23:06:30.69747292017-09-11T23:06:30.6974729<EFBFBD>I_
9<02>//#GGOptimistic replication<07>Data replication is a key technology in distributed systems that enables higher availability and performance. This article surveys optimistic replication algorithms. They allow replica contents to diverge in the short term to support concurrent work practices and tolerate failures in low-quality communication links. The importance of such techniques is increasing as collaboration through wide-area and mobile networks becomes popular.Optimistic replication deploys algorithms not seen in traditional &#8220;pessimistic&#8221; systems. Instead of synchronous replica coordination, an optimistic algorithm propagates changes in the background, discovers conflicts after they happen, and reaches agreement on the final contents incrementally.We explore the solution space for optimistic replication algorithms. This article identifies key challenges facing optimistic replication systems---ordering operations, detecting and resolving conflicts, propagating changes efficiently, and bounding replica divergence---and provides a comprehensive survey of techniques developed for addressing these challenges.ACM Comput. Surv.datastores/2017-09-11T23:06:30.5338339842017-09-11T23:06:30.533833984<EFBFBD>{^<00><02>+/#GGMap-reduce-merge: simplified relational data processing on large clusters<07>Map-Reduce is a programming model that enables easy development of scalable parallel applications to process a vast amount of data on large clusters of commodity machines. Through a simple interface with two functions, map and reduce, this model facilitates parallel implementation of many real-world tasks such as data processing jobs for search engines and machine learning.
 However,this model does not directly support processing multiple related heterogeneous datasets. While processing relational data is a common need, this limitation causes difficulties and/or inefficiency when Map-Reduce is applied on relational operations like joins.
 We improve Map-Reduce into a new model called Map-Reduce-Merge. It adds to Map-Reduce a Merge phase that can efficiently merge data already partitioned and sorted (or hashed) by map and reduce modules. We also demonstrate that this new model can express relational algebra operators as well as implement several join algorithms.SIGMOD Conferencedatastores/2017-09-11T23:06:30.3864240722017-09-11T23:06:30.386424072<EFBFBD>	]
S<02>)#GGMDCC: Multi-Data Center Consistency<07>Replicating data across multiple data centers allows using data closer to the client, reducing latency for applications, and increases the availability in the event of a data center failure. MDCC (Multi-Data Center Consistency) is an optimistic commit protocol for geo-replicated transactions, that does not require a master or static partitioning, and is strongly consistent at a cost similar to eventually consistent protocols. MDCC takes advantage of Generalized Paxos for transaction processing and exploits commutative updates with value constraints in a quorum-based system. Our experiments show that MDCC outperforms existing synchronous transactional replication protocols, such as Megastore, by requiring only a single message round-trip in the normal operational case independent of the master-location and by scaling linearly with the number of machines as long as transaction conflict rates permit.EuroSysdatastores/2017-09-11T23:06:30.2706640622017-09-11T23:06:30.270664062

9/
9<00>sb<00><02>Y
GGNo Silver Bullet: Essence and Accidents of Software Engineering<07>All software construction involves essential tasks, the fashioning of the complex conceptual structures that compose the abstract software entity, and accidental tasks, the representation of these abstract entities in programming languages and the mapping of these onto machine languages within space and speed constraints. Most of the big past gains in software productivity have come from removing artificial barriers that have made the accidental tasks inordinately hard, such as severe hardware constraints, awkward programming languages, lack of machine time. How much of what software engineers now do is still devoted to the accidental, as opposed to the essential? Unless it is more than 9/10 of all effort, shrinking all the accidental activities to zero time will not give an order of magnitude improvement. Therefore it appears that the time has come to address the essential parts of the software task, those concerned with fashioning abstract conceptual structures of great complexity. I suggest: • exploiting the mass market to avoid constructing what can be bought. • using rapid prototyping as part of a planned iteration in establishing software require-· ments. • growing software organically, adding more and more function to systems as they are run, used, and tested. • identifying and developing the great conceptual designers of the rising generation.design/2017-09-11T23:06:30.8289689942017-09-11T23:06:30.828968994<EFBFBD>Na<00>3<02>S#GGTowards a next generation data center architecture: scalability and commoditization<07>Applications hosted in today's data centers suffer from internal fragmentation of resources, rigidity, and bandwidth constraints imposed by the architecture of the network connecting the data center's servers. Conventional architectures statically map web services to Ethernet VLANs, each constrained in size to a few hundred servers owing to control plane overheads. The IP routers used to span traffic across VLANs and the load balancers used to spray requests within a VLAN across servers are realized via expensive customized hardware and proprietary software. Bisection bandwidth is low, severly constraining distributed computation Further, the conventional architecture concentrates traffic in a few pieces of hardware that must be frequently upgraded and replaced to keep pace with demand - an approach that directly contradicts the prevailing philosophy in the rest of the data center, which is to scale out (adding more cheap components) rather than scale up (adding more power and complexity to a small number of expensive components).
 Commodity switching hardware is now becoming available with programmable control interfaces and with very high port speeds at very low port cost, making this the right time to redesign the data center networking infrastructure. In this paper, we describe monsoon, a new network architecture, which scales and commoditizes data center networking monsoon realizes a simple mesh-like architecture using programmable commodity layer-2 switches and servers. In order to scale to 100,000 servers or more,monsoon makes modifications to the control plane (e.g., source routing) and to the data plane (e.g., hot-spot free multipath routing via Valiant Load Balancing). It disaggregates the function of load balancing into a group of regular servers, with the result that load balancing server hardware can be distributed amongst racks in the data center leading to greater agility and less fragmentation. The architecture creates a huge, flexible switching domain, supporting any server/any service and unfragmented server capacity at low cost.PRESTOdatastores/2017-09-11T23:06:30.7081779792017-09-11T23:06:30.708177979
/<0C>	<09><07><05>/<00>tg
}<02>Q
5GGKafka: a Distributed Messaging System for Log Processing<07>Log processing has become a critical component of the data pipeline for consumer internet companies. We introduce Kafka, a distributed messaging system that we developed for collecting and delivering high volumes of log data with low latency. Our system incorporates ideas from existing log aggregators and messaging systems, and is suitable for both offline and online message consumption. We made quite a few unconventional yet practical design choices in Kafka to make our system efficient and scalable. Our experimental results show that Kafka has superior performance when compared to two popular messaging systems. We have been using Kafka in production for some time and it is processing hundreds of gigabytes of new data each day.distributed_systems/2017-09-11T23:06:31.4034890142017-09-11T23:06:31.403489014<EFBFBD>f
u<02>'
5GGAbove the Clouds: A Berkeley View of Cloud Computing<07>Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission.distributed_systems/2017-09-11T23:06:31.2457958982017-09-11T23:06:31.245795898<EFBFBD>]e
c<02>+5GGA simple totally ordered broadcast protocol<07>This is a short overview of a totally ordered broadcast protocol used by ZooKeeper, called Zab. It is conceptually easy to understand, is easy to implement, and gives high performance. In this paper we present the requirements ZooKeeper makes on Zab, we show how the protocol is used, and we give an overview of how the protocol works.LADIS '08distributed_systems/2017-09-11T23:06:31.1631110842017-09-11T23:06:31.163111084<EFBFBD>[d
_<02>-/#GGThe Dangers of Replication and a Solution<07>Update anywhere-anytime-anyway transactional replication has unstable behavior as the workload scales up: a ten-fold increase in nodes and traffic gives a thousand fold increase in deadlocks or reconciliations. Master copy replication (primary copy) schemes reduce this problem. A simple analytic model demonstrates these results. A new two-tier replication algorithm is proposed that allows mobile (disconnected) applications to propose tentative update transactions that are later applied to a master copy. Commutative update transactions avoid the instability of other replication schemes.SIGMOD Conferencedatastores/2017-09-11T23:06:31.0370520022017-09-11T23:06:31.037052002<EFBFBD>{c
a<02>WKGGTraits: A mechanism for fine-grained reuse<07>Inheritance is well-known and accepted as a mechanism for reuse in object-oriented languages. Unfortunately, due to the coarse granularity of inheritance, it may be difficult to decompose an application into an optimal class hierarchy that maximizes software reuse. Existing schemes based on single inheritance, multiple inheritance, or mixins, all pose numerous problems for reuse. To overcome these problems we propose <i>traits</i>, pure units of reuse consisting only of methods. We develop a formal model of traits that establishes how traits can be composed, either to form other traits, or to form classes. We also outline an experimental validation in which we apply traits to refactor a nontrivial application into composable units.ACM Trans. Program. Lang. Syst.design/2017-09-11T23:06:30.9423659672017-09-11T23:06:30.942365967

k<02><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F>~vnf^VNF>6.&<0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E>~vnf^VNF>6.&
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
~
v
n
f
^
V
N
F
>
6
.
&



<0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C>~vnf^VNF>6.&<0B><0B><0B><0B><0B><0B><0B><0B><0B><0B><0B><0B><0B>}sj`VLB8.$
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
z
p
f
\
R
H
>
4
*
 


	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	w	m	c	Y	O	E	;	2	(			
	<08><08><08><08><08><08><08><08><08><08><08><08>ukaWMC9/%<07><07><07><07><07><07><07><07><07><07><07><07><07>{qg]SI?5+!
<06><06><06><06><06><06><06><06><06><06><06><06><06>wmcYOE;1'	<05><05><05><05><05><05><05><05><05><05><05><05><05>}si_UKA7-#<04><04><04><04><04><04><04><04><04><04><04><04><04>yoe[QG=3)
<03><03><03><03><03><03><03><03><03><03><03><03>ukaWMC9/%<02><02><02><02><07>k

Gc<07>j

Fc<07>i

Eb<07>h

Db<07>g

Cb<07>f

Bb<07>e

Ab<07>d

@b<07>c

?b<07>b

>b<07>a

=b<07>`

<a<07>_

;a<07>^

:a<07>]

9a<07>\

8a<07>[

7_<07>Z

6_<07>Y

_<07>X

5_<07>W

4_<07>V

3^<07>U

2^<07>T

1^<07>S

0^<07>R

^<07>Q

]<07>P

/]<07>O

.]<07>N

-]<07>M

,]<07>L

+\<07>K
<00>\<07>J

*\<07>I

)Z<07>H

(Z<07>G

'Z<07>F

&Z<07>E

%Z<07>D

$Y<07>C

#Y<07>B

"Y<07>A

!Y<07>@

 Y<07>?

X<07>>

X<07>=

X<07><
<00>X<07>;

X<07>:

W<07>9

W<07>8

W<07>7
<00>W<07>6

W<07>5

U<07>4

U<07>3

U<07>2

U<07>1

U<07>0

S<07>/

S<07>.

S<07>-

S<07>,

S<07>+
<00>R<07>*

R<07>)
<00>R<07>(
<00>R<07>'
<00>R<07>&


Q<07>%

Q<07>$

Q<07>#


Q<07>"

	Q<07>!

O<07> 

O<07>
<00>O<07>
<00>O<07>
<00>O<07>

N<07>

N<07>

N<07>

N<07>
<00>N<07>

N<07>


N<07>

N<07>
<00>N<07>
<00>N<07>
<00>M<07>
<00>L<07>
<00>L<07>
<00>L<07>
<00>L<07>

<00>L<07>
<00>K<07>
<00>K<07>

<00>K<07>	
<00>K<07>
<00>K<07>
<00>J<07>
<00>J<07>
<00>J<07>
<00>J<07>
<00>J<07>
<00>H<07>

<00>F<07>
<00>F<07>
<00>F<07>~
<00>F<07>}
<00>F<07>|
<00>E<07>{
<00>E<07>z
<00>E<07>y
<00>E<07>x
<00>E<07>w
<00>D<07>v
<00>D<07>u
<00>D<07>t
<00>D<07>s
<00>D<07>r
<00>B<07>q
<00>B<07>p
<00>B<07>o
<00>B<07>n
<00>B<07>m
<00>A<07>l
<00>@<07>k
<00>@<07>j
<00>@<07>i
<00>@<07>h
<00>@<07>g
<00>?<07>f
<00>?<07>e
<00>?<07>d
<00>?<07>c
<00>?<07>b
<00>?<07>a
<00>?<07>`
<00>?<07>_
<00>?<07>^
<00>?<07>]
<00>><07>\
<00>><07>[
<00>><07>Z
<00>><07>Y
<00>><07>X
<00>=<07>W
<00>=<07>V
<00>=<06>U

v=<07>T
<00>=<07>S
<00><<07>R
<00><<07>Q
<00><<07>P
<00><<07>O
<00><<07>N
<00><<07>M
<00><<07>L
<00><<07>K
<00><<07>J
<00>:<06>I

:<07>H
<00>:<07>G
<00>:<07>F
<00>:<07>E
<00>9<07>D
<00>9<07>C
<00>9<07>B
<00>9<07>A
<00>9<07>@
<00>8<07>?
<00>8<07>>
<00>8<07>=
<00>8<07><
<00>8<07>;
<00>7<06>:

7<07>9
<00>6<07>8
<00>6<07>7
<00>6<07>6
<00>6<07>5
<00>6<07>4
<00>5<07>3
<00>5<07>2
<00>5<07>1
<00>5<07>0
<00>4<07>/
<00>4<07>.
<00>4<07>-
<00>4<07>,
<00>4<07>+
<00>3<07>*
<00>3<07>)
<00>3<07>(
<00>3<07>'
<00>2<07>&
<00>2<07>%
<00>2<07>$
<00>2<07>#
<00>2<07>"
<00>1<07>!
<00>1<07> 
<00>1<07>
<00>1<07>
<00>1<07>
<00>0<07>
<00>0<07>
<00>0<07>
<00>0<07>
<00>0<07>
<00>*<07>
<00>*<07>
<00>*<07>
<00>*<07>
<00>*<07>
<00>(<07>
<00>(<07>
<00>(<06>

r(<07>
<00>(<07>
<00>'<07>

<00>'<07>
<00>'<07>
<00>'<07>

<00>'<07>	
<00>&<07>
<00>&<07>
<00>&<07>
<00>&<06>

c&<07>
<00>%<06>

%<06>

~%<06>


}$<06>

|$

{$~

z$}

y$|

x#{

w#z

v#y

u#x

t#w

s"v

r"u

q"t

p"s

o"r

n q

m p

l o

k n

j m

i l

h k

g j

fi

eh

dg

cf

be

ad

`c

_b

^a

]`

\_

[^

Z]

Y\

X[

WZ

VY

UX

TW

SV

RU

QT

PS

OR

NQ

MP

LO

KN

JM

IL

HK

GJ

FI

EH

DG

CF

BE

AD

@C

?B

>A

=@

<?

;
>

:
=

9
<

8
;

7
:

69

58

47

36

25

1
4

0
3

/
2

.
1

-
0

,	/

+	.

*	-

)	,

(	+

'*

)

&(

%'

$&

#%

"$

!#

 "

!

 

















































	

	






	
	
	
	
		

D<02><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F>~tj`VLB9/%<0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E>|rh^TJ@6,"
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
x
n
d
Z
P
F
<
2
(



<0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C>~tj`VLB8.$<0B><0B><0B><0B><0B><0B><0B><0B><0B><0B><0B><0B><0B>zpf\RH>4)
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
y
n
c
X
M
B
7
,
!


	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	|	q	f	[	P	E	:	/	$			<08><08><08><08><08><08><08><08><08><08><08>ti^SH=2'<07><07><07><07><07><07><07><07><07><07><07><07>wlaVK@5*	<06><06><06><06><06><06><06><06><06><06><06><06>zodYNC8-"
<05><05><05><05><05><05><05><05><05><05><05>}rg\QF;0%<04><04><04><04><04><04><04><04><04><04><04><04>vk`UJ?4)<03><03><03><03><03><03><03><03><03><03><03><03>yncXMB7,!
<02><02><02><02><02><02><02><02><02><02><08>/G<00><08>.F<00><08>-E<00><08>,D<00><08>+<00><00><08>*
<01><00><08>)C<00><07>(
w<00><08>'B<00><08>&A<00><08>%@<00><07>$
b<00><08>#?<00><08>"><00><08>!=<00><08> <<00><08>;<00><08>:<00><08>9<00><08>8<00><08>7<00><08>6<00><08>5<00><08>4<00><08>3<00><08>2<00><08>1<00><08>0<00><08>/<00><08>
<01><00><08>.<00><08>-<00><08>,<00><08>+<00><08>
*<00><08>)<00><08>(<00><08>
'<00><08>	&<00><08><00><00><08><00><00><08>%<00><08><00><00><08>$<00><07>
N<00><08>#<00><08>
"<00><08>
#<00><08>!<00><08>~ <00><08>}<00><08>|<00><08>{<00><08>z<00><08>y<00><08>x<00><08>w<00><08>v<00><08>u<00><08>t<00><08>s<00><08>r<00><08>q<00><08>p<00><08>o<00><08>n<00><08>m<00><08>l<00><08>k
<00><08>j<00><08>i<00><08>h
<00><08>g	<00><08>f<00><08>e<00><08>d<00><08>c<00><08>b<00><08>a<00><08>`<00><08>_
<00><08>^
Y<00><08>]
<01><00><08>\<00><08>[
<01><00><08>Z
<01><00><08>Y
<01><00><08>X
<01><00><08>W
<01><00><08>V
<01><00><08>U
<01><00><08>T
<01><00><08>S
<01><00><08>R
<01><00><08>Q
<01><00><08>P
<01><00><08>O
<01><00><08>N
<01><00><08>M
Y<00><08>L
<01><00><08>K
<01><00><08>J
<01><00><08>I
<01><00><08>H
<01><00><08>G
<01><00><08>F
<01><00><08>E
<01><00><08>D
Y<00><08>C
<01><00><08>B
<01><00><08>A
<01><00><08>@
<01><00><08>?
<01><00><08>>
<01><00><08>=
<01><00><08><
<01><00><08>;
_<00><08>:
<01><00><08>9
<01><00><08>8
<01><00><08>7
<01><00><08>6<00><00><08>5
%<00><08>4
<01><00><08>3
<01><00><08>2
<01><00><08>1
<01><00><08>0
<01><00><08>/
<01><00><08>.
<01><00><08>-
<01><00><08>,
<01><00><08>+
<01><00><08>*
<01><00><08>)
<01><00><08>(
<01><00><08>'<00><00><08>&
<01><00><08>%
<01><00><08>$
<01><00><08>#
<01><00><08>"
<01><00><08>!
<01><00><08> 
<01><00><08>
<01><00><08>
<01><00><08>
<01><00><08>
<01><00><08>
<01><00><08>
<01><00><08>
<01><00><08>
<01><00><08>
<01><00><08>
<01><00><08>
<01><00><08>
<01><00><08>
<01><00><08>
<01><00><08>
<01><00><08>
<01><00><08>
<01><00><08>
<01><00><08>

<01><00><08>
<01><00><08>
<01><00><08>

<01><00><08>	
<01><00><08>
<01><00><08>
<01><00><08>
<01><00><08>
<01><00><08>
<01><00><08>
<01><00><08>
<01><00><08>

<01><00><08>
<01><00><08>
<01><00><08>~
<01><00><08>}
<01><00><08>|
<01><00><08>{
<01><00><08>z<00><00><08>y
;<00><08>x
<01><00><08>w
<01><00><08>v
<01><00><08>u
<01><00><08>t
<01><00><08>s
<00><08>r<00><00><08>q
<01><00><08>p
<01><00><08>o
<01><00><08>n
<01><00><08>m
<01><00><08>l
<01><00><08>k<00><00><08>j
<01><00><08>i
<01><00><08>h
<01><00><08>g
<01><00><07>f

<01><07>e

<01><07>d

<01><07>c

<01><07>b

<01><07>a

<01>~<07>`

<01>~<07>_

<01>~<07>^

<01>~<07>]

<01>}<07>\

<01>}<07>[

<01>}<07>Z

<01>}<07>Y

<01>}<07>X

|<07>W

|<07>V

<01>|<07>U
<00>|<07>T

<01>|<07>S
<00>{<07>R

<01>{<07>Q

<01>{<07>P

<01>{<07>O

<01>{<07>N

<01>z<07>M

<01>z<07>L

<01>z<07>K

<01>z<07>J
<00>z<07>I

<01>y<07>H

<01>y<07>G

<01>y<07>F

<01>y<07>E

<01>y<07>D

<01>x<07>C

<01>x<07>B

x<07>A

qx<07>@

.x<07>?

<01>w<07>>

<01>w<07>=

Yw<07><

<01>w<07>;

<01>w<07>:

<01>v<07>9

<01>v<07>8

jv<07>7

<01>v<07>6

v<07>5

~u<07>4

}t<07>3

t<07>2
<00>t<07>1

|t<07>0

{t<07>/

zs<07>.

ys<07>-

xs<07>,

ws<07>+

vs<07>*

ur<07>)

tr<07>(

sr<07>'

=r<07>&
<00>r<07>%

q<07>$

rq<07>#

qq<07>"

pq<07>!

oq<07> 

p<07>

p<07>
<00>p<07>

np<07>

mp<07>

^n<07>

ln<07>

kn<07>

jn<07>

]n<07>

_m<07>

im<07>

hm<07>

gm<07>

fm<07>

ek<07>

dk<07>

ck<06>

dk<07>


bk<07>

j<07>
<00>j<07>


aj<07>	
<00>j<07>

`j<07>

_i<07>

^i<07>

]i<07>

\i<07>

i<07>

[h<07>


Zh<07>

Yh<06>

h<07>~

Xh<07>}

Wg<07>|

Vg<07>{

Ug<07>z

Tg<07>y

Sg<07>x

Rf<07>w

Qf<07>v

Pf<07>u

Of<07>t

Nf<07>s

Md<07>r

d<07>q
<00>d<07>p

Ld<07>o

Kd<07>n

Jc<07>m

Ic<07>l

Hc
<03><07><03><00>"j<00><02>_K5GGLinearizability: A Correctness Condition for Concurrent Objects<07>A concurrent object is a data object shared by concurrent processes. Linearizability is a correctness condition for concurrent objects that exploits the semantics of abstract data types. It permits a high degree of concurrency, yet it permits programmers to specify and reason about concurrent objects using known techniques from the sequential domain. Linearizability provides the illusion that each operation applied by concurrent processes takes effect instantaneously at some point between its invocation and its response, implying that the meaning of a concurrent object's operations can be given by pre- and post-conditions. This paper defines linearizability, compares it to other correctness conditions, presents and demonstrates a method for proving the correctness of implementations, and shows how to reason about concurrent objects, given they are linearizable.ACM Trans. Program. Lang. Syst.distributed_systems/2017-09-11T23:06:31.7390190432017-09-11T23:06:31.739019043<EFBFBD>oi
q<02>E5GGLarge-scale cluster management at Google with Borg<07>Google's Borg system is a cluster manager that runs hundreds of thousands of jobs, from many thousands of different applications, across a number of clusters each with up to tens of thousands of machines.
 It achieves high utilization by combining admission control, efficient task-packing, over-commitment, and machine sharing with process-level performance isolation. It supports high-availability applications with runtime features that minimize fault-recovery time, and scheduling policies that reduce the probability of correlated failures. Borg simplifies life for its users by offering a declarative job specification language, name service integration, real-time job monitoring, and tools to analyze and simulate system behavior.
 We present a summary of the Borg system architecture and features, important design decisions, a quantitative analysis of some of its policy decisions, and a qualitative examination of lessons learned from a decade of operational experience with it.EuroSysdistributed_systems/2017-09-11T23:06:31.6130800782017-09-11T23:06:31.613080078<EFBFBD>_h<00><02>y5GGChord: A scalable peer-to-peer lookup service for internet applications<07>A fundamental problem that confronts peer-to-peer applications is to efficiently locate the node that stores a particular data item. This paper presents <i>Chord</i>, a distributed lookup protocol that addresses this problem. Chord provides support for just one operation: given a key, it maps the key onto a node. Data location can be easily implemented on top of Chord by associating a key with each data item, and storing the key/data item pair at the node to which the key maps. Chord adapts efficiently as nodes join and leave the system, and can answer queries even if the system is continuously changing. Results from theoretical analysis, simulations, and experiments show that Chord is scalable, with communication cost and the state maintained by each node scaling logarithmically with the number of Chord nodes.SIGCOMMdistributed_systems/2017-09-11T23:06:31.4608430182017-09-11T23:06:31.460843018
i<00><0F><0F><0F>uU5<0E><0E><0E><0E>qM/
<0A>
<0A>
<0A>
h
>
<0C><0C><0C><0C>[3
<0B><0B><0B><0B>oF
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
o
A
	<09>	<09>	<09>	s	B	 <08><08><08><08>_6
<07><07><07>wY9<06><06><06>|Z8<05><05><05><05>nB<04><04><04><04>uN0<03><03><03><03>`8<02><02><02><02>]A
<01>
<01>
<01>
q
E
<00>*<2A>03R. Ha-Vinh LeuchterR.Ha-VinhLeuchter)<29>/1
+C. Borradori-TolsaC.Borradori-Tolsa)<29>.1
François LazeyrasFrançoisLazeyras0<73>-9Manon J. N. L. BendersManonJ. N. L.Benders!<21>,)
Jessica DuboisJessicaDubois<19>+!
Mark KleinMarkKlein8<6E>*A1Juan A. Rodríguez-AguilarJuanA.Rodríguez-Aguilar<1F>)'
Simon ParsonsSimonParsons<19>(!
Brian ZillBrianZill*<2A>'3Srinath T. V. SettySrinathT. V.Setty(<28>&1Michael L. RobertsMichaelL.Roberts<1B>%#
Bryan ParnoBryanParno <20>$)Jacob R. LorchJacobR.Lorch#<23>#+
Manos KapritsosManosKapritsos<19>"!
Jon HowellJonHowell%<25>!-
!Chris HawblitzelChrisHawblitzel<1F> '
Changhoon KimChanghoonKim%<25>-
Srikanth KandulaSrikanthKandula<1D>%
Navendu JainNavenduJain&<26>/James R. HamiltonJamesR.Hamilton<1C>%Brian M. OkiBrianM.Oki<1B>#
David ChaumDavidChaum<1B>#
Miron LivnyMironLivny$<24>-Michael J. CareyMichaelJ.Carey<1F>'
Jon CrowcroftJonCrowcroft<1B>#
Steven HandStevenHand<1D>%
Steven SmithStevenSmith'<27>/
!Thomas GazagnaireThomasGazagnaire<1D>%
Balraj SinghBalrajSingh <20>)David J. ScottDavidJ.Scott)<29>1#
Charalampos RotsosCharalamposRotsos#<23>+
Richard MortierRichardMortier'<27>/
%Anil MadhavapeddyAnilMadhavapeddy<19>!
Ning ZhangNingZhang<17>
Chao YangChaoYang<1F>
'
Gintaras WossGintarasWoss<1F>'
Guanghao ShenGuanghaoShen<1F>'
Sriram SankarSriramSankar<1F>
'
Philip ProninPhilipPronin$<24>	-Søren B. LassenSørenB.Lassen%<25>-
Sandhya KunnaturSandhyaKunnatur<1B>#
Tom JacksonTomJackson#<23>+
Lucian GrijincuLucianGrijincu'<27>/
!Sergey DoroshenkoSergeyDoroshenko<1D>%
Tudor BosmanTudorBosman<1B>#
Iain BeckerIainBecker#<23>+
Michael CurtissMichaelCurtiss<1F>
'
Iulian MoraruIulianMoraru%<25>-
Georges GonthierGeorgesGonthier#<23>+
Cédric FournetCédricFournet&<26>~/Marshall C. PeaseMarshallC.Pease&<26>}/Robert E. ShostakRobertE.Shostak#<23>|+
Michael BurrowsMichaelBurrows#<23>{+
Patrick WendellPatrickWendell!<21>z)
!Kay OusterhoutKayOusterhout#<23>y+
David MazièresDavidMazières(<28>x1Yifeng Frank HuangYifengFrankHuang<1F>w'
Andrea BittauAndreaBittau.<2E>v7#Ali José MashtizadehAliJoséMashtizadeh2<68>u;#Christos T. KaramanolisChristosT.Karamanolis(<28>t1Alistair C. VeitchAlistairC.Veitch<1E>s'Mehul A. ShahMehulA.Shah<1F>r'
Arif MerchantArifMerchant(<28>q1Marcos K. AguileraMarcosK.Aguilera+<2B>p3
!Grzegorz CzajkowskiGrzegorzCzajkowski<1B>o#
Naty LeiserNatyLeiser<17>n
Ilan HornIlanHorn$<24>m-James C. DehnertJamesC.Dehnert <20>l)Aart J. C. BikAartJ. C.Bik(<28>k1Matthew H. AusternMatthewH.Austern'<27>j/
Grzegorz MalewiczGrzegorzMalewicz&<26>i/Samuel C. KendallSamuelC.Kendall<1D>h%
Ann WollrathAnnWollrath<1B>g#
Geoff WyantGeoffWyant<17>f
Jim WaldoJimWaldo!<21>e)
Barbara LiskovBarbaraLiskov<1F>d'
Miguel CastroMiguelCastro#<23>c+
Joshua RedstoneJoshuaRedstone%<25>b-
Robert GriesemerRobertGriesemer.<2E>a7Tushar Deepak ChandraTusharDeepakChandra<1F>`'
Jorgen ThelinJorgenThelin<1F>_'
Gabriel KliotGabrielKliot<1B>^#
Alan GellerAlanGeller<1D>]%
Sergey BykovSergeyBykov-<2D>\5
%Michael Abd-El-MalekMichaelAbd-El-Malek'<27>[/
#Malte SchwarzkopfMalteSchwarzkopf <20>Z)Paul R. WilsonPaulR.Wilson&<26>Y/Robert D. BlumofeRobertD.Blumofe*<2A>X3Kathryn S. MckinleyKathrynS.Mckinley"<22>W+Emery D. BergerEmeryD.Berger&<26>V/Fred B. SchneiderFredB.Schneider<1B>U#
Sam WhittleSamWhittle!<21>T)
Paul NordstromPaulNordstrom<1D>S%
Daniel MillsDanielMills<1B>R#
Sam McveetySamMcveety<19>Q!
Reuven LaxReuvenLax<1F>P'
Josh HabermanJoshHaberman!<21>O)
Slava ChernyakSlavaChernyak!<21>N)
Kaya BekirogluKayaBekiroglu<1D>M%
Alex BalikovAlexBalikov<1D>L%
Tyler AkidauTylerAkidau&<26>K/Jeannette M. WingJeannetteM.Wing<1B>J#
John WilkesJohnWilkes<17>I
Eric TuneEricTune'<27>H/
#David OppenheimerDavidOppenheimer

k<02><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F>zrjc[SKC;3+#<0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E>{skd\UNF>6.&
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
~
v
n
f
^
V
N
F
>
6
.
&



<0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C>~vnf^VNF>6.&<0B><0B><0B><0B><0B><0B><0B><0B><0B><0B><0B><0B><0B><0B>wmcYOE;1'	
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
}
s
i
_
U
K
A
7
-
#


	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	y	o	e	[	Q	G	=	3	)				
<08><08><08><08><08><08><08><08><08><08><08><08>ukaWMC9/%<07><07><07><07><07><07><07><07><07><07><07><07><07>{qg]SI?5+!
<06><06><06><06><06><06><06><06><06><06><06><06><06>wmcYOE;1'	<05><05><05><05><05><05><05><05><05><05><05><05><05>}si_UKA7-#<04><04><04><04><04><04><04><04><04><04><04><04><04>yoe[QG=3)<03><03><03><03><03><03><03><03><03><03><03><03><03>vlbXND:0&<02><02><02><02><07>k

Ji<07>j

Ii<07>i

Hi<07>h

Gi<07>g

Fi<07>f

Ei<07>e

Dh<07>d

Ch<07>c

Bh<07>b

Ah<07>a

9h<07>`

@g<07>_

?g<07>^

>g<07>]

=f<07>\

<f<07>[

;f<07>Z

:f<07>Y

9f<07>X

8f<07>W

7f<07>V

6f<07>U

5f<07>T

4f<07>S

3f<07>R

2f<07>Q
<00>f<07>P

1f<07>O

0e<07>N

/e<06>M

Md<07>L

.d<07>K
<00>d<07>J

-d<07>I

,c<07>H

+c<07>G

*c<07>F

)c<07>E

(c<07>D

'b<07>C

&a<07>B

%a<07>A

$a<07>@

#a<07>?

"a<07>>

!`<07>=

 _<07><

_<07>;

^<07>:

^<07>9

^<07>8

^<07>7

]<07>6

]<07>5

]<07>4

]<07>3

\<07>2

\<07>1

\<07>0

\<07>/

\<07>.

\<07>-

\<07>,

\<07>+

\<07>*


Z<07>)

Z<07>(

Z<07>'


Z<07>&

	Y<07>%

Y<07>$

Y<07>#

X<07>"

X<07>!

X<07> 

X<07>

X<07>


X<07>

X<07>
<00>X<07>
<00>X<07>
<00>X<07>
<00>X<07>
<00>X<07>
<00>X<07>
<00>X<07>
<00>W<07>
<00>W<07>
<00>V<07>
<00>U<07>
<00>U<07>
<00>U<07>
<00>U<07>
<00>U<07>

<00>U<07>
<00>U<07>
<00>T<07>

<00>T<07>	
<00>T<07>
<00>T<07>
<00>S<07>
<00>S<07>
<00>S<07>
<00>S<07>
<00>R<07>
<00>R<07>

<00>R<07>
<00>Q<07>
<00>Q<07>~
<00>O<07>}
<00>O<07>|
<00>N<07>{
<00>N<07>z
<00>N<07>y
<00>N<07>x
<00>N<07>w
<00>N<07>v
<00>M<07>u
<00>M<07>t
<00>M<07>s
<00>M<07>r
<00>M<07>q
<00>M<07>p
<00>M<07>o
<00>M<07>n
<00>M<07>m
<00>M<07>l
<00>M<07>k
<00>L<07>j
<00>K<07>i
<00>K<07>h
<00>K<07>g
<00>J<07>f
<00>J<07>e
<00>I<07>d
<00>I<07>c
<00>H<07>b
<00>G<07>a
<00>F<07>`
<00>F<07>_
<00>F<07>^
<00>F<07>]
<00>E<07>\
<00>E<07>[
<00>D<07>Z
<00>C<07>Y
<00>C<07>X
<00>C<07>W
<00>B<07>V
<00>B<07>U
<00>A<07>T
<00>@<07>S
<00>@<07>R
<00>?<07>Q
<00>?<07>P
<00>?<07>O
<00>><07>N
<00>=<07>M
<00>=<07>L
<00>=<07>K
<00>=<07>J
<00>=<07>I
<00><<07>H
<00><<07>G
<00>;<07>F
<00>;<07>E
<00>;<07>D
<00>:<07>C
<00>:<07>B
<00>:<07>A
<00>9<07>@
<00>9<07>?
<00>9<07>>
<00>9<07>=
<00>9<07><
<00>9<07>;
<00>9<07>:
<00>9<07>9
<00>8<07>8
<00>8<07>7
<00>8<07>6
<00>8<07>5
<00>8<07>4
<00>8<07>3
<00>8<07>2
<00>7<07>1
<00>7<07>0
<00>7<07>/
<00>6<07>.
<00>6<07>-
<00>6<07>,
<00>5<07>+
<00>5<07>*
<00>5<07>)
<00>4<07>(
<00>4<07>'
<00>4<07>&
<00>4<07>%
<00>4<07>$
<00>3<07>#
<00>3<07>"
<00>3<07>!
<00>3<07> 
<00>3<07>
<00>3<07>
<00>3<07>
<00>2<07>
<00>2<07>
<00>2<07>
<00>2<07>
<00>2<07>
<00>1<07>
<00>1<07>
<00>0<07>
<00>0<07>
<00>0<07>
<00>0<07>
<00>/<07>
<00>/<07>
<00>.<07>
<00>-<07>
<00>-<07>

<00>-<07>
<00>,<07>
<00>,<07>

<00>+<07>	
<00>*<06>

*<06>

~)<06>

})<06>

|)<06>

{(<06>

z'<06>

y'<06>


x&<06>

w&

v&~

u&}

t&|

s&{

r&z

q&y

p&x

o&w

n&v

m%u

l%t

k%s

j$r

i$q

h$p

g$o

f$n

e#m

d#l

c#k

b"j

a!i

` h

_g

^f

]e

\d

[c

Zb

Ya

X`

W_

V^

U]

T\

S[

RZ

QY

PX

OW

NV

MU

LT

KS

JR

IQ

HP

GO

FN

EM

DL

CK

BJ

AI

@H

?G

>F

=E

<D

;C

:B

9A

8@

7?

6>

5=

4<

3;

2:

19

08

/7	

6	
5

.4	
3

-
2

,
1

+
0

*
/

)
.

(
-

'
,

&
+

%
*

$
)

#
(

"
'

!
&

 
%


$


#


"


!


 




	

	

















	




















	



	

	














		

A<02><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F>~tj`VLB8.$<0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E>zpf\RH>4* 
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
v
l
b
X
N
D
:
0
&


<0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C>|rh^TJ?4)<0B><0B><0B><0B><0B><0B><0B><0B><0B><0B><0B><0B>yncXMB7,!
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
|
q
f
[
P
E
:
/
$


	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>		t	i	^	S	H	=	2	'			<08><08><08><08><08><08><08><08><08><08><08><08>wlaVK@5*	<07><07><07><07><07><07><07><07><07><07><07><07>zodYNC8-"
<06><06><06><06><06><06><06><06><06><06><06>}rg\QF;0%<05><05><05><05><05><05><05><05><05><05><05><05>uj_TI>3(<04><04><04><04><04><04><04><04><04><04><04><04>xmbWLA6+ 
<03><03><03><03><03><03><03><03><03><03><03><03>{peZOD9.#
<02><02><02><02><02><02><02><02><02><02><08>,`<00><08>+_<00><08>*^<00><08>)]<00><08>(
<01><00><08>'
<01><00><08>&\<00><08>%[<00><08>$Z<00><08>#Y<00><08>"X<00><08>!W<00><08> V<00><08>U<00><08>T<00><08>S<00><08>R<00><08>Q<00><08>P<00><08>O<00><08>N<00><08>M<00><08>L<00><08>K<00><08>J<00><08>I<00><08>H<00><08>G<00><08>F<00><08>E<00><08>D<00><08>
C<00><08>B<00><08>A<00><08>
@<00><08>	?<00><08>><00><08>=<00><08><<00><08>;<00><08>
<01><00><08>
<01><00><08><00><00><08>
<00><00><08>:<00><08>9<00><08>~8<00><08>}7<00><08>|6<00><08>{5<00><08>z4<00><08>y3<00><08>x2<00><08>w1<00><08>v0<00><08>u/<00><08>t.<00><08>s-<00><08>r,<00><08>q+<00><08>p*<00><08>o)<00><08>n(<00><08>m'<00><08>l&<00><08>k%<00><08>j$<00><08>i#<00><08>h"<00><08>g!<00><08>f <00><08>e<00><08>d<00><08>c<00><08>b<00><08>a<00><08>`<00><08>_<00><08>^<00><08>]<00><08>\<00><08>[<00><08>Z<00><08>Y<00><08>X<00><08>W<00><00><08>V<00><08>U<00><08>T
<01><00><08>S<00><00><08>R<00><08>Q
!<00><08>P<00><08>O
<00><08>N<00><08>M<00><08>L
<00><08>K	<00><08>J<00><08>I<00><00><08>H<00><00><08>G<00><08>F<00><00><08>E<00><08>D<00><08>C<00><08>B<00><08>A<00><08>@
<00><08>?<00><08>>
<01><00><08>=
<01><00><08><
<01><00><08>;
<01><00><08>:
<01><00><08>9
<01><00><08>8
<01><00><08>7
<01><00><08>6
<01><00><08>5
<01><00><08>4
<01><00><08>3
<01><00><08>2
<01><00><08>1
<01><00><08>0
<01><00><08>/
<01><00><08>.
<01><00><08>-
<01><00><08>,
<01><00><08>+
<01><00><08>*
<01><00><08>)
<01><00><08>(
<01><00><08>'
<01><00><08>&
<01><00><08>%
<01><00><08>$
<01><00><08>#
<01><00><08>"
<01><00><08>!
<01><00><08> 
<01><00><08><00><00><08>
<01><00><08>
<01><00><08>
<01><00><08>
<01><00><08>
<01><00><08>
<01><00><08>
<01><00><08>
<01><00><08>
<01><00><08>
<01><00><08>
<01><00><08>
<01><00><08>
<01><00><08>
<01><00><08>
<01><00><08>
<01><00><08>
<01><00><08>

<01><00><08>
<01><00><08>
<01><00><08>

<01><00><08>	
<01><00><08>
<01><00><08>
<01><00><08>
<01><00><08>
<01><00><08>
<01><00><08>
<01><00><08>
<01><00><08>

<01><00><08>
<01><00><08>
<01><00><08>~
<01><00><08>}
<01><00><08>|
<01><00><08>{
<01><00><08>z
<01><00><08>y
<01><00><08>x
<01><00><08>w
<01><00><08>v
<01><00><08>u
<01><00><08>t
<01><00><08>s
<01><00><08>r
<01><00><08>q
<01><00><08>p
<01><00><08>o
<01><00><08>n
<01><00><08>m
<01><00><08>l
<01><00><08>k
<01><00><08>j
<01><00><08>i
<01><00><08>h
<01><00><08>g
<01><00><08>f
<01><00><08>e
<01><00><08>d
<01><00><08>c
<01><00><08>b
<01><00><08>a
<01><00><08>`
<01><00><08>_
<01><00><08>^
<01><00><08>]
<01><00><08>\
<01><00><08>[
<01><00><08>Z
<01><00><08>Y
<01><00><08>X
<01><00><08>W
<01><00><08>V
&<00><08>U
%<00><08>T
$<00><08>S
#<00><08>R
<01><00><08>Q
<01><00><08>P
<01><00><08>O
<01><00><08>N
"<00><08>M
e<00><08>L
<01><00><08>K
<01><00><07>J

<01><07>I

<01><07>H

<07>G

<01>~<07>F

<01>~<07>E

<01>~<07>D

<01>~<07>C

<01>~<07>B

<01>~<07>A

<01>~<07>@

<01>~<07>?

<01>~<07>>

<01>}<07>=

<01>}<07><

<01>}<07>;

<01>}<07>:

<01>}<07>9

<01>}<07>8

<01>}<07>7

<01>}<07>6

<01>}<07>5

<01>}<07>4

<01>}<07>3

<01>}<07>2

<01>}<07>1

<01>}<07>0
<00>|<07>/
<00>|<07>.

<01>|<07>-
<00>{<07>,

<01>z<07>+

z<07>*

~y<07>)

}y<07>(
<00>y<07>'

|x<07>&

Aw<07>%

Cw<07>$

Dw<07>#
<00>w<07>"

9v<07>!

:v<07> 

{v<07>

zv<07>

yu<07>

xu<07>

wu<07>

vu<07>

ut<07>

tt<07>

st<07>

rt<07>

qt<07>

ps<07>

os<07>

ns<07>

ms<07>

ls<07>

ks<07>

js<07>

ir<07>


hr<07>

gr<07>

fr<07>


eq<07>	

dq<07>

cp<07>

bp<07>

ap<07>

`o<07>

_o<07>

^o<07>

]o<07>


o<07>

Jn<07>

\n<07>~

<n<07>}

[n<07>|

Zm<07>{

Ym<07>z

Xm<07>y

Wm<07>x

Vl<07>w

Uk<07>v

Tk<07>u

Sk<07>t

Rk<07>s

Qk<07>r

Pk<07>q

Ok<07>p

Nk<07>o

Mk<07>n

Lk<07>m

Kj<07>l
<00>j
<03><0B>	<09><03><00>
m<00><02>]5GGHoard: A Scalable Memory Allocator for Multithreaded Applications<07>Parallel, multithreaded C and C++ programs such as web servers, database managers, news servers, and scientific applications are becoming increasingly prevalent. For these applications, the memory allocator is often a bottleneck that severely limits program performance and scalability on multiprocessor systems. Previous allocators suffer from problems that include poor performance and scalability, and heap organizations that introduce false sharing. Worse, many allocators exhibit a dramatic increase in memory consumption when confronted with a producer-consumer pattern of object allocation and freeing. This increase in memory consumption can range from a factor of <i>P</i> (the number of processors) to unbounded memory consumption.This paper introduces Hoard, a fast, highly scalable allocator that largely avoids false sharing and is memory efficient. Hoard is the first allocator to simultaneously solve the above problems. Hoard combines one global heap and per-processor heaps with a novel discipline that provably bounds memory consumption and has very low synchronization costs in the common case. Our results on eleven programs demonstrate that Hoard yields low average fragmentation and improves overall program performance over the standard Solaris allocator by up to a factor of 60 on 14 processors, and up to a factor of 18 over the next best allocator we tested.ASPLOSdistributed_systems/2017-09-11T23:06:32.0108491212017-09-11T23:06:32.010849121<EFBFBD>l<00>/<02>O/5GGImplementing Fault-Tolerant Services Using the State Machine Approach: A Tutorial<07>The state machine approach is a general method for implementing fault-tolerant services in distributed systems. This paper reviews the approach and describes protocols for two different failure models&#8212;Byzantine and fail stop. Systems reconfiguration techniques for removing faulty components and integrating repaired components are also discussed.ACM Comput. Surv.distributed_systems/2017-09-11T23:06:32.0013259282017-09-11T23:06:32.001325928<EFBFBD>@k<00><02>S5GGMillWheel: Fault-Tolerant Stream Processing at Internet Scale<07>MillWheel is a framework for building low-latency data-processing applications that is widely used at Google. Users specify a directed computation graph and application code for individual nodes, and the system manages persistent state and the continuous flow of records, all within the envelope of the framework's fault-tolerance guarantees. This paper describes MillWheel's programming model as well as its implementation. The case study of a continuous anomaly detector in use at Google serves to motivate how many of MillWheel's features are used. MillWheel's programming model provides a notion of logical time, making it simple to write time-based aggre-gations. MillWheel was designed from the outset with fault tolerance and scalability in mind. In practice, we find that MillWheel's unique combination of scalability, fault tolerance, and a versatile programming model lends itself to a wide variety of problems at Google.PVLDBdistributed_systems/2017-09-11T23:06:31.9035219732017-09-11T23:06:31.903521973
<05>m<07><05>
c<02>y5EEPaxos made live: an engineering perspective<07>We describe our experience in building a fault-tolerant data-base using the Paxos consensus algorithm. Despite the existing literature in the field, building such a database proved to be non-trivial. We describe selected algorithmic and engineering problems encountered, and the solutions we found for them. Our measurements indicate that we have built a competitive system.PODCdistributed_systems/2017-09-11T23:06:32.265479982017-09-11T23:06:32.26547998<EFBFBD>Xo<00><02>y
5GGOrleans: Distributed Virtual Actors for Programmability and Scalability<07>High-scale interactive services demand high throughput with low latency and high availability, difficult goals to meet with the traditional stateless 3-tier architecture. The actor model makes it natural to build a stateful middle tier and achieve the required performance. However, the popular actor model platforms still pass many distributed systems problems to the developers. The Orleans programming model introduces the novel abstraction of virtual actors that solves a number of the complex distributed systems problems, such as reliability and distributed resource management, liberating the developers from dealing with those concerns. At the same time, the Orleans runtime enables applications to attain high performance, reliability and scalability. This paper presents the design principles behind Orleans and demonstrates how Orleans achieves a simple programming model that meets these goals. We describe how Orleans simplified the development of several scalable production applications on Windows Azure, and report on the performance of those production systems.distributed_systems/2017-09-11T23:06:32.2062829592017-09-11T23:06:32.206282959<EFBFBD>n<00><02>k5GGOmega: flexible, scalable schedulers for large compute clusters<07>Increasing scale and the need for rapid response to changing requirements are hard to meet with current monolithic cluster scheduler architectures. This restricts the rate at which new features can be deployed, decreases efficiency and utilization, and will eventually limit cluster growth. We present a novel approach to address these needs using parallelism, shared state, and lock-free optimistic concurrency control.
 We compare this approach to existing cluster scheduler designs, evaluate how much interference between schedulers occurs and how much it matters in practice, present some techniques to alleviate it, and finally discuss a use case highlighting the advantages of our approach -- all driven by real-life Google production workloads.EuroSysdistributed_systems/2017-09-11T23:06:32.1113601072017-09-11T23:06:32.111360107
F	G<04>F<00>
s
o<02>	5GGPregel: a system for large-scale graph processing<07>Many practical computing problems concern large graphs. Standard examples include the Web graph and various social networks. The scale of these graphs - in some cases billions of vertices, trillions of edges - poses challenges to their efficient processing. In this paper we present a computational model suitable for this task. Programs are expressed as a sequence of iterations, in each of which a vertex can receive messages sent in the previous iteration, send messages to other vertices, and modify its own state and that of its outgoing edges or mutate graph topology. This vertex-centric approach is flexible enough to express a broad set of algorithms. The model has been designed for efficient, scalable and fault-tolerant implementation on clusters of thousands of commodity computers, and its implied synchronicity makes reasoning about programs easier. Distribution-related details are hidden behind an abstract API. The result is a framework for processing large graphs that is expressive and easy to program.PODCdistributed_systems/2017-09-11T23:06:32.7381860352017-09-11T23:06:32.738186035<EFBFBD>nr
K<02>M75GGA Note on Distributed Computing<07>We argue that objects that interact in a distributed system need to be dealt with in ways that are intrinsically different from objects that interact in a single address space. These differences are required because distributed systems require that the programmer be aware of latency, have a different model of memory access, and take into account issues of concurrency and partial failure. We look at a number of distributed systems that have attempted to paper over the distinction between local and remote objects, and show that such systems fail to support basic requirements of robustness and reliability. These failures have been masked in the past by the small size of the distributed systems that have been built. In the enterprise-wide distributed systems foreseen in the near future, however, such a masking will be impossible. We conclude by discussing what is required of both systems-level and application-level programmers and designers if one is to take distribution seriously.Mobile Object Systemsdistributed_systems/2017-09-11T23:06:32.5877800292017-09-11T23:06:32.587780029<EFBFBD>6q<00>
<02>=5GGPractical byzantine fault tolerance and proactive recovery<07>Our growing reliance on online services accessible on the Internet demands highly available systems that provide correct service without interruptions. Software bugs, operator mistakes, and malicious attacks are a major cause of service interruptions and they can cause arbitrary behavior, that is, Byzantine faults. This article describes a new replication algorithm, BFT, that can be used to build highly available systems that tolerate Byzantine faults. BFT can be used in practice to implement real services: it performs well, it is safe in asynchronous environments such as the Internet, it incorporates mechanisms to defend against Byzantine-faulty clients, and it recovers replicas proactively. The recovery mechanism allows the algorithm to tolerate any number of faults over the lifetime of the system provided fewer than 1/3 of the replicas become faulty within a small window of vulnerability. BFT has been implemented as a generic program library with a simple interface. We used the library to implement the first Byzantine-fault-tolerant NFS file system, BFS. The BFT library and BFS perform well because the library incorporates several important optimizations, the most important of which is the use of symmetric cryptography to authenticate messages. The performance results show that BFS performs 2&percnt; faster to 24&percnt; slower than production implementations of the NFS protocol that are not replicated. This supports our claim that the BFT library can be used to build practical systems that tolerate Byzantine faults.ACM Trans. Comput. Syst.distributed_systems/2017-09-11T23:06:32.3522580572017-09-11T23:06:32.352258057
<03>)<03><00>fv
e<02>E5GGSparrow: distributed, low latency scheduling<07>Large-scale data analytics frameworks are shifting towards shorter task durations and larger degrees of parallelism to provide low latency. Scheduling highly parallel jobs that complete in hundreds of milliseconds poses a major challenge for task schedulers, which will need to schedule millions of tasks per second on appropriate machines while offering millisecond-level latency and high availability. We demonstrate that a decentralized, randomized sampling approach provides near-optimal performance while avoiding the throughput and availability limitations of a centralized design. We implement and deploy our scheduler, Sparrow, on a 110-machine cluster and demonstrate that Sparrow performs within 12% of an ideal scheduler.SOSPdistributed_systems/2017-09-11T23:06:32.9525480962017-09-11T23:06:32.952548096<EFBFBD>u
<02>5GGReplication, history, and grafting in the Ori file system<07>Ori is a file system that manages user data in a modern setting where users have multiple devices and wish to access files everywhere, synchronize data, recover from disk failure, access old versions, and share data. The key to satisfying these needs is keeping and replicating file system history across devices, which is now practical as storage space has outpaced both wide-area network (WAN) bandwidth and the size of managed data. Replication provides access to files from multiple devices. History provides synchronization and offline access. Replication and history together subsume backup by providing snapshots and avoiding any single point of failure. In fact, Ori is fully peer-to-peer, offering opportunistic synchronization between user devices in close proximity and ensuring that the file system is usable so long as a single replica remains. Cross-file system data sharing with history is provided by a new mechanism called <i>grafting</i>. An evaluation shows that as a local file system, Ori has low overhead compared to a File system in User Space (FUSE) loopback driver; as a network file system, Ori over a WAN outperforms NFS over a LAN.SOSPdistributed_systems/2017-09-11T23:06:32.9191740722017-09-11T23:06:32.919174072<EFBFBD>Tt<00><02>K=5GGSinfonia: A new paradigm for building scalable distributed systems<07>We propose a new paradigm for building scalable distributed systems. Our approach does not require dealing with message-passing protocols -- a major complication in existing distributed systems. Instead, developers just design and manipulate data structures within our service called Sinfonia. Sinfonia keeps data for applications on a set of memory nodes, each exporting a linear address space. At the core of Sinfonia is a novel minitransaction primitive that enables efficient and consistent access to data, while hiding the complexities that arise from concurrency and failures. Using Sinfonia, we implemented two very different and complex applications in a few months: a cluster file system and a group communication service. Our implementations perform well and scale to hundreds of machines.ACM Trans. Comput. Syst.distributed_systems/2017-09-11T23:06:32.8341459962017-09-11T23:06:32.834145996
<<02>K
?<04>{f<0B> 
<EFBFBD><02>o<05>
<00>G<EFBFBD>C
<00>M;%GGhttps://github.com/papers-we-love/papers-we-love/blob/master/mathematics/transcendence-of-pi.pdfThe Transcendence of pimathematics/2017-09-11T23:06:15.7994541022017-09-11T23:06:15.799454102<EFBFBD><0B>B	m/GGhttp://www.ccs.neu.edu/racket/pubs/icfp10-cf.pdfFortifying Macrosmacros/2017-09-11T23:06:15.7983291022017-09-11T23:06:15.798329102<<00>	sYGGhttp://people.csail.mit.edu/jrb/Projects/dexprs.pdfD-Expressions: Lisp Power, Dylan Stylemacros/2017-09-11T23:06:15.7983291022017-09-11T23:06:15.798329102<EFBFBD><04>@	I1/GGhttp://arxiv.org/abs/1004.4240arXiv/cs/1004:4240machine_learning/2017-09-11T23:06:15.7669990232017-09-11T23:06:15.7669990233<00><05>/GGhttp://www.kdd.org/kdd2016/papers/fi<66>%<25>A	sYGG<00>http://people.csail.mit.edu/jrb/Projects/dexprs.pdfD-Expressions: Lisp Power, Dylan Stylemacros/2017-09-11T23:06:15.7983291022017-09-11T23:06:15.798329102<05>
<00><>Q<EFBFBD>>
<02>o/GG<00>http://www.berkkapicioglu.com/wp-content/uploads/2013/11/thesis_final.pdfApplications of Machine Learning to Location Datamachine_learning/2017-09-11T23:06:15.7669990232017-09-11T23:06:15.766999023<EFBFBD>1<EFBFBD>8
<02>
M/GG<00>http://www.cs.uvm.edu/~icdm/algorithms/10Algorithms-08.pdfTop 10 algorithms in data miningmachine_learning/2017-09-11T23:06:15.7669990232017-09-11T23:06:15.766999023<08>+
<00>;/GGhttp://rd.springer.com/conten<65>
<0A>B	m/GG<00>http://www.ccs.neu.edu/racket/pubs/icfp10-cf.pdfFortifying Macrosmacros/2017-09-11T23:06:15.7983291022017-09-11T23:06:15.798329102<EFBFBD>)<29><
<02>;/GG<00>http://rd.springer.com/content/pdf/10.1007%2FBF00994018.pdfSupport-Vector Networksmachine_learning/2017-09-11T23:06:15.7669990232017-09-11T23:06:15.766999023<EFBFBD><00>;<02>+<2B>?/GG<00>http://repository.upenn.edu/cgi/viewcontent.cgi?article=1162&context=cis_papersConditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Datamachine_learning/2017-09-11T23:06:15.7669990232017-09-11T23:06:15.766999023<EFBFBD> <20>:
<02>)/GG<00>https://www.stat.berkeley.edu/~breiman/randomforest2001.pdfRandom Forestsmachine_learning/2017-09-11T23:06:15.7669990232017-09-11T23:06:15.766999023
T
<00>
M/GGhttp://www.cs.uvm.edu/~icdm/algorithms/10Algorithms-08.pdfTop 10 algorithms in data miningmachine_learning/2017-09-11T23:06:15.7669990232017-09-11T23:06:15.766999023L<00>=<3D>39GGhttp://www.pps.univ-paris-diderot.fr/~saurin/Enseignement/LMFI/articles/Martin-Lof83.pdfOn the Meanings of the Logical Constants and the Justifica<63>I<EFBFBD>C
<02>M;%GG<00>https://github.com/papers-we-love/papers-we-love/blob/master/mathematics/transcendence-of-pi.pdfThe Transcendence of pimathematics/2017-09-11T23:06:15.7994541022017-09-11T23:06:15.799454102<EFBFBD>Z<EFBFBD>?<02><05>/GG<00>http://www.kdd.org/kdd2016/papers/files/rfp0573-ribeiroA.pdf"Why Should I Trust You?" Explaining the Predictions of Any Classifiermachine_learning/2017-09-11T23:06:15.7669990232017-09-11T23:06:15.766999023<EFBFBD>=<3D>=
<02>_/GG<00>https://www.cs.princeton.edu/~chazelle/pubs/FJLT-sicomp09.pdfThe Fast Johnson-Lindenstrauss Transformsmachine_learning/2017-09-11T23:06:15.7669990232017-09-11T23:06:15.766999023<EFBFBD>@<40>9	}q/GG<00>http://homes.cs.washington.edu/~pedrod/papers/cacm12.pdfA Few Useful Things to Know about Machine Learningmachine_learning/2017-09-11T23:06:15.7669990232017-09-11T23:06:15.766999023<EFBFBD><08>7<02>=<3D>39GG<00>http://www.pps.univ-paris-diderot.fr/~saurin/Enseignement/LMFI/articles/Martin-Lof83.pdfOn the Meanings of the Logical Constants and the Justifications of the Logical Lawslogic_and_programming/2017-09-11T23:06:15.7549079592017-09-11T23:06:15.754907959<EFBFBD>O<EFBFBD>6
<02>u9GG<00>http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.148.524Purely Functional Lazy Non-deterministic Programminglogic_and_programming/2017-09-11T23:06:15.7549079592017-09-11T23:06:15.754907959<EFBFBD>^<5E>5
<02>Cc1GG<00>http://research.microsoft.com/en-us/um/people/simonpj/papers/history-of-haskell/history.pdfA History of Haskell: Being Lazy With Classlanguages/haskell/2017-09-11T23:06:15.7042490232017-09-11T23:06:15.704249023
<00><04><08><08><08><08><08>r`M=&<07><07><07><07><07><07>}k[M<'<06><06><06><06><06><06><06>{l]M2<05><05><05><05><05><05><05>k<04><04>ZF6<0F><0F><0F><0F><0F><0F><0F>~hSB.<0E><0E><0E><0E><0E><0E><0E>ydN7
<0A>
<0A>
<0A>
<0A>
<0A><04>
o
U
>
%
<0C><0C><0C><0C><0C><0C><0C><0C>qbRA,<0B><0B><0B><0B><0B><0B><0B><04>zkZ?+
<EFBFBD>
<EFBFBD>
<EFBFBD><04>
<EFBFBD>
<EFBFBD>
<EFBFBD>
n
_
L
7
"
	<09>	<09>	<09>	<09>	<09>	q	U	F	/			<08><08><08><04><04><04><04><04><04>saN=, 
<03><03><03><03><03><03><03><03>vaO@1"<02><02><02><02><02><02><02>yl\G0!
<01>
<01>
<01>
<01>
<01>H. Kim<05>+Jacob M. Taylor<02>/Jacob Gorm Hansen<05>%Jacob Albers-J.michael Ashley<02>
J. Ye?J. YanJ. W. Lee\J. Velosa<04>/J. Strother Moore<02>+J. Ross Quinlan!J. Roseira<04>J. Reis<04>J. Regula%!J. Prakash<03>
J. Pinho<04>J. Park<05>+J. P. H. Drenth4+J. P. GutierrezK%J. P. Barker<02>)J. M. Ferreira<04>)J. M. AlustizaK
J. Li<05>J. KarnerlJ. K. Ryu^J. K. LeeY%J. J. FurmanN+J. I. EmparanzaT
J. Hajal<04>!J. H. YoonLJ. H. Son[J. H. Lee<04>J. H. Han<05>J. Goulis<04>)J. Garcia Cano<%J. Fernandes<04>)J. Feichtinger-J. Eliot B. Moss
<01>J. Cho<05>#J. Carvalho<04>#J. C. Sousa<04>'J. Bou Jaoude<04>%J. BorovickaI#J. A. Sloan13J. A. M. Verma%Gael Sentís<05>3Emmanuel Lopez-Neri<05>7Engineer Bainomugisha<05>9Gerth Stølting Brodal<05>)Frank Piessens<05>'Emilia Thiuri<05>/Frank D. Francone<05>#
Eric Bodden)Eric A. Brewer<03>#Eran Tromer<00>5Emmanuel Dellandréa,Emma Fulu<03>+Emin Gün Sirer
	+Emery D. Berger
W%
Eman RamadanA)
Elmar Eisemann_%
Elaine CohenU#Edwin Brady<02>-Edward J. Rykiel1Edsger W. Dijkstra<03>7Edmund B. Nightingale<!E. Zehnter<04>E. ZapataIE. Soaresw#E. Sklyarov!E. Shehata<04>#E. SalvadorL%E. S. TharwaoE. Novo<03>!E. Morello<03>7E. Michael Maximilien<02>)E. M. Abdelaaln!E. Liusina<04>E. Kimn+E. I. Sharipova #E. Garanina#
E. Fuchs!E. Cancela<04>%E. Bugianesi<03>E. Branco<04>E. Albano<03>E. Adel<04>)
Dustin Freemanv)Dragan Gasevic<03>5Douglas Stott Parker
1
Douglas M. CarmeanH-Douglas B. Terry
<01>!Doug Simon<02>/Dor Laor Qumranet<05>#
Dongjing He'Donald Beaver~'
Dominik Grewe%#Dogan Engin<03>
Dirk FoxcDing Yuan
<01>#Dieter Foxy<02>!Dieter Fox<02>%Diego Ongaro<03>
H. He<03>!H. Hachiyah%H. Guerreiro^H. Friess!H. Cardoso<04>!H. B. Chae<05>/Günther KnoblichoGunho Lee
69Gunavardhan Kakulapati6?Guilherme Renna Rodrigues
<01>?Guilherme Horta Travassos<02>'Guanghao Shen
<01>/Grzegorz Malewicz
j3Grzegorz Czajkowski
p3Gregory V. Chockler<03>/Gregory H. Cooper1+Gregor Richards<02>+Gregor Kiczales<02>'Greg Friedman<00>!
Gong ZhangE/Giuseppe Decandia3-Gioacchino Noris<00>'Gintaras Woss
<01>)Gilles Duboscq<02>-Georges Gonthier
<01>=
George Van Den Driessche%George Stiny<00>'George Candea<00>%
Georg SeeligJ)Geoffrey Romer<00>7Geoffrey J. Mclachlan #Geoff Wyant
gGene Pang
%Gareth TysonH'Gabriel Kliot
_!G. Villano<03>7G. V. Papatheodoridis<04>!G. UmefuneuG. Teuber<04>
G. Storm<03>#G. SemadeniE+G. R. Burganova&G. Pevnev%+G. Nigel Martin<02>#G. Mazzella !G. Marasco<04>G. Macedo<04>%G. LetamendiO-G. J. M. WebstercG. Gwak<04>'G. E. Tontini<04>G. Di Leo<04>!G. Dalekos<04>!G. Chiriacu!G. A. Nagy:/Friedrich M. Wahl<02>-Fredrik Lindsten(3Frederick P. Brooks
'/Fred B. Schneider
V5François X. Sillion<00>1François Lazeyras
<01>#Frank Dabek<03>3Francisca Ogwueleka	=Francesco Zappa Nardelli<00>1
Francesca Spezzano;9Flemming Friche Rodler<00>9Flavio Paiva Junqueira<03>3Flavio P. Junqueira
0/Fernando Pereiraz<02>-Fernando Pereira*+Fernando Pedone[Fay Chang+)
Fabrice Neyret]%F. Zanconati<03>F. Yuan<05>'F. Sardanelli<04>#F. Ravaioli<04>'F. PleiningerF. NevensF. Karnelm
F. Bende<03>#Evan Herbst<02>)Evan Czaplicki|#Eugene Wong
+Ethan L. Miller<00>-Ernesto Jiménez<03>!Ernest Lin<00>!
Erika ChinErik Tews<00>#Erik Meijerc)Erik Johansson<00>Eric Tune
I%Eric Rollins<00>
Eric Jul<05>
<08>B<00>,y
I<02>7K5GGThe Byzantine Generals Problem<07>A definition • Byzantine (www.m-w.com): 1: of, relating to, or characteristic of the ancient city of Byzantium … 4b: intricately involved : labyrinthine <rules of Byzantine complexity> • Lamport's reason: " I have long felt that, because it was posed as a cute problem about philosophers seated around a table, Dijkstra's dining philosopher's problem received much more attention than it deserves. "ACM Trans. Program. Lang. Syst.distributed_systems/2017-09-11T23:06:33.2295629882017-09-11T23:06:33.229562988<EFBFBD>Nx<00><02>m5GGThe Chubby Lock Service for Loosely-Coupled Distributed Systems<07>We describe our experiences with the Chubby lock service, which is intended to provide coarse-grained locking as well as reliable (though low-volume) storage for a loosely-coupled distributed system. Chubby provides an interface much like a distributed file system with advisory locks, but the design emphasis is on availability and reliability, as opposed to high performance. Many instances of the service have been used for over a year, with several of them each handling a few tens of thousands of clients concurrently. The paper describes the initial design and expected use, compares it with actual use, and explains how the design had to be modified to accommodate the differences.OSDIdistributed_systems/2017-09-11T23:06:33.1348068852017-09-11T23:06:33.134806885<EFBFBD>jw
A<02>q5GGResilient Overlay Networks<07>A Resilient Overlay Network (RON) is an architecture that allows distributed Internet applications to detect and recover from path outages and periods of degraded performance within several seconds, improving over today's wide-area routing protocols that take at least several minutes to recover. A RON is an application-layer overlay on top of the existing Internet routing substrate. The RON nodes monitor the functioning and quality of the Internet paths among themselves, and use this information to decide whether to route packets directly over the Internet or by way of other RON nodes, optimizing application-specific routing metrics.Results from two sets of measurements of a working RON deployed at sites scattered across the Internet demonstrate the benefits of our architecture. For instance, over a 64-hour sampling period in March 2001 across a twelve-node RON, there were 32 significant outages, each lasting over thirty minutes, over the 132 measured paths. RON's routing mechanism was able to detect, recover, and route around <i>all</i> of them, in less than twenty seconds on average, showing that its methods for fault detection and recovery work well at discovering alternate paths in the Internet. Furthermore, RON was able to improve the loss rate, latency, or throughput perceived by data transfers; for example, about 5% of the transfers doubled their TCP throughput and 5% of our transfers saw their loss probability reduced by 0.05. We found that forwarding packets via at most one intermediate RON node is sufficient to overcome faults and improve performance in most cases. These improvements, particularly in the area of fault detection and recovery, demonstrate the benefits of moving some of the control over routing into the hands of end-systems.SOSPdistributed_systems/2017-09-11T23:06:33.0871088872017-09-11T23:06:33.087108887
<02>	C<06><02><00>_|
q<02>+5GGThere is more consensus in Egalitarian parliaments<07>This paper describes the design and implementation of Egalitarian Paxos (EPaxos), a new distributed consensus algorithm based on Paxos. EPaxos achieves three goals: (1) optimal commit latency in the wide-area when tolerating one and two failures, under realistic conditions; (2) uniform load balancing across all replicas (thus achieving high throughput); and (3) graceful performance degradation when replicas are slow or crash.
 Egalitarian Paxos is to our knowledge the first protocol to achieve the previously stated goals efficiently---that is, requiring only a simple majority of replicas to be non-faulty, using a number of messages linear in the number of replicas to choose a command, and committing commands after just one communication round (one round trip) in the common case or after at most two rounds in any case. We prove Egalitarian Paxos's properties theoretically and demonstrate its advantages empirically through an implementation running on Amazon EC2.SOSPdistributed_systems/2017-09-11T23:06:33.4618039552017-09-11T23:06:33.461803955<EFBFBD>Q{
=<02>=5GGThe Part-Time Parliament<07>Recent archaeological discoveries on the island of Paxos reveal that the parliament functioned despite the peripatetic propensity of its part-time legislators. The legislators maintained consistent copies of the parliamentary record, despite their frequent forays from the chamber and the forgetfulness of their messengers. The Paxon parliament's protocol provides a new way of implementing the state machine approach to the design of distributed systems.ACM Trans. Comput. Syst.distributed_systems/2017-09-11T23:06:33.3980859382017-09-11T23:06:33.398085938<EFBFBD>:z<00>
<02>?5GGThe Join Calculus: A Language for Distributed Mobile Programming<07>In these notes, we give an overview of the join calculus, its semantics, and its equational theory. The join calculus is a language that models distributed and mobile programming. It is characterized by an explicit notion of locality, a strict adherence to local synchronization, and a direct embedding of the ML programming language. The join calculus is used as the basis for several distributed languages and implementations, such as JoCaml and functional nets. Local synchronization means that messages always travel to a set destination , and can interact only after they reach that destination; this is required for an efficient implementation. Specifically, the join calculus uses ML's function bindings and pattern-matching on messages to program these synchronizations in a declarative manner. Formally, the language owes much to concurrency theory, which provides a strong basis for stating and proving the properties of asynchronous programs. Because of several remarkable identities, the theory of process equivalences admits simplifications when applied to the join calculus. We prove several of these identities, and argue that equivalences for the join calculus can be rationally organized into a five-tiered hierarchy, with some trade-off between expressiveness and proof techniques. We describe the mobility extensions of the core calculus, which allow the programming of agent creation and migration. We briefly present how the calculus has been extended to model distributed failures on the one hand, and cryptographic protocols on the other.APPSEMdistributed_systems/2017-09-11T23:06:33.3153669432017-09-11T23:06:33.315366943

"<07>
<00>$<00>#<02>W?5GGTransactional Client-Server Cache Consistency: Alternatives and Performance<07>Client-server database systems based on a data shipping model can exploit client memory resources by caching copies of data items across transaction boundaries. Caching reduces the need to obtain data from servers or other sites on the network. In order to ensure that such caching does not result in the violation of transaction semantics, a transactional cache consistency maintenance algorithm is required. Many such algorithms have been proposed in the literature and, as all provide the same functionality, performance is a primary concern in choosing among them. In this article we present a taxonomy that describes the design space for transactional cache consistency maintenance algorithms and show how proposed algorithms relate to one another. We then investigate the performance of six of these algorithms, and use these results to examine the tradeoffs inherent in the design choices identified in the taxonomy. The results show that the interactions among dimensions of the design space impact performance in many ways, and that classifications of algorithms as simply &#8220;pessimistic&#8221; or &#8220;optimistic&#8221; do not accurately characterize the sim
s<02>U5GGUnikernels: library operating systems for the cloud<07>We present <i>unikernels</i>, a new approach to deploying cloud services via applications written in high-level source code. Unikernels are single-purpose appliances that are compile-time specialised into standalone kernels, and sealed against modification when deployed to a cloud platform. In return they offer significant reduction in image sizes, improved efficiency and security, and should reduce operational costs. Our Mirage prototype compiles OCaml code into unikernels that run on commodity clouds and offer an order of magnitude reduction in code size without significant performance penalty. The architecture combines static type-safety with a single address-space layout that can be made immutable via a hypervisor extension. Mirage contributes a suite of type-safe protocol libraries, and our results demonstrate that the hypervisor is a platform that overcomes the hardware compatibility issues that have made past library operating systems impractical to deploy in the real-world.ASPLOSdistributed_systems/2017-09-11T23:06:33.6906950682017-09-11T23:06:33.690695068<EFBFBD>[}
m<02>%5GGUnicorn: A System for Searching the Social Graph<07>Unicorn is an online, in-memory social graph-aware indexing system designed to search trillions of edges between tens of billions of users and entities on thousands of commodity servers. Unicorn is based on standard concepts in information retrieval, but it includes features to promote results with good social proximity. It also supports queries that require multiple round-trips to leaves in order to retrieve objects that are more than one edge away from source nodes. Unicorn is designed to answer billions of queries per day at latencies in the hundreds of milliseconds, and it serves as an infrastructural building block for Facebook's Graph Search product. In this paper, we describe the data model and query language supported by Unicorn. We also describe its evolution as it became the primary backend for Facebook's search offerings.PVLDBdistributed_systems/2017-09-11T23:06:33.5491799322017-09-11T23:06:33.549179932
aia<00><04>

k<02>{5GGViewstamped Replication: A General Primary Copy<07>One of the potential benefits of distributed systems is their use in providing highly-available services that are likely to be usable when needed. Availabilay is achieved through replication. By having inore than one copy of information, a service continues to be usable even when some copies are inaccessible, for example, because of a crash of the computer where a copy was stored. This paper presents a new replication algorithm that has desirable performance properties. Our approach is based on the primary copy technique. Computations run at a primary. which notifies its backups of what it has done. If the primary crashes, the backups are reorganized, and one of the backups becomes the new primary. Our method works in a general network with both node crashes and partitions. Replication causes little delay in user computations and little information is lost in a reorganization; we use a special kind of timestamp called a viewstamp to detect lost information. 1 Introduction One of the potential benefits of distributed systems is their use in providing highly-available services, that is, services that are likely to be up and accessible when needed. Availability is essential to many computer-based services; for example, in airline reservation systems the failure of a single computer can prevent ticket sales for a considerable time, causing a loss of revenue and passenger goodwill.PODCdistributed_systems/2017-09-11T23:06:34.0234819342017-09-11T23:06:34.023481934<EFBFBD><13><00><02>]#5GGUntraceable Electronic Mail, Return Addresses, and Digital Pseudonyms<07>A technique based on public key cryptography is presented that allows an electronic mail system to hide who a participant communicates with as well as the content of the communication-in spite of an unsecured underlying telecommunication system. The technique does not require a universally trusted authority. One correspondent can remain anonymous to a second, while allowing the second to respond via an untraceble return address. The technique can also be used to form rosters of untraceable digital pseudonyms from selected applications. Applicants retain the exclusive ability to form digital signatures corresponding to their pseudonyms. Elections in which any interested party can verify that the ballots have been properly counted are possible if anonymously mailed ballots are signed with pseudonyms from a roster of registered voters. Another use allows an individual to correspond with a record-keeping organization under a unique pseudonym which appears in a roster of acceptable clients.Commun. ACMdistributed_systems/2017-09-11T23:06:33.9009379882017-09-11T23:06:33.900937988
&
&<00>j<EFBFBD>
w<02>5/!GGAuctions and bidding: A guide for computer scientists<07>There is a veritable menagerie of auctions&#8212;single-dimensional, multi-dimensional, single-sided, double-sided, first-price, second-price, English, Dutch, Japanese, sealed-bid&#8212;and these have been extensively discussed and analyzed in the economics literature. The main purpose of this article is to survey this literature from a computer science perspective, primarily from the viewpoint of computer scientists who are interested in learning about auction theory, and to provide pointers into the economics literature for those who want a deeper technical understanding. In addition, since auctions are an increasingly important topic in computer science, we also look at work on auctions from the computer science literature. Overall, our aim is to identifying what both these bodies of work these tell us about creating electronic auctions.ACM Comput. Surv.economics/2017-09-11T23:06:34.3237980962017-09-11T23:06:34.323798096<EFBFBD><03>
}<02>g5GGIronFleet: proving practical distributed systems correct<07>Distributed systems are notorious for harboring subtle bugs. Verification can, in principle, eliminate these bugs a priori, but verification has historically been difficult to apply at full-program scale, much less distributed-system scale.
 We describe a methodology for building practical and provably correct distributed systems based on a unique blend of TLA-style state-machine refinement and Hoare-logic verification. We demonstrate the methodology on a complex implementation of a Paxos-based replicated state machine library and a lease-based sharded key-value store. We prove that each obeys a concise safety specification, as well as desirable liveness requirements. Each implementation achieves performance competitive with a reference system. With our methodology and lessons learned, we aim to raise the standard for distributed systems from "tested" to "correct."SOSPdistributed_systems/2017-09-11T23:06:34.2188640142017-09-11T23:06:34.218864014<EFBFBD>a<EFBFBD>
m<02>%#5GGVL2: a scalable and flexible data center network<07>To be agile and cost effective, data centers should allow dynamic resource allocation across large server pools. In particular, the data center network should enable any server to be assigned to any service. To meet these goals, we present VL2, a practical network architecture that scales to support huge data centers with uniform high capacity between servers, performance isolation between services, and Ethernet layer-2 semantics. VL2 uses (1) flat addressing to allow service instances to be placed anywhere in the network, (2) Valiant Load Balancing to spread traffic uniformly across network paths, and (3) end-system based address resolution to scale to large server pools, without introducing complexity to the network control plane. VL2's design is driven by detailed measurements of traffic and fault data from a large operational cloud service provider. VL2's implementation leverages proven network technologies, already available at low cost in high-speed hardware implementations, to build a scalable and reliable network architecture. As a result, VL2 networks can be deployed today, and we have built a working prototype. We evaluate the merits of the VL2 design using measurement, analysis, and experiments. Our VL2 prototype shuffles 2.7 TB of data among 75 servers in 395 seconds - sustaining a rate that is 94% of the maximum possible.Commun. ACMdistributed_systems/2017-09-11T23:06:34.1214880372017-09-11T23:06:34.121488037

.<08>
.<00>b<EFBFBD><00><02>5GGSimple Testing Can Prevent Most Critical Failures: An Analysis of Production Failures in Distributed Data-Intensive Systems<07>Large, production quality distributed systems still fail periodically , and do so sometimes catastrophically, where most or all users experience an outage or data loss. We present the result of a comprehensive study investigating 198 randomly selected, user-reported failures that occurred on Cassandra, HBase, Hadoop Distributed File System (HDFS), Hadoop MapReduce, and Redis, with the goal of understanding how one or multiple faults eventually evolve into a user-visible failure. We found that from a testing point of view, almost all failures require only 3 or fewer nodes to reproduce, which is good news considering that these services typically run on a very large number of nodes. However, multiple inputs are needed to trigger the failures with the order between them being important. Finally, we found the error logs of these systems typically contain sufficient data on both the errors and the input events that triggered the failure, enabling the diagnose and the reproduction of the production failures. We found the majority of catastrophic failures could easily have been prevented by performing simple testing on error handling code – the last line of defense – even without an understanding of the software design. We extracted three simple rules from the bugs that have lead to some of the catastrophic failures, and developed a static checker, Aspirator, capable of locating these bugs. Over 30% of the catastrophic failures would have been prevented had Aspirator been used and the identified bugs fixed. Running Aspirator on the code of 9 distributed systems located 143 bugs and bad practices that have been fixed or confirmed by the developers.OSDIdistributed_systems/2017-09-11T23:06:34.6237900392017-09-11T23:06:34.623790039<EFBFBD>h<EFBFBD><00><02>!5GGStructural asymmetries of perisylvian regions in the preterm newborn<07>During the last trimester of human pregnancy, the cerebral cortex of foetuses becomes greatly and quickly gyrified, and post-mortem studies have demonstrated that hemispheres are already asymmetric at the level of Heschl gyrus, planum temporale and superior temporal sulcus (STS). Recently, magnetic resonance 
<EFBFBD>
<EFBFBD>
<EFBFBD>
~
^
5
	<09>	<09>	<09>	[	8	<08><08><08><08>k><07><07><07>qS-<06><06><06><06>g:<05><05><05><05>jD<04><04><04><04>]#<03><03><03>W5<02><02><02><02>jN,
<01>
<01>
<01>
j
C
<00><1B>#
Leo BreimanLeoBreiman&<26>/Pedro M. DomingosPedroM.Domingos$<24>-Edward J. RykielEdwardJ.Rykiel%<25>-#
Chung-Chieh ShanChung-ChiehShan<1F>'
Oleg KiselyovOlegKiselyov'<27>/
Sebastian FischerSebastianFischer<1F>'
Kjell WinbladKjellWinblad)<29>1
%David KlafteneggerDavidKlaftenegger<1F>'
Philip WadlerPhilipWadler<19>!
Paul HudakPaulHudak&<26>/Simon J. ThompsonSimonJ.Thompson<19>
!
Huiqing LiHuiqingLi<1D>%
Jacob AlbersJacobAlbers'<27>/
Mitchell SpradlinMitchellSpradlin<1D>
%
Brian HempelBrianHempel<19>	!
Ravi ChughRaviChugh<1F>'
Chris OkasakiChrisOkasaki9<69>A+
!Jean-Christophe FilliâtreJean-ChristopheFilliâtre<1D>%
Luc MarangetLucMaranget<1F>'
Cynthia DworkCynthiaDwork+<2B>3
+Sam Tobin-HochstadtSamTobin-Hochstadt<1D>%
Rowan DaviesRowanDavies7<73>?
/Ambrose Bonnaire-SergeantAmbroseBonnaire-Sergeant$<24>
-Jon M. KleinbergJonM.Kleinberg!<21>)
Éric GaussierÉricGaussier+<2B>3
Stéphane ClinchantStéphaneClinchant!<21>~)
Shojiro NishioShojiroNishio<1F>}'
Takahiro HaraTakahiroHara%<25>|-
Masumi ShirakawaMasumiShirakawa#<23>{+
Takuya KatayamaTakuyaKatayama<19>z!
Rami YaredRamiYared!<21>y)
Xavier DéfagoXavierDéfago+<2B>x3
#Naohiro HayashibaraNaohiroHayashibara<1D>w%
Chris ThomasChrisThomas<1F>v'
Valient GoughValientGough<1D>u%
Dan DumitriuDanDumitriu*<2A>t3Robbert Van RenesseRobbertVanRenesse#<23>s+
Ashish MotivalaAshishMotivala!<21>r)
Indranil GuptaIndranilGupta!<21>q)!
Abhinandan DasAbhinandanDas<1D>p%
Yaron MinskyYaronMinsky<1B>o#
Mihai BudiuMihaiBudiu<17>n
Zhen XiaoZhenXiao#<23>m+
Öznur ÖzkasapÖznurÖzkasap<1B>l#
Mark HaydenMarkHayden&<26>k/Kenneth P. BirmanKennethP.Birman&<26>j/Maarten Van SteenMaartenVanSteen-<2D>i5!
Anne-Marie KermarrecAnne-MarieKermarrec!<21>h)
Márk JelasityMárkJelasity$<24>g-Douglas B. TerryDouglasB.Terry*<2A>f3Daniel C. SwinehartDanielC.Swinehart&<26>e/Howard E. SturgisHowardE.Sturgis<1F>d'
Scott ShenkerScottShenker<1B>c#
John LarsonJohnLarson<17>b
Wes IrishWesIrish <20>a)Carl H. HauserCarlH.Hauser$<24>`-Daniel H. GreeneDanielH.Greene <20>_)Alan J. DemersAlanJ.Demers.<2E>^7Luís E. T. RodriguesLuísE. T.Rodrigues.<2E>]7José Orlando PereiraJoséOrlandoPereira<1F>\'
João LeitãoJoãoLeitão.<2E>[7Simon L. Peyton JonesSimonL. PeytonJones"<22>Z+Roshan P. JamesRoshanP.James&<26>Y/Timothy L. HarrisTimothyL.Harris<1D>X%
Simon MarlowSimonMarlow <20>W)Henry G. BakerHenryG.Baker$<24>V-J. Eliot B. MossJ.Eliot B.Moss&<26>U/Richard L. HudsonRichardL.Hudson*<2A>T3Jerome C. YochelsonJeromeC.Yochelson#<23>S+
Robert FenichelRobertFenichel"<22>R+James A. LandayJamesA.Landay<1C>Q%Ian E. SmithIanE.Smith'<27>P/
Katherine EverittKatherineEveritt!<21>O)
Sunny ConsolvoSunnyConsolvo<1A>N#V. T. RajanV.T.Rajan<1B>M#
Perry ChengPerryCheng <20>L)David F. BaconDavidF.Bacon!<21>K)
Steffen GrarupSteffenGrarup#<23>J+
Jacob SeligmannJacobSeligmann*<2A>I3Joan Morris DimiccoJoanMorrisDimicco"<22>H+David R. MillenDavidR.Millen1<6E>G9
'Jennifer Thom-SantelliJenniferThom-Santelli<1D>F%
Nuria OliverNuriaOliver#<23>E+
Mauro CherubiniMauroCherubini*<2A>D3Rodrigo De OliveiraRodrigoDeOliveira$<24>C-Lennart E. NackeLennartE.Nacke<1D>B%
Rilla KhaledRillaKhaled<17>A
Dan DixonDanDixon+<2B>@3
Sebastian DeterdingSebastianDeterding(<28>?1Kathrin M. GerlingKathrinM.Gerling<1D>>%
Ken ThompsonKenThompson$<24>=-David S. JohnsonDavidS.Johnson<1B><#
Juho HamariJuhoHamari<1B>;#
Kai HuotariKaiHuotari<1F>:'
Michael StummMichaelStumm<1B>9#
Pranay JainPranayJain<1D>8%
Yongle ZhangYongleZhang<13>7
Xu ZhaoXuZhao6<6F>6?Guilherme Renna RodriguesGuilhermeRennaRodrigues<19>5!
Xin ZhuangXinZhuang<11>4
Yu LuoYuLuo<17>3
Ding YuanDingYuan <20>2)Petra S. HuppiPetraS.Huppi-<2D>15'
Jean-Francois ManginJean-FrancoisMangin
<02>o<05><02><00>T<EFBFBD>
<00><02>
'GGExploring the Potential of Gamification Among Frail Elderly Persons<07>The application of game elements a in non-gaming context offers a great potential regarding the engagement of senior citizens with information systems. In this paper, we suggest the application of gamification to routine tasks and leisure activities, namely physical and cognitive therapy, the gamification of real-life activities which are no longer accessible due to age-related changes and the application of game design elements to foster social interaction. Furthermore, we point out important chances and challenges such as the lack of gaming experience among the target audience and highlight possible areas for future work which offer valuable design opportunities for frail elderly audiences.gamification/2017-09-11T23:06:34.9897380372017-09-11T23:06:34.989738037<EFBFBD>#<23>	
G<02>i#GGReflections on Trusting Trust<07><italic>To what extent should one trust a statement that a program is free of Trojan horses? Perhaps it is more important to trust the people who wrote the software.</italic>Commun. ACMethics/2017-09-11T23:06:34.9361850592017-09-11T23:06:34.936185059<EFBFBD>L<EFBFBD><00><02>q}AGGA theoretician's guide to the experimental analysis of algorithms<07>This paper presents an informal discussion of issues that arise when one attempts to analyze algorithms experimentally. It is based on lessons learned by the author over the course of more than a decade of experimentation, survey paper writing, refereeing, and lively discussions with other experimentalists. Although written from the perspective of a theoretical computer scientist, it is intended to be of use to researchers from all fields who want to study algorithms experimentally. It has two goals: first, to provide a useful guide to new experimen-talists about how such work can best be performed and written up, and second, to challenge current researchers to think about whether their own work might be improved from a scientific point of view. With the latter purpose in mind, the author hopes that at least a few of his recommendations will be considered controversial.Data Structures, Near Neighbor Searches, and Methodologyexperimental_algorithmics/2017-09-11T23:06:34.8923630372017-09-11T23:06:34.892363037<EFBFBD>
<0A>
y<02>'GGDefining gamification: a service marketing perspective<07>During recent years "gamification" has gained significant attention among practitioners and game scholars. However, the current understanding of gamification has been solely based on the act of adding systemic game elements into services. In this paper, we propose a new definition for gamification, which emphases the experiential nature of games and gamification, instead of the systemic understanding. Furthermore, we tie this definition to theory from service marketing because majority of gamification implementations aim towards goals of marketing, which brings to the discussion the notion of how customer / user is always ultimately the creator of value. Since now, the main venue for academic discussion on gamification has mainly been the HCI community. We find it relevant both for industry practitioners as well as for academics to study how gamification can fit in the body of knowledge of existing service literature because the goals and the means of gamification and marketing have a significant overlap.MindTrekgamification/2017-09-11T23:06:34.7430820312017-09-11T23:06:34.743082031
<00><0B><06><00><00>
<EFBFBD><00><02>e3GGIncremental Mature Garbage Collection Using the Train Algorithm<07>We present an implementation of the Train Algorithm, an incremental collection scheme for reclamation of mature garbage in generation-based memory management systems. To the best of our knowledge, this is the rst Train Algorithm implementation ever. Using the algorithm, the traditional mark-sweep garbage collector employed by the Mjjlner run-time system for the object-oriented BETA programming language was replaced by a non-disruptive one, with only negligible time and storage overheads.ECOOPgarbage_collection/2017-09-11T23:06:36.1259221192017-09-11T23:06:36.125922119<EFBFBD>
<01>
e<02>	'GGRemoving gamification from an enterprise SNS<07>Gamification, the use of game mechanics in non-gaming applications, has been applied to various systems to encourage desired user behaviors. In this paper, we examine patterns of user activity in an enterprise social network service after the removal of a points-based incentive system. Our results reveal that the removal of the incentive scheme did reduce overall participation via contribution within the SNS. We also describe the strategies by point leaders and observe that users geographically distant from headquarters tended to comment on profiles outside of their home country. Finally, we describe the implications of the removal of extrinsic rewards, such as points and badges, on social software systems, particularly those deployed within an enterprise.CSCWgamification/2017-09-11T23:06:35.9502648932017-09-11T23:06:35.950264893<EFBFBD>T<EFBFBD><00>A<02>K'GGMoviPill: improving medication compliance for elders using a mobile persuasive social game<07>Medication compliance is a critical component in the success of any medical treatment. However, only 50% of patients correctly adhere to their prescription regimens. Mobile and ubiquitous technologies have been proposed to tackle this challenge, mainly in the form of memory aid solutions that remind patients to take their pills. However, most of these methods do not <i>engage</i> patients in shifting their behavior towards better compliance. In this paper, we propose and evaluate a mobile phone-based game called <i>MoviPill</i> that persuades patients to be more adherent to their medication prescription by means of social competition. In a 6-week user study conducted with 18 elders, the use of <i>MoviPill</i> improved both their compliance to take the daily medication and also the accuracy of the drug intake time according to the prescribed time. Moreover, the improvement in the latter increased from 43% to 56% when we considered only participants that had any interest in games, which reveals the importance of applying persuasive techniques in a personalized manner. We conclude with a set of implications for the design of persuasive mobile solutions in this domain.UbiCompgamification/2017-09-11T23:06:35.8032438962017-09-11T23:06:35.803243896<EFBFBD>
<0A><00><02>u'CCFrom game design elements to gamefulness: defining "gamification"<07>Recent years have seen a rapid proliferation of mass-market consumer software that takes inspiration from video games. Usually summarized as "gamification", this trend connects to a sizeable body of existing concepts and research in human-computer interaction and game studies, such as serious games, pervasive games, alternate reality games, or playful design. However, it is not clear how "gamification" relates to these, whether it denotes a novel phenomenon, and how to define it. Thus, in this paper we investigate "gamification" and the historical origins of the term in relation to precursors and similar concepts. It is suggested that "gamified" applications provide insight into novel, <i>gameful</i> phenomena complementary to playful phenomena. Based on our research, we propose a definition of "gamification" as <i>the use of game design elements in non-game contexts</i>.MindTrekgamification/2017-09-11T23:06:35.07447292017-09-11T23:06:35.0744729

7<00>4
<02><02>E
<01>
<01>
<0A>
<0A>
r
G
<0C><0C><0C>J<07>g<07>
6<07>gJ<06><06>p(<05><00><05>x
b<00>'<04><03><04><03>g<0F><0F>o( 
k<0E><0E>V<&
<EFBFBD>l
<EFBFBD>
N
<01>
*	<09>	<09>	<09>	A
	<08><08>iRea(SOrganizing Programs Without Classes"GFunctional Reactive Animation
<01>)UGenetic Programming: An Introduction

<01>Live Migrati3
Dynamic Hash TablesL+YFast asymmetric thread synchronization
w5mGamification in educational software development
hiLarge-scalK<04>Efficient Selectivity and Backup Operators in Monte-Carlo Tree Search
$KEfficient Predicate Dispatching<00>,[Efficient Lock-free Binary Search Treesǁ<04>
Effective Inter-Component Communication Mapping in Android with Epicc: An Essential Step Towards Holistic Security Analysis5mEM Algorithms for Probabilistic Mapping Networks
6oDynamo: amazon's highly available key-value store
%6q
Dremel: Interactive Analysis of Web-Scale DatasetsUD<04>	How the Hidden Hand Shapes the Market for Software Reliability
J5mHigh-Level Specifications: Lessons from Industry
I1eHarvest, Yield and Scalable Tolerant Systems
HN<04>Herbivore: A Scalable and Efficient Protocol for Anonymous Communication
G5mHigh-Performance Graphics in Racket with DirectX<00>F<04>
Heap architectures for concurrent languages using message passing7B<04>
HaLoop: Efficient Iterative Data Processing on Large ClustersZP<04>#
GigaVoxels: ray-guided streaming for efficient and detailed voxel rendering2gFundamental Concepts in Programming Languages<00>/aFunctional reactive programming, continued<00>L<04>Functional Programming with Bananas, Lenses, Envelopes and Barbed Wire<00>G<04>From game design elements to gamefulness: defining "gamification"<00>O<04>Freenet: A Distributed Anonymous Information Storage and Retrieval System
'/Fortifying macros<00>r<04>g
FlowDroid: precise context, flow, field, object-sensitive and lifecycle-aware taint analysis for Android apps;Flat Datacenter Storage
&,[FlashNet: flash/network stack co-design<00>@<04>
Finding race conditions in Erlang with QuickCheck and PULSE87Fast String Searching
.a
F1: A Distributed SQL Database That ScalesXI<04>Exploring the Potential of Gamification Among Frail Elderly Persons<00><02>Making Programs Forget: Enforcing Lifetime for Sensitive Data<00>H<04>
MEXICA: A computer model of a cognitive account of creative writing'S
MDCC: Multi-Data Center Consistency]"GLooking Inside the (Drop) Box<00><04>
Linearizability: A Correctness Condition for Concurrent Objectsj*WLinear work suffix array construction<00>8u
Lightweight Locking for Main Memory Database SystemsR,]
Light Propagation Volumes in Cryengine 3+Large-scale cluster management at Google with Borgi<03>Large-Scale Newscast Computing on the Internet<00>Z<04>7
KinectFusion: real-time 3D reconstruction and interaction using a moving depth camera&IKafka: a Distributed Messaging System for Log Processingg4kJoint action: bodies and minds moving together.<00>)UJails: Confining the<68>.<04>]Faculty of Associated Medical Sciences 1. Anterior Translation of Humeral Head in Glenohumeral Joint: Comparison between Limb Dominance and Gender Using Ultrasonography
<01>2i
Experience with Processes and Monitors in Mesa<V<04>/
Everything you always wanted to know about synchronization but were afraid to ask6-Event-Driven FRP<00>4m
Evaluating Generative Models for Text Generation=Epidemic Broadcast Trees<00><{Epidemic Algorithms for Replicated Database Maintenance<00>*WEnd-To-End Arguments in System Design<00>;yEluding carnivores: file sharing with strong anonymity
C,[Elm: Concurrent FRP for Functional GUIs<00>J<04>Efficient reconciliation and flow control for anti-entropy protocols<00>-Ideal Hash Trees
5IDF for Word N-grams<00>7s
HyperDex: a distributed, searchable key-value storeYJ<04>HyParView: A Membership Protocol for Reliable Gossip-Based Broadcast<00>0cHow to design a good API and why it matters
/
Hopscotch HashingK
Hol;F<04>
Hoard: A Scalable Memory Allocator for Multithreaded Applicationsm%MHints for Computer System Design
2gHigh-throughput DNA sequence data compression
!7s
High-quality single-shot capture of facial geometry4

x<00>`<60><00><02>'GGDesign requirements for technologies that encourage physical activity<07>Overweight and obesity are a global epidemic, with over one billion overweight adults worldwide (300+ million of whom are obese). Obesity is linked to several serious health problems and medical conditions. Medical experts agree that physical activity is critical to maintaining fitness, reducing weight, and improving health, yet many people have difficulty increasing and maintaining physical activity in everyday life. Clinical studies have shown that health benefits can occur from simply increasing the number of steps one takes each day and that social support can motivate people to stay active. In this paper, we describe Houston, a prototype mobile phone application for encouraging activity by sharing step count with friends. We also present four design requirements for technologies that encourage physical activity that we derived from a three-week long in situ pilot study that was conducted with women who wanted to increase their physical activity.CHIgamification/2017-09-11T23:06:36.2992419432017-09-11T23:06:36.299241943<EFBFBD><04>
Y<02>3GGA unified theory of garbage collection<07>Tracing and reference counting are uniformly viewed as being fundamentally different approaches to garbage collection that possess very distinct performance properties. We have implemented high-performance collectors of both types, and in the process observed that the more we optimized them, the more similarly they behaved - that they seem to share some deep structure. 
 We present a formulation of the two algorithms that shows that they are in fact duals of each other. Intuitively, the difference is that tracing operates on live objects, or "matter", while reference counting operates on dead objects, or "anti-matter". For every operation performed by the tracing collector, there is a precisely corresponding anti-operation performed by the reference counting collector.
 Using this framework, we show that all high-performance collectors (for example, deferred reference counting and generational collection) are in fact hybrids of tracing and reference counting. We develop a uniform cost-model for the collectors to quantify the trade-offs that result from choosing different hybridizations of tracing and reference counting. This allows the correct scheme to be selected based on system performance requirements and the expected properties of the target application.OOPSLAgarbage_collection/2017-09-11T23:06:36.2074350592017-09-11T23:06:36.207435059
<00>
<01><0F><0F><0F><0F><0F><0F>}tV@#
<0E><0E><0E><0E><0E><0E><0E><0E><0E>whZD7-
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
h
R
<
3
*


<0C><0C><0C><0C><0C><0C><0C><0C><0C>u[O=1
<0B><0B><0B><0B><0B><0B><0B><0B><0B>ylZQ/
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
w
m
\
Q
C
:
$

	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	q	_	N	B	3	(		<08><08><08><08><08><08><08><08>{o\RI@/ <07><07><07><07><07><07><07><07>}nO=*<06><06><06><06><06><06><06><06><06><06>weV?.$<05><05><05><05><05><05>wfW@"<04><04><04><04><04><04><04><04>|jLA8/#<03><03><03><03><03><03><03><03><03><03>}ti^G3%<02><02><02><02><02><02><02>}fSB6-$
<01>
<01>
<01><0C>=assembler<07><byte<0E>;#polymorphic<11>:)hindley-milner<06>9ner<06>8cpl<06>7adl	<09>6formal<0E>5#irrelevance<10>4'bracket types<14>3/first-order logic<13>2-regular category<18>17dependent type theory	<09>0typing<06>/fun<1A>.;parametric polymorphism<0C>-subtyping<0B>,checking<08>+check	<09>*static<0E>)#soft typing<0B>(run-time<11>')dependent type<14>&/algebraic effects<08>%monad<08>$guage<06>#lev<19>"9functional programming<06>!suc<07> unix<07>lisp<06>mop<06>ant<06>clo<10>'major feature<06>tod<07>memo<1B>=efficient implementation<0B>wormhole	<09>flavor<06>rpc<06>gui<08>async<1B>=graphical user interface<0F>%continuation<07>afrp<08>yampa<06>frp<08>
arrow<0C>animation<19>9abstract argumentation<1A>
;argumentation semantics<06>	iff<1A>;argumentation framework<0C>labelling<1B>=prototype-based language<14>/natural extension<0C>data type<0E>#class-based<11>)others' action
<0A>
!psychology<12>+joint attention<18>7shared representation<14>~/co-representation<06>}tem<17>|5end-to-end principle<06>{hop
<EFBFBD>zplement<06>yaic<07>xsloc<0E>w#refactoring<14>v/lambda expression<0C>urecursion<0F>t%catamorphism<06>sfix<06>rjer
<EFBFBD>qalgebra<11>p)virtualization
<EFBFBD>ovserver<0C>ncontainer<15>m1paravirtualization	<09>ldenali<06>klso<06>jxen<13>i-interface design
<EFBFBD>hcommute<08>gposix<10>f'commutativity<0F>e%dissertation<1C>d?multithreaded application<0C>cdirectory<0B>bcommuter<15>a1parallel operation<06>`bst<16>_3binary search trees<10>^'fetch-and-add<0C>]wait-free<06>\faa<07>[wild<07>Zspdy<19>Y9network characteristic<0C>Xload time<0E>W#reclamation<06>Vebr<06>Urcu<07>Tslab<10>S'kernel memory	<09>Rbuffer<11>Q)complex object<07>Pfpga<06>Ommu
<EFBFBD>Nmutator<1A>M;machine learning method<06>Lann<0B>Kclinical<14>J/cancer prediction<15>I1language extension<06>Hvar
<EFBFBD>Gclarity<08>Fmacro<0C>Edebugging	<09>Dpreter<0E>C#interpreter<0F>B%maximization<12>A+kernel function<08>@lkopf
<0A>?!sequence x<06>>sgd<0B>=labels t<0E><#local model<11>;)vertices of g.<06>:rfs<0F>9%randomforest<0B>8boosting
<0A>7!out-of-bag<0B>6adaboost<13>5-feature engineer<06>4ers<0B>3classifi<08>2curse<0E>1#overfitting<07>0lazy<12>/+non-determinism<0E>.#memoization<13>--call-time choice<06>,ets<07>+edsl<0B>*eighties<16>)3generic programming<12>(+formal semantic*<2A>'[functional programming language haskell<1F>&Easynchronous message passing<06>%cep<0F>$%programmatic
<EFBFBD>#spacing<0B>"workflow<11>!)random testing<08> ation<06>enc
<0A>!quickcheck<0C>generator<07>enum
<0A>!enumerator<0B>iterator<11>)decision trees<0E>#compilation<13>-statistical data	<09>pertur<0F>%definition 1	<09>bation<17>5statistical database	<09>racket
<0A>!javascript<14>/occurrence typing<08>idiom
<EFBFBD>clojure<07>
blog
<0A>!data space<0B>pagerank<12>
+authority score<08>	salsa<06>lgd<06>prf
<0A>!burstiness<06>les<06>exp<13>-data aggregation<13>-failure detector<15>
1resource discovery<15>1message complexity<0C>primitive<13>~-high reliability
<0A>}!resilience<12>|+gossip protocol<0F>{%flow control<07>zping<07>yswim<14>x/failure detection<0B>wscalable<07>vties
<EFBFBD>uoverlay<13>t-sampling service<0B>sepidemic<0C>rspreading<0F>q%anti-entropy
<0A>p!membership	<09>ogossip<06>ntcp<0F>m%partial view	<09>lrandom<0E>k#block layer<06>jghc<14>i/garbage collector
<EFBFBD>hpointer<0C>gtreadmill<07>fheap<1A>e;generational collection<13>d-train algorithms<1B>c=mobile phone application<06>bhci<11>a)social support<12>`+number of steps<11>_)activity level<07>^dual<15>]1reference counting<0C>\collector<12>[+reference count
0<00>
<01>	<0B>8-SZ<04><02>E5Ujh9-<0E><0E><0E><0E><0E><0E><0E><0E><0E><0E>Mzqg]J:&

<0A>
<0A>
<0A>
<0A><0B>
<0A>
<0A>
<0A>
<0A>
|
m
`
X
N
@
0
 

<0C><0C><0C><0C><0C><0C><0C><0C><0C>x%Q	<02><02><02><02><02><02>f<02><04><04>
<01><04><04>ul<0B>^VJA1'<03><0B><03><0B><03>|<03><03><03><03>h<08><08><08><08><08><08>zb_<04>WM<0B>^D;3'T<07><07><07><07><07><07><07><07><07><07>t<0B>`O:%<06><06><06><06><06><06><06>@="<06><0B><06>2s<02>kaPG>6!-<05><05><05>Z<05>9<05><05><05><05>F<05>w<0F><0F><0F><0F><0F><0F>
<01><0F>{oK
p
g
\
Q
B
0<04>

U	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	n	Q	9	!Q		<02><08><04>		'mathematician<03>invariant<03>gpe<03>/in-depth analysis<03>'impossibility<03>
gnutella
{
mapre<03>
indexing<03>;large-scale application<03>kelips<03>gossip
<01>lookup<03>-interface designi#interactive

inter<00>

intent%
intelligence.int
)%installation<02>#input array<03>#inheritance
HQ'goal position<02>#local state<03><04>+google bigtableu9kinectfusion algorithm<00>+key-value store
 /key cryptosystems<00>'kernel memoryS+kernel functionA	
judge#+joint attention<02>7johnson-lindenstrauss"jocaml
<01>jerr	ject
=!javascriptity<03>itselfW
itmB
iteratorisa<02>#irrelevance<02>ironfleet
<01>!invocation
a#interpreterC/intermediate node<03>%google, inc.s!Elarge-scale software systems<03>gps
w+google's chubby
<01>lsm-trees<03><08>n
gpuc
locality}	mcmcq
gpusflcaj<08>grammar<00>mar<00>mapreduce
!map-reduce
2
malwaremalloc
gmalism<02>'major feature<02>
macroF;machine learning methodM-machine language<00>5
machine intelligence lsok
lshUlruI
lrfuP#low latency
<01>	loto<02>
los!logical<00>
log data
S	lock<00>#local model<
local<02>load timeX)load balancing
<
lkopf@
liveness
<01>-
little knowledge9	lisp<02>
lirQ
linkedin
T+linearizability
+linearisability
`#linear time)linear hashing<00>?line integral convolution<00>
lightings

lifecycle%life science
<01>lie
<01>lgd
lfuRlev<02>les
length n
lemma$lem
%
leak
!leadership
<01>leader
<01>
ldaClceHlcdG	lazy0
laser<02>1language extensionI7language capabilitiesT/lambda expressionv
labels t=labelling<02>%knuth-morris
knapsack<00>kmp
path planning<02>jpass%partial view
<01>Npartial evaluation66paravirtualizationm;parametric polymorphism<02>1parallel operationa
panorama<00>
pagerank	pace
#
owsoverlay
<01>#overfitting1!out-of-bag7)others' action<02>otg<02>osd
goracle<02>9optimistic replication
4?optical flow<02>operating<00>
opera<02>
ologn
[odt<00>
octreeseoch
<01>/occurrence typing
occam<02>
ocaml
<01>1obstacle avoidance<02><04>number of steps
<01>/number of records<00>
nosql
/isoform<04>iotq1inductive learningl7logic and computationjhandlergmagnete;interactive application]+lazy evaluationX7higher-order functionU	glueSispPjseN%joint actionJlocking8)linear algebra2#low-latencyinitiator/locality property	7malicious participant)legacy systems!graph data<03> Cimplementation of mapreduce<03>impala
%immutability<00>%illumination<00>iff<02>
idiomicp<02>
iccibm+i/o2hypertext<00>#hypersphere<03>!hyperspace
"!hyperplane<03>
hyperdex
!	http
<01>
hppGhotspot7hopscotch<00>hop{hol<00>	
hipaa%	hintZ)hindley-milner<02>5high-level operators<03>+high throughput<03>-high reliability
<01>herbivore<03>	heap
<01>hdfzhci
<01>)hashing method<03>!hash table<00>'hash function<00>	hash	hard<02>har
<01>
handling<00>-
hamiltonian pathH	hair<00>h-store


gyroscope`gui<02>
guest4
guage<02>
grid map<02>graphx
v=graphical user interface<02>+
graphical model
graphicj
graph gE+gossip protocol
<01>+google's pregel
ymbeddr:%maximizationB%matrix group<02>
matea1matching algorithm
master
.masking
tmarketing
<01>3
market applications
%S<02>%<00>z<EFBFBD><00><02>-+3EEThe treadmill: real-time garbage collection without motion sickness<07>A simple real-time garbage collection algorithm is presented which does not copy, thereby avoiding some of the problems caused by the asynchronous motion of objects. This in-place "treadmill" garbage collection scheme has approximately the same complexity as other non-moving garbage collectors, thus making it usable in a high-level language implementation where some pointers cannot be traced. The treadmill is currently being used in a Lisp system built in Ada.SIGPLAN Noticesgarbage_collection/2017-09-11T23:06:36.462885012017-09-11T23:06:36.46288501<EFBFBD>,<2C>
]<02>[3GGIncremental Collection of Mature Objects<07>We present a garbage collection algorithm that extends generational scav-enging to collect large older generations (mature objects) non-disruptively. The al-gorithm's approach is to process bounded-size pieces of mature object space at each collection; the subtleties lie in guaranteeing that it eventually collects any and all garbage. The algorithm does not assume any special hardware or operating system support, e.g., for forwarding pointers or protection traps. The algorithm copies objects, so it naturally supports compaction and reclustering.IWMMgarbage_collection/2017-09-11T23:06:36.3862150882017-09-11T23:06:36.386215088<EFBFBD>)<29><00><02>#3GGA LISP garbage-collector for virtual-memory computer systems<07>In this paper a garbage-collection algorithm for list-processing systems which operate within very large virtual memo, ies is described. The object of the algorithm is more the compaction of active storage than the discovery of free storage. Because free storage is never really exhausted, the decision to garbage collect is not easily made; therefore, various criteria of this decision are discussed. Users of list processing are familiar with garbage-collectors of the sort first described by McCarthy [1]. Systems using collectors of this sort run freely until space is nearly exhausted. Then, all execution stops while a marking routine marks every free-storage cell which is reachable by program. Finally, a gathering routine scans the free-storage area, collecting the unmarked cells onto a free-storage list, and unmarking the marked cells. Garbage-collection has always been necessary because the computer's supply of addressable space has always been much less than the total space used during execution of a list-processing program. Garbage-collection makes it possible to reuse the system's limited supply of addressable space. (01). Reproduction in whole or in part is permitted for any purpose of the United States Government. With the coming of virtual-memory systems [2, 3], the problem of limited addressable space is hardly present. In MULTICS, for example, a LISP system might be made to operate with a potential free-storage list of billions of LISP cells. Such a system may run almost endlessly with no need for garbage-collection. As operation proceeds, however, performance degrades. This is because the active-list-storage becomes spread over a larger and larger region of virtual storage, and it becomes increasingly likely that a given reference to this virtual memory will require a reference to secondary storage. Bobrow and Murphy [4] faced a substantially similar problem, but the virtual memory of their system was not yet so large as to be effectively infinite. Many of their strategies for pointer enrichment and for data segmenta-tion are appropriate to an infinite memory system, but their garbage-collector is not. What is needed is a collector whose task is not so much the discovery of free storage as the compaction of active storage. It is especially clear that a routine will not do if its gathering phase must scan all potential storage. The procedure is shown in detail below. Briefly, it operates by dividing the potential storage space into two semispaces. Only one semispace is used for free storage (only one semispaee …Commun. ACMgarbage_collection/2017-09-11T23:06:36.3688259282017-09-11T23:06:36.368825928
<04>
S<08><04>
{<02>WGGEpidemic Algorithms for Replicated Database Maintenance<07>When a database is replicated at many sites, maintaining mutual consistency among the sites in the face of updates is a significant problem. This paper describes several randomized algorithms for distributing updates and driving the replicas toward consistency. The algorithms are very simple and require few guarantees from the underlying communication system, yet they ensure that the effect of every update is eventually reflected in all replicas. The cost and performance of the algorithms are tuned by choosing appropriate distributions in the randomization step. The algorithms are closely analogous to epidemics, and the epidemiology literature aids in understanding their behavior. One of the algorithms has been implemented in the Clearinghouse servers of the Xerox Corporate Internet. solving long-standing problems of high traffic and database inconsistency.PODCgossip/2017-09-11T23:06:36.8139609382017-09-11T23:06:36.813960938<EFBFBD>I<EFBFBD><00><02>E<EFBFBD>AGGHyParView: A Membership Protocol for Reliable Gossip-Based Broadcast<07>Gossip, or epidemic, protocols have emerged as a powerful strategy to implement highly scalable and resilient reliable broadcast primitives. Due to scalability reasons, each participant in a gossip protocol maintains a partial view of the system. The reliability of the gossip protocol depends upon some critical properties of these views, such as degree distribution and clustering coefficient. Several algorithms have been proposed to maintain partial views for gossip protocols. In this paper, we show that under a high number of faults, these algorithms take a long time to restore the desirable view properties. To address this problem, we present HyParView, a new membership protocol to support gossip-based broadcast that ensures high levels of reliability even in the presence of high rates of node failure. The HyParView protocol is based on a novel approach that relies in the use of two distinct partial views, which are maintained with different goals by different strategies.37th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN'07)gossip/2017-09-11T23:06:36.7100849612017-09-11T23:06:36.710084961<EFBFBD>)<29><00>'<02>	3GGParallel generational-copying garbage collection with a block-structured heap<07>We present a parallel generational-copying garbage collector implemented for the Glasgow Haskell Compiler. We use a block-structured memory allocator, which provides a natural granularity for dividing the work of GC between many threads, leading to a simple yet effective method for parallelising copying GC. The results are encouraging: we demonstrate wall-clock speedups of on average a factor of 2 in GC time on a commodity 4-core machine with no programmer intervention, compared to our best sequential GC.ISMMgarbage_collection/2017-09-11T23:06:36.5267819822017-09-11T23:06:36.526781982
	<08>	<00><02>
/<02>%=GGBimodal Multicast<07>There are many methods for making a multicast protocol &#8220;reliable.&#8221; At one end of the spectrum, a reliable multicast protocol might offer tomicity guarantees, such as all-or-nothing delivery, delivery ordering, and perhaps additional properties such as virtually synchronous addressing. At the other are protocols that use local repair to overcome transient packet loss in the network, offering &#8220;best effort&#8221; reliability. Yet none of this prior work has treated stability of multicast delivery as a basic reliability property, such as might be needed in an internet radio, television, or conferencing application. This article looks at reliability with a new goal: development of a multicast protocol which is reliable in a sense that can be rigorously quantified and  includes throughput stability guarantees. We characterize this new protocol as a &#8220;bimodal multicast&#8221; in reference to its reliability model, which corresponds to a family of bimodal probability distributions. Here, we introduce the protocol, provide a theoretical analysis of its behavior, review experimental results, and discuss some candidate applications. These confirm that bimodal multicast is reliable, scalable, and that the protocol provides remarkably stable delivery throughput.ACM Trans. Comput. Syst.gossip/2017-09-11T23:06:37.0699108892017-09-11T23:06:37.069910889<EFBFBD>m<EFBFBD><00>K<02>y!GGThe Peer Sampling Service: Experimental Evaluation of Unstructured Gossip-Based Implementations<07>In recent years, the gossip-based communication model in large-scale distributed systems has become a general paradigm with important applications which include information dissemination, aggrega-tion, overlay topology management and synchronization. At the heart of all of these protocols lies a fundamental distributed abstraction: the peer sampling service. In short, the aim of this service is to provide every node with peers to exchange information with. Analytical studies reveal a high reliability and efficiency of gossip-based protocols, under the (often implicit) assumption that the peers to send gossip messages to are selected uniformly at random from the set of all nodes. In practice—instead of requiring all nodes to know all the peer nodes so that a random sample could be drawn—a scalable and efficient way to implement the peer sampling service is by constructing and maintaining dynamic unstructured overlays through gossiping membership information itself. This paper presents a generic framework to implement reliable and efficient peer sampling services. The framework generalizes existing approaches and makes it easy to introduce new ones. We use this framework to explore and compare several implementations of our abstraction. Through extensive experimental analysis, we show that all of them lead to different peer sampling services none of which is uniformly random. This clearly renders traditional theoretical approaches invalid, when the underlying peer sampling service is based on a gossip-based scheme. Our observations also help explain important differences between design choices of peer sampling algorithms, and how these impact the reliability of the corresponding service.Middlewaregossip/2017-09-11T23:06:36.9866020512017-09-11T23:06:36.986602051
<02><0B>0<02><00>o<EFBFBD><00><02>5GGEfficient reconciliation and flow control for anti-entropy protoc
i<02>
GGLarge-Scale Newscast Computing on the Internet<07>This paper introduces the newscast model of computation for large-scale computing on the Internet. The engine realizing this model is a lazy fully distributed information propagation protocol among the participants which is responsible for membership management and communication. It maintains a constantly changing communication graph over the participants. This graph has useful emergent properties like small diameter and sufficiently random structure without deploying special purpose protocols to achieve these properties. For adding a new participant only the address of an arbitrary member is needed and for removal no action is necessary. We provide theoretical and empirical evidence that—besides being simple and lightweight—our newscast computing engine is extremely scalable and robust. We also suggest some interesting application areas including information dissemination, monitoring of large systems, resource sharing and efficient multi-casting.gossip/2017-09-11T23:06:37.1503210452017-09-11T23:06:37.150321045
	F<0B>	F<00>+<2B>
]<02>y
GGA Gossip-Style Failure Detection Service<07>Failure Detection is valuable for system management, replication, load balancing , and other distributed services. To date, Failure Detection Services scale badly in the number of members that are being monitored. This paper describes a new protocol based on gossiping that does scale well and provides timely detection. We analyze the protocol, and then extend it to discover and leverage the underlying network topology for much improved resource utilization. We then combine it with another protocol, based on broadcast, that is used to handle partition failures.gossip/2017-09-11T23:06:37.4515729982017-09-11T23:06:37.451572998<EFBFBD><07>=<02>+<2B>1GGEpidemic Broadcast Trees<07>There is an inherent trade-off between epidemic and deterministic tree-based broadcast primitives. Tree-based approaches have a small message complexity in steady-state but are very fragile in the presence of faults. Gossip, or epidemic, protocols have a higher message complexity but also offer much higher resilience. This paper proposes an integrated broadcast scheme that combines both approaches. We use a low cost scheme to build and maintain broadcast trees embedded on a gossip-based overlay. The protocol sends the message payload preferably via tree branches but uses the remaining links of the gossip overlay for fast recovery and expedite tree healing. Experimental evaluation presented in the paper shows that our new strategy has a low overhead and that is able to support large number of faults while maintaining a high reliability.2007 26th IEEE International Symposium on Reliable Distributed Systems (SRDS 2007)gossip/2017-09-11T23:06:37.3923540042017-09-11T23:06:37.392354004

<04><04><00>&<26>
K<02>yGGThe Φ Accrual Failure Detector<07>Detecting failures is a fundamental issue for fault-tolerance in distributed systems. Recently, many people have come to realize that failure detection ought to be provided as some form of generic service, similar to IP address lookup or time synchronization. However, this has not been successful so far. One of the reasons is the difficulty to satisfy several application requirements simultaneously when using classical failure detectors. We present a novel abstraction, called accrual failure detectors, that emphasizes flexibility and expressiveness and can serve as a basic building block to implementing failure detectors in distributed systems. Instead of providing information of a boolean nature (trust vs. suspect), accrual failure detectors output a suspicion level on a continuous scale. The principal merit of this approach is that it favors a nearly complete decoupling between application requirements and the monitoring of the environment. In this paper, we describe an implementation of such an accrual failure detector, that we call the ϕ failure detector. The particularity of the ϕ failure detector is that it dynamically adjusts to current network conditions the scale on which the suspicion level is expressed. We analyzed the behavior of our ϕ failure detector over an intercontinental communication link during several days. Our experimental results show that our ϕ failure detector performs equally well as other known adaptive failure detection mechanisms, with an improved flexibility. I. INTRODUCTION It is well-known that failure detection constitutes a fundamental building block for ensuring fault tolerance in distributed systems. For this reason, many people have been advocating that failure detection should be provided as a service [1]–[5], similar to IP address lookup (DNS) or time synchronization (e.g., NTP). Unfortunately, in spite of important technical breakthroughs, this view has met little success so far. We believe that one of the main reasons is that the conventional boolean interaction (i.e., trust vs. suspect) makes it difficult to meet the requirements of several distributed applications running simultaneously. For this reason, we advocate a different abstraction that helps decoupling application requirements from issues related to the underlying system. It is well-known that there exists an inherent tradeoff between (1) conservative failure detection (i.e., reducing the risk of wrongly suspecting a running process), and (2) aggressive failure detection (i.e., quickly detecting the occurrence of a real crash). There exists a continuum of valid choices between these two extremes, and what defines an appropriate choice is strongly related to application requirements. …SRDSgossip/2017-09-11T23:06:37.5015358892017-09-11T23:06:37.501535889
<04>
:]<04><00>Y<EFBFBD>!
Y<02>19GGInformation-based models for ad hoc IR<07>We introduce in this paper the family of information-based models for <i>ad hoc</i> information retrieval. These models draw their inspiration from a long-standing hypothesis in IR, namely the fact that the difference in the behaviors of a word at the document and collection levels brings information on the significance of the word for the document. This hypothesis has been exploited in the 2-Poisson mixture models, in the notion of eliteness in BM25, and more recently in DFR models. We show here that, combined with notions related to burstiness, it can lead to simpler and better models.SIGIRinformation_retrieval/2017-09-11T23:06:37.7713569342017-09-11T23:06:37.771356934<EFBFBD>Y<EFBFBD> 
}<02>
9GGThe PageRank Citation Ranking: Bringing Order to the Web<07>The importance of a Web page is an inherently subjective matter, which depends on the readers interests, knowledge and attitudes. But there is still much that can be said objectively about the relative importance of Web pages. This paper describes PageRank, a method for rating Web pages objectively and mechanically, eeectively measuring the human interest and attention devoted to them. We compare PageRank to an idealized random Web surfer. We show how to eeciently compute PageRank for large numbers of pages. And, we showhow to apply PageRank to search and to user navigation.information_retrieval/2017-09-11T23:06:37.7392980962017-09-11T23:06:37.739298096<EFBFBD>B<EFBFBD>
5<02>-9EEIDF for Word N-grams<07>Inverse Document Frequency (IDF) is widely accepted term weighting scheme whose robustness is supported by many theoretical justifications. However, applying IDF to word N-grams (or simply N-grams) of any length without relying on heuristics has remained a challenging issue. This article describes a theoretical extension of IDF to handle N-grams. First, we elucidate the theoretical relationship between IDF and information distance, a universal metric defined by the Kolmogorov complexity. Based on our understanding of this relationship, we propose N-gram IDF, a new IDF family that gives fair weights to words and phrases of any length. Based only on the magnitude relation of N-gram IDF weights, dominant N-grams among overlapping N-grams can be determined. We also propose an efficient method to compute the N-gram IDF weights of all N-grams by leveraging the enhanced suffix array and wavelet tree. Because the exact computation of N-gram IDF provably requires significant computational cost, we modify it to a fast approximation method that can estimate weight errors analytically and maintain application-level performance. Empirical evaluations with unsupervised/supervised key term extraction and web search query segmentation with various experimental settings demonstrate the robustness and language-independent nature of the proposed N-gram IDF.TOISinformation_retrieval/2017-09-11T23:06:37.585510012017-09-11T23:06:37.58551001
ll<00><0F>#
U<02>+1GGPractical Optional Types for Clojure<07>Typed Clojure is an optional type system for Clojure, a dynamic language in the Lisp family that targets the JVM. Typed Clojure's type system build on the design of Typed Racket, repurposing in particular occurrence typing, an approach to statically reasoning about predicate tests. However, in adapting the type system to Clo-jure, changes and extensions are required to accommodate additional language features and idioms used by Clojure programmers. In this paper, we describe Typed Clojure and present these type system extensions, focusing on three features widely used in Clo-jure. First, Java interoperability is central to Clojure's mission but introduces challenges such as ubiquitous null; Typed Clojure handles Java interoperability while ensuring the absence of null-pointer exceptions in typed programs. Second, Clojure programmers idiomatically use immutable dictionaries for data structures; Typed Clojure handles this in the type system with multiple forms of heterogeneous dictionary types. Third, multimethods provide extensi-ble operations, and their Clojure semantics turns out to have a surprising synergy with the underlying occurrence typing framework. We provide a formal model of the Typed Clojure type system incorporating these and other features, with a proof of soundness. Additionally, Typed Clojure is now in use by numerous corporations and developers working with Clojure, and we report on experience with the system and its lessons for the future. The popularity of dynamically-typed languages in software development , combined with a recognition that types often improve programmer productivity, software reliability, and performance, has led to the recent development of a wide variety of optional and gradual type systems aimed at checking existing programs written in existing languages. These include Microsoft's TypeScript for JavaScript, Facebook's Hack for PHP and Flow for JavaScript, and MyPy for Python among the optional systems, and Typed Racket, Reticulated Python, and GradualTalk among gradually-typed systems. 1 One key lesson of these systems, indeed a lesson known to early developers of optional type systems such as StrongTalk, is that type systems for existing languages must be designed to work with the features and idioms of the target language. Often this takes the form of a core language, be it of functions or classes and objects, together with extensions to handle distinctive language features. We synthesize these lessons to present Typed Clojure, an optional type system for Clojure. Typed Clojure builds on the core type checking approach of Typed Racket, an existing gradual type system for Racket. However, Typed Clojure extends …ESOPlanguages/clojure/2017-09-11T23:06:38.0478491212017-09-11T23:06:38.047849121<EFBFBD>}<7D>"
q<02>c9GGAuthoritative Sources in a Hyperlinked Environment<07>The network structure of a hyperlinked environment can be a rich source of information about the content of the environment, provided we have effective means for understanding it. We develop a set of algorithmic tools for extracting information from the link structures of such environments, and report on experiments that demonstrate their effectiveness in a variety of context on the World Wide Web. The central issue we address within our framework is the distillation of broad search topics, through the discovery of &#8220;authorative&#8221; information sources on such topics. We propose and test an algorithmic formulation of the notion of authority, based on the relationship between a set of relevant authoritative pages and the set of &#8220;hub pages&#8221; that join them together in  the link structure. Our formulation has connections to the eigenvectors of certain matrices associated with the link graph; these connections in turn motivate additional heuristrics for link-based analysis.SODAinformation_retrieval/2017-09-11T23:06:37.9623029792017-09-11T23:06:37.962302979
!<0B>}<07><04>
s!<00>N<EFBFBD>)<00>!<02>_1EEBreadth-first numbering: lessons from a small exercise in algorithm design<07>Every programmer has blind spots. Breadth-first numbering is an interesting toy problem that exposes a blind spot common to many---perhaps most---functional programmers.ICFPlanguages/clojure/2017-09-11T23:06:38.612770022017-09-11T23:06:38.61277002<EFBFBD>#<23>(<00><02>1GGQuickCheck: a lightweight tool for random testing of Haskell programs<07>Quick Check is a tool which aids the Haskell programmer in formulating and testing properties of programs. Properties are described as Haskell functions, and can be automatically tested on random input, but it is also possible to define custom test data generators. We present a number of case studies, in which the tool was successfully used, and also point out some pitfalls to avoid. Random testing is especially suitable for functional programs because properties can be stated at a fine grain. When a function is built from separately tested components, then random testing suffices to obtain good coverage of the definition under test.ICFPlanguages/clojure/2017-09-11T23:06:38.5041120612017-09-11T23:06:38.504112061<EFBFBD>[<5B>'
9<02>c1GGBacktracking iterators<07>Iterating over the elements of an abstract collection is usually done in ML using a fold-like higher-order function provided by the data structure. This article discusses a different paradigm of iteration based on purely functional, immutable cursors. Contrary to fold-like iterators, the iteration can be cleanly interrupted at any step. Contrary to imperative cursors (such as those found in C++ and Java libraries) it is possible to backtrack the iterator to a previous step. Several ways to iterate over binary trees are examined and close links with G&#233;rard Huet's <i>Zipper</i> are established. Incidentally, we show the well-known two-lists implementation of functional queues arising from a <i>Zipper</i>-based breadth-first traversal.MLlanguages/clojure/2017-09-11T23:06:38.4455300292017-09-11T23:06:38.445530029<EFBFBD><00>&	W
1GGQuickCheck Testing for Fun and Profit<07>PADLlanguages/clojure/2017-09-11T23:06:38.4015681152017-09-11T23:06:38.401568115<EFBFBD>v<EFBFBD>%
o<02>c1GGCompiling pattern matching to good decision trees<07>We address the issue of compiling ML pattern matching to compact and efficient decisions trees. Traditionally, compilation to decision trees is optimized by (1) implementing decision trees as dags with maximal sharing; (2) guiding a simple compiler with heuristics. We first design new heuristics that are inspired by necessity, a concept from lazy pattern matching that we rephrase in terms of decision tree semantics. Thereby, we simplify previous semantic frameworks and demonstrate a straightforward connection between necessity and decision tree runtime efficiency. We complete our study by experiments, showing that optimizing compilation to decision trees is competitive with the optimizing match compiler of Le Fessant and Maranget (2001).MLlanguages/clojure/2017-09-11T23:06:38.2713439942017-09-11T23:06:38.271343994<EFBFBD><05>$
5<02>33GGDifferential Privacy<07>In 1977 Dalenius articulated a desideratum for statistical databases: nothing about an individual should be learnable from the database that cannot be learned without access to the database. We give a general impossibility result showing that a formalization of Dalenius' goal along the lines of semantic security cannot be achieved. Contrary to intuition, a variant of the result threatens the privacy even of someone not in the database. This state of affairs suggests a new measure, differential privacy, which, intuitively, captures the increased risk to one's privacy incurred by participating in a database. The techniques developed in a sequence of papers [8, 13, 3], culminating in those described in [12], can achieve any desired level of privacy under this measure. In many cases, extremely accurate information about the database can be provided while simultaneously ensuring very high levels of privacy.ICALPinformation_theory/2017-09-11T23:06:38.1927958982017-09-11T23:06:38.192795898

k	<09>E<02>
k<00>*<2A>-
c<02>S1GGA history of Haskell: being lazy with class<07>This paper describes the history of Haskell, including its genesis and principles, technical contributions, implementations and tools, and applications and impact.HOPLlanguages/haskell/2017-09-11T23:06:39.0653601072017-09-11T23:06:39.065360107<EFBFBD>(<28>,
3<02>
/GGA history of Erlang<07>Erlang was designed for writing concurrent programs that "run forever." Erlang uses concurrent processes to structure the program. These processes have no shared memory and communicate by asynchronous message passing. Erlang processes are lightweight and belong to the language, not the operating system. Erlang has mechanisms to allow programs to change code "on the fly" so that programs can evolve and change as they run. These mechanisms simplify the construction of software for implementing non-stop systems.
 This paper describes the history of Erlang. Material for the paper comes from a number of different sources. These include personal recollections, discussions with colleagues, old newspaper articles and scanned copies of Erlang manuals, photos and computer listings and articles posted to Usenet mailing lists.HOPLlanguages/erlang/2017-09-11T23:06:38.9075449222017-09-11T23:06:38.907544922<EFBFBD>
<0A>+
y<02>o+/GGMulticore profiling for Erlang programs using percept2<07>Erlang is a functional programming language with built-in support for concurrency based on share-nothing processes and asynchronous message passing. The design of Erlang makes it suitable for writing concurrent and parallel applications, taking full advantage of the computing power of modern multicore machines. However many existing Erlang applications are sequential, in need of parallelisation.
 In this paper, we present the Erlang concurrency profiling tool Percept2,and demonstrate how the information provided by it can help the user to explore the potential parallelism in an Erlang application and how the system performs on the Erlang multicore system. Percept2 thus allows users improve the performance and scalability of their applications.Erlang Workshoplanguages/erlang/2017-09-11T23:06:38.7957749022017-09-11T23:06:38.795774902<EFBFBD>&<26>*
y<02>UGGProgrammatic and direct manipulation, together at last<07>Direct manipulation interfaces and programmatic systems have distinct and complementary strengths. The former provide intuitive, immediate visual feedback and enable rapid prototyping, whereas the latter enable complex, reusable abstractions. Unfortunately, existing systems typically force users into just one of these two interaction modes. We present a system called Sketch-n-Sketch that integrates programmatic and direct manipulation for the particular domain of Scalable Vector Graphics (SVG). In Sketch-n-Sketch, the user writes a program to generate an output SVG canvas. Then the user may directly manipulate the canvas while the system immediately infers a program update in order to match the changes to the output, a workflow we call live synchronization. To achieve this, we propose (i) a technique called trace-based program synthesis that takes program execution history into account in order to constrain the search space and (ii) heuristics for dealing with ambiguities. Based on our experience with examples spanning 2,000 lines of code and from the results of a preliminary user study, we believe that Sketch-n-Sketch provides a novel workflow that can augment traditional programming systems. Our approach may serve as the basis for live synchronization in other application domains, as well as a starting point for yet more ambitious ways of combining programmatic and direct manipulation.PLDIlanguages/domain-specific-languages/2017-09-11T23:06:38.6634440922017-09-11T23:06:38.663444092
<00><0C>~<00><00>1<EFBFBD>0
u<02>O
9GGTesting ecological models: the meaning of validation<07>The ecological literature reveals considerable confusion about the meaning of validation in the context of simulation models. The confusion arises as much from semantic and philosophical considerations as from the selection of validation procedures. Validation is not a procedure for testing scientific theory or for certifying the 'truth' of current scientific understanding, nor is it a required activity of every modelling project. Validation means that a model is acceptable for its intended use because it meets specified performance requirements. Before validation is undertaken, (1) the purpose of the model, (2) the performance criteria, and (3) the model context must be specified. The validation process can be decomposed into several components: (1) operation, (2) theory, and (3) data. Important concepts needed to understand the model evaluation process are verification, calibration, validation, credibility, and qualification. These terms are defined in a limited technical sense applicable to the evaluation of simulation models, and not as general philosophical concepts. Different tests and standards are applied to the operational, theoretical, and data components. The operational and data components can be validated; the theoretical component cannot. The most common problem with ecological and environmental models is failure to state what the validation criteria are. Criteria must be explicitly stated because there are no universal standards for selecting what test procedures or criteria to use for validation. A test based on comparison of simulated versus observed data is generally included whenever possible. Because the objective and subjective components of validation are not mutually exclusive, disagreements over the meaning of validation can only be resolved by establishing a convention.logic_and_programming/2017-09-11T23:06:39.6138391112017-09-11T23:06:39.613839111<EFBFBD>	<09>/
s<02>]19GGPurely functional lazy nondeterministic programming<07>Functional logic programming and probabilistic programming have demonstrated the broad benefits of combining laziness (non-strict evaluation with sharing of the results) with non-determinism. Yet these benefits are seldom enjoyed in functional programming, because the existing features for non-strictness, sharing, and non-determinism in functional languages are tricky to combine.
 We present a practical way to write purely functional lazy non-deterministic programs that are efficient and perspicuous. We achieve this goal by embedding the programs into existing languages (such as Haskell, SML, and OCaml) with high-quality implementations, by making choices lazily and representing data with non-deterministic components, by working with custom monadic data types and search strategies, and by providing equational laws for the programmer to reason about their code.J. Funct. Program.logic_and_programming/2017-09-11T23:06:39.2150791022017-09-11T23:06:39.215079102<EFBFBD>q<EFBFBD>.
g<02>I+/GGOn the scalability of the Erlang term storage<07>The Erlang Term Storage (ETS) is an important component of the Erlang runtime system, especially when parallelism enters the picture, as it provides an area where processes can share data. It is therefore important that ETS's implementation is efficient, flexible, but also as scalable as possible. In this paper we document and describe the current implementation of ETS in detail, discuss the main data structures that support it, and present the main points of its evolution across Erlang/OTP releases. More importantly, we measure the scalability of its implementations, the effects of its tuning options, identify bottlenecks, and suggest changes and alternative designs that can improve both its performance and its scalability.Erlang Workshoplanguages/erlang/2017-09-11T23:06:39.1534780272017-09-11T23:06:39.153478027
9
<EFBFBD>
2<06>9<00>)<29>5<00>?<02>u/GGConditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data<07>We present conditional random fields, a framework for building probabilistic models to segment and label sequence data. Conditional random fields offer several advantages over hidden Markov models and stochastic grammars for such tasks, including the ability to relax strong independence assumptions made in those models. Conditional random fields also avoid a fundamental limitation of maximum entropy Markov models (MEMMs) and other discrimi-native Markov models based on directed graph-ical models, which can be biased towards states with few successor states. We present iterative parameter estimation algorithms for conditional random fields and compare the performance of the resulting models to HMMs and MEMMs on synthetic and natural-language data.ICMLmachine_learning/2017-09-11T23:06:40.3000939942017-09-11T23:06:40.300093994<EFBFBD>H<EFBFBD>4
M<02>mO/GGTop 10 algorithms in data mining<07>This paper presents the top 10 data mining algorithms identified by the IEEE International Conference on Data Mining (ICDM) in December 2006: C4.5, k-Means, SVM, Apriori, EM, PageRank, AdaBoost, kNN, Naive Bayes, and CART. These top 10 algorithms are among the most influential data mining algorithms in the research community. With each algorithm, we provide a description of the algorithm, discuss the impact of the algorithm, and review current and further research on the algorithm. These 10 algorithms cover classification, clustering, statistical learning, association analysis, and link mining, which are all among the most important topics in data mining research and development.Knowledge and Information Systemsmachine_learning/2017-09-11T23:06:40.1463469242017-09-11T23:06:40.146346924~<7E>3	]

/GGThe Fast Johnson-lindenstrauss Transform<07>machine_learning/2017-09-11T23:06:40.0619599612017-09-11T23:06:40.061959961<EFBFBD>a<EFBFBD>2
)<02>e-/GGRandom Forests<07>Random forests are a combination of tree predictors such that each tree depends on the values of a random vector sampled independently and with the same distribution for all trees in the forest. The generalization error for forests converges a.s. to a limit as the number of trees in the forest becomes large. The generalization error of a forest of tree classifiers depends on the strength of the individual trees in the forest and the correlation between them. Using a random selection of features to split each node yields error rates that compare favorably to Adaboost (Y. Freund & R. Schapire, Machine Learning: Proceedings of the Thirteenth International conference, ***, 148–156), but are more robust with respect to noise. Internal estimates monitor error, strength, and correlation and these are used to show the response to increasing the number of features used in the splitting. Internal estimates are also used to measure variable importance. These ideas are also applicable to regression.Machine Learningmachine_learning/2017-09-11T23:06:39.9340800782017-09-11T23:06:39.934080078<EFBFBD>d<EFBFBD>1
q<02>1#/EEA few useful things to know about machine learning<07>Tapping into the "folk knowledge" needed to advance machine learning applications.Commun. ACMmachine_learning/2017-09-11T23:06:39.842757082017-09-11T23:06:39.84275708
k<00><0F><0F><0F>}[?<0E><0E><0E><0E>pF%
<0A>
<0A>
<0A>
n
>
<0C><0C><0C>}a/<0B><0B><0B>lI"
<EFBFBD>
<EFBFBD>
<EFBFBD>
l
R
:
	<09>	<09>	<09>	<09>	a	A	<08><08><08><08>c9<07><07><07>qJ"<06><06><06><06>bD.<05><05><05><05>h;<04><04><04><04>|[8<03><03><03><03>^@<02><02><02><02>f@
<01>
<01>
<01>
<01>
`
8
<00><1B>#
Amin VahdatAminVahdat!<21>)
Luis RodriguezLuisRodriguez%<25>
-
J.michael AshleyJ.michaelAshley#<23>+
Gregor KiczalesGregorKiczales<1F>'
Conal ElliottConalElliott-<2D>~5
'Daniel Winograd-CortDanielWinograd-Cort<1F>}'
Stephen ChongStephenChong!<21>|)
Evan CzaplickiEvanCzaplicki<1F>{'
John PetersonJohnPeterson#<23>z+
Antony CourtneyAntonyCourtney!<21>y)
Henrik NilssonHenrikNilsson<19>x!
Walid TahaWalidTaha<1D>w%
Zhanyong WanZhanyongWan/<2F>v7%
Massimiliano GiacominMassimilianoGiacomin#<23>u+
Martin CaminadaMartinCaminada<1F>t'
Pietro BaroniPietroBaroni<1B>s#
Urs HölzleUrsHölzle<1F>r'
Bay-Wei ChangBay-WeiChang<1B>q#
David UngarDavidUngar!<21>p)
Craig ChambersCraigChambers'<27>o/
Günther KnoblichGüntherKnoblich%<25>n-
Harold BekkeringHaroldBekkering!<21>m)
Natalie SebanzNatalieSebanz <20>l)David D. ClarkDavidD.Clark<1E>k'David P. ReedDavidP.Reed&<26>j/Jerome H. SaltzerJeromeH.Saltzer<19>i!
Jan LahodaJanLahoda<17>h
Danny DigDannyDig<1F>g'
Lyle FranklinLyleFranklin<19>f!
Alex GyoriAlexGyori<1F>e'
Ross PatersonRossPaterson*<2A>d3Maarten M. FokkingaMaartenM.Fokkinga<1B>c#
Erik MeijerErikMeijer<1F>b'
Andrew TuckerAndrewTucker<1D>a%
Daniel PriceDanielPrice#<23>`+
Andrew WarfieldAndrewWarfield<17>_
Ian PrattIanPratt#<23>^+
!Rolf NeugebauerRolfNeugebauer<13>]
Alex HoAlexHo<1B>\#
Keir FraserKeirFraser!<21>[)
Boris DragovicBorisDragovic<1B>Z#
Paul BarhamPaulBarham&<26>Y/Robert N M WatsonRobertN MWatson'<27>X/%
Poul-Henning KampPoul-HenningKamp(<28>W1Austin T. ClementsAustinT.Clements%<25>V-
Philippas TsigasPhilippasTsigas$<24>U-Nhan Nguyen DangNhanNguyenDang#<23>T+
!Bapi ChatterjeeBapiChatterjee0<65>S9)John M. Mellor-CrummeyJohnM.Mellor-Crummey<1D>R%
Chaoran YangChaoranYang"<22>Q+Thomas R. GrossThomasR.Gross'<27>P/
Kornilios KourtisKorniliosKourtis'<27>O/
Ioannis KoltsidasIoannisKoltsidas#<23>N+
Jonas PfefferleJonasPfefferle!<21>M)
Patrick StuediPatrickStuedi#<23>L+
Bernard MetzlerBernardMetzler#<23>K+
Nikolas IoannouNikolasIoannou#<23>J+
Animesh TrivediAnimeshTrivedi<1F>I'
Michael WelzlMichaelWelzl<1D>H%
Gareth TysonGarethTyson#<23>G+
Yehia El-KhatibYehiaEl-Khatib(<28>F1Angela Demke BrownAngelaDemkeBrown$<24>E-Paul E. MckenneyPaulE.Mckenney <20>D)Thomas E. HartThomasE.Hart<17>C
R. ShireyR.Shirey!<21>B)
#D. SchmalstiegD.Schmalstieg<15>A
B. KainzB.Kainz<17>@
M. KenzelM.Kenzel!<21>?)
#M. SteinbergerM.Steinberger*<2A>>3!J. A. M. VermaserenJ.A. M.Vermaseren"<22>=+John C. CollinsJohnC.Collins<1D><%
Jeff BonwickJeffBonwick<1D>;%
Sunil ShuklaSunilShukla$<24>:-David S. WishartDavidS.Wishart <20>9)Joseph A. CruzJosephA.Cruz!<21>8)
Ryan CulpepperRyanCulpepper%<25>7-
Jonathan BorweinJonathanBorwein%<25>6-
Lennart BerggrenLennartBerggren,<2C>55Robert Bruce FindlerRobertBruceFindler<1D>4%
Jay MccarthyJayMccarthy/<2F>37
'Shriram KrishnamurthiShriramKrishnamurthi<19>2!
Arjun GuhaArjunGuha&<26>1/Gregory H. CooperGregoryH.Cooper#<23>0+
Vladimir VapnikVladimirVapnik!<21>/)
Corinna CortesCorinnaCortes!<21>.)
Keith PlayfordKeithPlayford'<27>-/
Jonathan BachrachJonathanBachrach-<2D>,5
#Emmanuel DellandréaEmmanuelDellandréa<1D>+%
Yoann BaveyeYoannBaveye%<25>*-
Fernando PereiraFernandoPereira#<23>)+
Andrew MccallumAndrewMccallum$<24>(-John D. LaffertyJohnD.Lafferty<1F>''
Dan SteinbergDanSteinberg<1E>&'David J. HandDavidJ.Hand'<27>%/
Michael SteinbachMichaelSteinbach<1D>$%
Zhi-Hua ZhouZhi-HuaZhou<1C>#%Philip S. YuPhilipS.Yu<15>"
Bing LiuBingLiu <20>!)Angus F. M. NgAngusF. M.Ng.<2E> 7Geoffrey J. MclachlanGeoffreyJ.Mclachlan!<21>)
Hiroshi MotodaHiroshiMotoda<19>!
Qiang YangQiangYang<1F>'
Joydeep GhoshJoydeepGhosh"<22>+J. Ross QuinlanJ.RossQuinlan<1B>#
Vipin KumarVipinKumar<19>!
Xindong WuXindongWu!<21>)
John ThickstunJohnThickstun

%%
q<02>)
/GGAutomatic prediction of emotions induced by movies<07>N before have movies been as easily accessible to viewers, who can enjoy anywhere the almost unlimited potential of movies for inducing emotions. Thus, knowing in advance the emotions that a movie is likely to elicit to its viewers could help to improve the accuracy of content delivery, video indexing or even summarization. However, transferring this expertise to computers is a complex task due in part to the subjective nature of emotions. The present thesis work is dedicated to the automatic prediction of emotions induced by movies based on the intrinsic properties of the audiovisual signal. To computationally deal with this problem, a video dataset annotated along the emotions induced to viewers is needed. However, existing datasets are not public due to copyright issues or are of a very limited size and content diversity. To answer to this specific need, this thesis addresses the development of the LIRIS-ACCEDE dataset. The advantages of this dataset are threefold: (1) it is based on movies under Creative Commons licenses and thus can be shared without infringing copyright, (2) it is composed of 9,800 good quality video excerpts with a large content diversity extracted from 160 feature films and short films, and (3) the 9,800 excerpts have been ranked through a pair-wise video comparison protocol along the induced valence and arousal axes using crowdsourcing. The high inter-annotator agreement reflects that annotations are fully consistent, despite the large diversity of raters’ cultural backgrounds. Three other experiments are also introduced in this thesis. First, affective ratings were collected for a subset of the LIRIS-ACCEDE dataset in order to cross-validate the crowdsourced annotations. The affective ratings made also possible the learning of Gaussian Processes for Regression, modeling the noisiness from measurements, to map the whole ranked LIRIS-ACCEDE dataset into the 2D valence-arousal affective space. Second, continuous ratings for 30 movies were collected in order develop temporally relevant computational models. Finally, a last experiment was performed in order to collect continuous physiological measurements for the 30 movies used in the second experiment. The correlation between both modalities strengthens the validity of the results of the experiments. Armed with a dataset, this thesis presents a computational model to infer the emotions induced by movies. The framework builds on the recent advances in deep learning and takes into account the relationship between consecutive scenes. It is composed of two fine-tuned Convolutional Neural Networks. One is dedicated to the visual modality and uses as input crops of key frames extracted from video segments, while the second one is dedicated to the audio modality through the use of audio spectrograms. The activations of the last fully connected layer of both networks are con-machine_learning/2017-09-11T23:06:40.3464990232017-09-11T23:06:40.346499023

<01><05>
<01><00>|<7C>8
;<02>	-/GGSupport-vector networks<07>Thesupport-vector network is a new learning machine for two-group classification problems. The machine conceptually implements the following idea: input vectors are non-linearly mapped to a very high-dimension feature space. In this feature space a linear decision surface is constructed. Special properties of the decision surface ensures high generalization ability of the learning machine. The idea behind the support-vector network was previously implemented for the restricted case where the training data can be separated without errors. We here extend this result to non-separable training data. High generalization ability of support-vector networks utilizing polynomial input transformations is demonstrated. We also compare the performance of the support-vector network to various classical learning algorithms that all took part in a benchmark study of Optical Character Recognition.Machine Learningmachine_learning/2017-09-11T23:06:40.5418139652017-09-11T23:06:40.541813965<EFBFBD>x<EFBFBD>7
Y<02>
GGD-Expressions: Lisp Power, Dylan Style<07>1 Abstract This paper aims to demonstrate that it is possible for a language with a rich, conventional syntax to provide Lisp-style macro power and simplicity. We describe a macro system and syntax manipulation toolkit designed for the Dylan programming language that meets, and in some areas exceeds, this standard. The debt to Lisp is great, however, since although Dylan has a conventional algebraic syntax, the approach taken to describe and represent that syntax is distinctly Lisp-like in philosophy. 2 Introduction The ability to extend a programming language with new constructs is a valuable tool. With it, system designers can grow a language towards their problem domain and enhance productivity and ease of maintenance. A macro system provides this capability in a portable, high-level fashion by allowing new constructs to be implemented in terms of existing ones via programmer-defined source-to-source transformations. Beyond the above, the ability to read, write, and easily manipulate the syntax of a language from within that language can be especially powerful. It can allow the full language to be brought to bear when implementing macros. It can provide a convenient means of saving and restoring structured data in text form. It can form the basis of code analysis tools and be the starting point for experiments with new language processors or into modified language semantics. Lisp is the only language family (cf [9], [10]) that has succeeded in providing integrated macro systems along with simple and powerful syntax manipulation tools like these. They are considered one of Lisp's unique strengths, perhaps even the most important and distinctive feature of the language. But the key to their viability in Lisp is the simplicity and regularity of its syntax. Recognizing their utility, attempts have been made to provide powerful macro facilities in languages with more conventional syntaxes like those of C or Pascal, but in comparison with what Lisp provides, the solutions have been restrictive, difficult to explain and use, or both. None have been standardized. Further, the utility of syntax manipulation tools independent of the macroex-pansion process is typically forgotten. This paper aims finally to demonstrate that it is possible for a language with a richer, more conventional syntax to provide Lisp-style macro power and simplicity. We describe a macro system and syntax manipulation toolkit designed for the Dylan programming language (cf [13], [7]) that meets our goals as well as, if not better than, those commonly …macros/2017-09-11T23:06:40.4014399412017-09-11T23:06:40.401439941
b<00>
<01>
mG<07><07><07><07><07><07>s	<09>	<09><08>	<09>	<09>	<09>	p	^
<01>
<01>
<01>P=<02>	z<02><02><06>+<02><06>	<06><06><06><06>hQ9%<08><05><05><05><05><05><05>|fSB*<04><04><04><04><04><04><04>~nL<0F><0F><0F><0F>	&<0F>ydS@0	<0E><0E><0E><0E><0E>}]N7&

<0A>
<0A>
<0A>
<01>
<01><<03>7<03><03>
<0A><03><03>	:S/<03>_H<02>+b
<0A>
<0A>
<0A>

h
P
=
$
<0C><0C><0C><0C><0C><08><0C><0C>ueR>+<0B><0B><0B><0B><0B><0B>	P
<01><03>	Y
<01><02><0B><03>4<07>~e<08>S=%
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD><08>
z
g
U
C
0


	<09>	<09><03><03><03><03><03><03>ub!M. S. Choi<04>K. C. Koh<04>K. Honein<04>Jay Kreps
>#Jason BakerK!Jan Lahodai'L. Sandulescu<04>-L. M. Sconfienza<04>1L. Carlo Pescatori<04>%Jeff Bonwick<'Jayadev Misra<02>%Jay Mccarthy4+K. Zisimopoulos<04><02>)Jean E. Sammet<02>K. Zachou<04>b!Jeff Shute<00>3Jayanthkumar Kannan<02>L. Santos<04>b-Jean-Michel LeonQAJean-Christophe Filliâtre
L. Zhang	L. MiaoK. Zhu+K. Kleinschmidt-Jon M. Kleinberg
BMatthew+Jacob Seligmann
<01>
K. Koike<05>K. Takagiw#K. IshigakiqK. MinlK. Lee`-L. Taberna-Arana=-K. Mönkemüller;+L. M. Van Driel3%L. Macconell.)K. Van Erpecum*K. SongK. Huh
K. YuK. RyuK. Tanaka!Jon Howell
<01>'Jon Crowcroft
<01>#John Wilkes
J)John W. Backus<02>)John Thickstun'John Peterson{

John Nham&%John Maloney
9John M. Mellor-CrummeyS#John Larson
<01>1John K. Ousterhoutw#John Hughes<00>'John Harrison<00>-John D. Lafferty(+John Cieslewicz
+John C. Collins='Joe Armstrong
!3Joan Morris Dimicco
<01>!Jinyang LiJ%Jinliang Fan>)Jing Jing Long<00>Jim Waldo
f
Jim Gray
-)Jessica Dubois
<01>1Jesper Wilhelmsson<00>/Jerome H. Saltzerj3Jerome C. Yochelson
<01>3Jeroen Van De Graaf<03>)Jeroen Beltman<02>%Jeremy Elson=9Jennifer Thom-Santelli
<01>%Jeffrey Dean,/Jeannette M. Wing
K+Jean-Paul Haton<02>5Jean-Francois Mangin
<01>
L. Tomé~fM'
Jacques KleinL. Micus
M. A. Elj-James C. CorbettM)
James BornholtF-James B. Rothnie
)James B. Orlinj+James A. Landay
<01>#Jae-Pil Heo<03>%Jade Alglave<00>%L. ZubiaurreQ<00>M. D. De JuanN'M. CelikbilekC
M. Li@<08>mM. Iancu=<08>4M. Gordan;<08>%M. A. Munteanu9#M. C. Hogan03M. K. K. Neijenhuis.	)Levan Atanelov
+Laszlo Szekeres<05>)Ken Dellapenta<05>'James Kennedy<05>%Jimmy Cleary<05>'Jelani Nelson<05>'Jean Bourgain<05>)Jonathan Evans<05>-K. N. Saifullina<05>
L. Huang<05>'
Jamie Shottont+
James T. Kajiya{/James R. Hamilton
<01>%James LarsonP!James Lang<03>!James Gips<00>-James C. Dehnert
m%Luis Pedrosa
F3
Luis Leopoldo Perez4

Luis CezeI+Lucian Grijincu
<01>'Luca Cardelli<02>%Luc Van Gool<00>%Luc Maranget'Lov K. Grover<02>%Linpeng Tang<00>)Leslie Lamport<00>1Leonard M. Adleman<00>#Leo Breiman-Lennart E. Nacke
<01>-Lennart Berggren61Leith Casey Leedom<00>1Lawrence R Rabiner<02>1Laurie A. Williams<02>-Lauretta O. Osho'
Laurent Sifre3Larry J. StockmeyerrLance Alt<02>%L. Sydorchuk
#
L M Adleman@-Kyle Littlefield
Kun Ren<00>/Kornilios KourtisP/
Koray Kavukcuoglu+5Konstantinos Sagonas<00>%Konrad Slind<00>'Koen Claessen<00>+
Klara Nahrstedt'Kjell Winblad!Kexin Rong<02>)Ketaki Solanki/Kenneth P. Birman
<01>%Ken Thompson
<01>)Keith Playford.)Keith Marzullo<03>#Keith Adams<02>#Keir Fraser\)Kaya Bekiroglu
N)Kay Ousterhout
z3Kathryn S. Mckinley
X'Kathrin PeterW1Kathrin M. Gerling
<01>/Katherine Everitt
<01>)
Kate Greenwood)Karl N. Levitt<03>'
Karin StraussK#Kai Huotari
<01>)K. Mani Chandy<03>!Junfeng He<03>Jun Rao
@'Julien Tierny<00>5
Julian Schrittwieser #Juho Hamari
<01>/Juha Kärkkäinen<02>#	Judea PearlAJuan A. Rodríguez-Aguilar
<01>'João Leitão
<01>'Joydeep Ghosh7José Orlando Pereira
<01> CJosé A. Ruipérez Valiente<03>+Joshua Redstone
c+Joshua J. Bloch'Josh Haberman
P)Joseph A. Cruz9!Jos Warmer<02>'Jorgen Thelin
`#Jorge OrtizI+Jorge Biolchini<02>7
Jordan L. Boyd-Graber>%
Jongmin BaekY-Jonathan Borwein7/Jonathan Bachrach-+Jonas PfefferleN5Jonas Braband Jensen<02>
<03>Vo<03><00><18>;
/<02>]1GGFortifying macros<07>Existing macro systems force programmers to make a choice between clarity of specification and robustness. If they choose clarity, they must forgo validating significant parts of the specification and thus produce low-quality language extensions. If they choose robustness, they must write in a style that mingles the implementation with the specification and therefore obscures the latter.
 This paper introduces a new language for writing macros. With the new macro system, programmers naturally write robust language extensions using easy-to-understand specifications. The system translates these specifications into validators that detect misuses - including violations of context-sensitive constraints - and automatically synthesize appropriate feedback, eliminating the need for ad hoc validation code.J. Funct. Program.macros/2017-09-11T23:06:40.8861699222017-09-11T23:06:40.886169922<EFBFBD>c<EFBFBD>:
=<02>
%GGTwo Tasty Servings of Pi<07>Perhaps no concept has captured the mathematical imagination more than the circle ratio π, while no mathematical symbol has evoked more mystery, romanticism and popular appeal than π itself. Why this fascination with math-ematics' most famous number? For the professional mathematician, π has long presented a challenge, being taciturn by nature and yielding up its splendours only grudgingly. When they are teased out, however, the effort expended is often handsomely repaid. Among reasons drawing the amateur to π are: its habit of turning up everywhere, often in unexpected places; the highly publicized search for its decimal digits, with world records tumbling almost annually in today's age of the supercomputer; and its long, colourful history filled with incident, drama, humour, genius and eccentricity. Continued interest in π over four millennia has resulted in the accumulation of a vast π-archive. What, then, do the two books under review here contribute to this collection? Pi : A Source Book, the first source book on π ever to be published, documents , mainly through original writings, the history of π from the dawn ofmathematics/2017-09-11T23:06:40.8219489752017-09-11T23:06:40.821948975<EFBFBD>&<26>9<00>!<02>
1GGTeaching Garbage Collection without Implementing Compilers or Interpreters<07>Given the widespread use of memory-safe languages, students must understand garbage collection well. Following a constructivist philosophy, an effective approach would be to have them implement garbage collectors. Unfortunately, a full implementation depends on substantial knowledge of compilers and runtime systems, which many courses do not cover or cannot assume. This paper presents an instructive approach to teaching gc, where students implement it atop a simplified stack and heap. Our approach eliminates enormous curricular dependencies while preserving the essence of gc algorithms. We take pains to enable testability, comprehensibility, and facilitates debugging. Our approach has been successfully classroom-tested for several years at several institutions.memory_management/2017-09-11T23:06:40.7388068852017-09-11T23:06:40.738806885

;<0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F>|qf[PE:/$<0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E>uj_TI>3(
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
y
n
c
X
M
B
7
,
!


<0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C>|qf[PE:/$<0B><0B><0B><0B><0B><0B><0B><0B><0B><0B><0B><0B>uj_TI>3)
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
y
n
c
X
M
B
7
,
!


	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	|	q	f	[	P	E	:	/	$			<08><08><08><08><08><08><08><08><08><08><08>ti^SH=2'<07><07><07><07><07><07><07><07><07><07><07><07>wlaVK@5*	<06><06><06><06><06><06><06><06><06><06><06><06>|qf[QF;0%<05><05><05><05><05><05><05><05><05><05><05><05>uj_TI>3(<04><04><04><04><04><04><04><04><04><04><04><04>yncXMB7,!<03><03><03><03><03><03><03><03><03><03><03>|qf[PE:/$<02><02><02><02><02><02><02><02><02><02><02><08>jE
<08>iD
<08>hC
<08>gB
<08>fA
<08>e@
<08>d?
<08>c>
<08>b=
<08>a<
<08>`;
<08>_:
<08>^9
<08>]8
<08>\7
<08>[6
<08>ZC
<08>Y5
<08>X4

<08>Wp

<08>V3

<08>U2

<08>T1

<08>S0
<08>R/
<08>Q.
<08>P-
<08>O,
<08>N+

<08>M*

<08>L)

<08>K(

<08>J'

<08>I<00>
	<08>H&
<08>G%
<08>F$
<08>E#
<08>D"
<08>C!
<08>B 
<08>A
<08>@
<08>?
<08>>
<08>=
<08><
<08>;
<08>:
<08>9
<08>8
<08>7
<08>6
<08>5
<07>4
n
<08>3
<08>2
<08>1
<08>0
<08>/
<08>.

<08>-
<08>,
<08>+

<08>*	

<08>)
<01>

<08>(

<08>'

<08>&

<08>%<00><08>$<00><08>#<00><08>"<00><08>!<00><08> <00><08><02><00><08>
<00><08><00><08>
<00><08><02><00><08><02><00><08><02><00><08><02><00><08><02><00><08><02><00><08><02><00><08><02><00><08><02><00><08><02><00><07>
)<00><08><02><00><08><02><00><08><02><00><07>

<00><08><02><00><08><02><00><08>
<02><00><08>	<02><00><08><02><00><08><02><00><08><02><00><07>
&<00><08><02><00><08><02><00><08><02><00><08>
<02><00><08><02><00><08><02><00><08>~<02><00><08>}<02><00><08>|<02><00><08>{<02><00><08>z<02><00><08>y<02><00><08>x<02><00><08>w<02><00><08>v<02><00><08>u<02><00><08>t<02><00><08>s<02><00><08>r<02><00><08>q<02><00><08>p<02><00><08>o<02><00><08>n<02><00><08>m<02><00><08>l<02><00><08>k<02><00><08>j<02><00><08>i<02><00><08>h<02><00><08>g<02><00><08>f<02><00><08>e<02><00><08>d<02><00><08>c<02><00><08>b<02><00><08>a<02><00><08>`<02><00><08>_<02><00><08>^<02><00><08>]<02><00><08>\<02><00><08>[
<01><00><08>Z<00><08>Y<02><00><08>X<02><00><08>W<02><00><08>V<02><00><08>U<02><00><08>TC<00><08>S<02><00><08>R<02><00><08>Q<02><00><08>P<02><00><08>O4<00><08>N
)<00><08>M<02><00><08>L<02><00><08>K<02><00><08>J<02><00><08>I<02><00><08>H<02><00><08>G<02><00><08>F<02><00><08>E<02><00><08>D<02><00><08>C<02><00><08>B<02><00><08>A
H<00><08>@<02><00><08>?<02><00><08>><02><00><08>=<02><00><08><<02><00><08>;<02><00><08>:<02><00><08>9<02><00><08>8<02><00><08>7<02><00><08>6<02><00><08>5
)<00><08>4<02><00><08>3<02><00><08>2<02><00><08>1<02><00><08>0<02><00><08>/<00><00><08>.<02><00><08>-<02><00><08>,<02><00><08>+<02><00><08>*<02><00><08>)<02><00><08>(<02><00><08>'<02><00><08>&<02><00><08>%<02><00><08>$<02><00><08>#<02><00><08>"
<01><00><08>!<02><00><07> 
5<00><08><02><00><08><02><00><08><02><00><08><02><00><08><02><00><08><02><00><08><02><00><08>u<00><08><02><00><08><00><08><02><00><08><02><00><07>

<00><08><02><00><08><02><00><08><02><00><08><02><00><08><02><00><08>


<00><08><00><08><02><00><08>
<02><00><08>	<02><00><08><02><00><08><02><00><08><02><00><08><02><00><08><02><00><08><02><00><08>
H<00><08>
<02><00><08><02><00><08><02><00><08>~<02><00><08>}<02><00><08>|<00><08>{~<00><08>z}<00><08>y|<00><08>x
<01><00><08>w{<00><08>vz<00><08>uy<00><08>t
)<00><08>sx<00><08>rw<00><08>qv<00><08>pu<00><08>ot<00><08>ns<00><08>mr<00><08>lq<00><08>kp<00><08>j<00><00><08>i4<00><08>ho<00><08>gn<00><08>f<00><00><08>em<00><08>dl<00><08>ck<00><08>bj<00><08>ai<00><07>`
)<00><08>_h<00><08>^<00><00><08>]g<00><08>\f<00><08>[e<00><08>Zd<00><08>Yc<00><08>Xb<00><08>Wa<00><08>V<00><00><08>U<00><00><08>T`<00><08>S_<00><08>R^<00><07>Q
N<00><08>P<00><00><08>O]<00><08>N\<00><08>M[<00><08>LZ<00><08>K
<01><00><08>JY<00><08>IX<00><08>HW<00><08>GV<00><08>FU<00><08>E<00><00><08>D
L<00><08>CT<00><08>B
h<00><08>AS<00><08>@R<00><08>?Q<00><08>>
<01><00><08>=P<00><08><O<00><08>;
<01><00><08>:N<00><08>9N<00><08>8
<01><00><08>7<00><00><08>64<00><08>5M<00><08>4L<00><08>3K<00><08>2J<00><08>1I<00><08>0H<00>
<02><08><02><00>_<EFBFBD>=<00>]<02>A1GGMessage analysis-guided allocation and low-pause incremental garbage collection in a concurrent language<07>We present a memory management scheme for a concurrent programming language where communication occurs using message-passing with copying semantics. The runtime system is built around process-local heaps, which frees the memory manager from redundant synchronization in a multithreaded implementation and allows the memory reclamation of process-local heaps to be a private business and to often take place without garbage collection. The allocator is guided by a static analysis which speculatively allocates data possibly used as messages in a shared memory area. To respect the (soft) real-time requirements of the language, we develop a generational, incremental garbage collection scheme tailored to the characteristics of this runtime system. The collector imposes no overhead on the mutator, requires no costly barrier mechanisms, and has a relatively small space overhead. We have implemented these schemes in the context of an industrial-strength implementation of a concurrent functional language used to develop large-scale, highly concurrent, embedded applications. Our measurements across a range of applications indicate that the incremental collector substantially reduces pause times, imposes only very small overhead on the total runtime, and achieves a high degree of mutator utilization.ISMMmemory_management/2017-09-11T23:06:41.0834641112017-09-11T23:06:41.083464111<EFBFBD>|<7C><<00><02>+1/GGApplications of Machine Learning in Cancer Prediction and Prognosis<07>Machine learning is a branch of artificial intelligence that employs a variety of statistical, probabilistic and optimization techniques that allows computers to "learn" from past examples and to detect hard-to-discern patterns from large, noisy or complex data sets. This capability is particularly well-suited to medical applications, especially those that depend on complex proteomic and genomic measurements. As a result, machine learning is frequently used in cancer diagnosis and detection. More recently machine learning has been applied to cancer prognosis and prediction. This latter approach is particularly interesting as it is part of a growing trend towards personalized, predictive medicine. In assembling this review we conducted a broad survey of the different types of machine learning methods being used, the types of dat
/<02>1EEAxodraw Version 2<07>We present version two of the L A T E X graphical style file Axodraw. It has a number of new drawing primitives and many extra options, and it can now work with pdflatex to directly produce output in PDF file format (but with the aid of an auxiliary program).ArXivmemory_management/2017-09-11T23:06:41.275104982017-09-11T23:06:41.27510498<EFBFBD>q<EFBFBD>?<00><02>)'1GGThe Slab Allocator: An Object-Caching Kernel Memory Allocator<07>This paper presents a comprehensive design overview of the SunOS 5.4 kernel memory allocator. This allocator is based on a set of object-caching primitives that reduce the cost of allocating complex objects by retaining their state between uses. These same primitives prove equally effective for managing stateless memory (e.g. data pages and temporary buffers) because they are space-efficient and fast. The allocator's object caches respond dynamically to global memory pressure, and employ an object-coloring scheme that improves the system's overall cache utilization and bus balance. The allocator also has several statistical and debugging features that can detect a wide range of problems throughout the system.USENIX Summermemory_management/2017-09-11T23:06:41.1589250492017-09-11T23:06:41.158925049<EFBFBD>K<EFBFBD>><00>I<02>-1GGAnd then there were none: a stall-free real-time garbage collector for reconfigurable hardware<07>Programmers are turning to radical architectures such as reconfigurable hardware (FPGAs) to achieve performance. But such systems, programmed at a very low level in languages with impoverished abstractions, are orders of magnitude more complex to use than conventional CPUs. The continued exponential increase in transistors, combined with the desire to implement ever more sophisticated algorithms, makes it imperative that such systems be programmed at much higher levels of abstraction. One of the fundamental high-level language features is automatic memory management in the form of garbage collection.
 We present the first implementation of a complete garbage collector in hardware (as opposed to previous "hardware-assist" techniques), using an FPGA and its on-chip memory. Using a completely concurrent snapshot algorithm, it provides single-cycle access to the heap, and never stalls the mutator for even a single cycle, achieving a deterministic mutator utilization (MMU) of 100%.
 We have synthesized the collector to hardware and show that it never consumes more than 1% of the logic resources of a high-end FPGA. For comparison we also implemented explicit (malloc/free) memory management, and show that real-time collection is about 4% to 17% slower than malloc, with comparable energy consumption. Surprisingly, in hardware real-time collection is superior to stop-the-world collection on every performance axis, and even for stressful micro-benchmarks can achieve 100% MMU with heaps as small as 1.01 to 1.4 times the absolute minimum.PLDImemory_management/2017-09-11T23:06:41.1202089842017-09-11T23:06:41.120208984
<0F>
x<00>m<EFBFBD>D
U<02>CKGGCan SPDY really make the web faster?<07>HTTP is a successful Internet technology on top of which a lot of the web resides. However, limitations with its current specification have encouraged some to look for the next generation of HTTP. In SPDY, Google has come up with such a proposal that has growing community acceptance, especially after being adopted by the IETF HTTPbis-WG as the basis for HTTP/2.0. SPDY has the potential to greatly improve web experience with little deployment overhead, but we still lack an understanding of its true potential in different environments. This paper offers a comprehensive evaluation of SPDY's performance using extensive experiments. We identify the impact of network characteristics and website infrastructure on SPDY's potential page loading benefits, finding that these factors are decisive for an optimal SPDY deployment strategy. Through exploring such key aspects that affect SPDY, and accordingly HTTP/2.0, we feed into the wider debate regarding the impact of future protocols.2014 IFIP Networking Conferencenetworks/2017-09-11T23:06:41.7080280762017-09-11T23:06:41.708028076<EFBFBD><05>C<00>5<02><1D>+1GGMaking lockless synchronization fast: performance implications of memory reclamation<07>Achieving high performance for concurrent applications on modern multiprocessors remains challenging. Many programmers avoid locking to improve performance, while others replace locks with non-blocking synchronization to protect against deadlock, priority inversion, and convoying. In both cases, dynamic data structures that avoid locking, require a memory reclamation scheme that reclaims nodes once they are no longer in use. The performance of existing memory reclamation schemes has not been thoroughly evaluated. We conduct the first fair and comprehensive comparison of three recent schemes -quiescent-state-based reclamation, epoch-based reclamation, and hazard-pointer-based reclamation - using a flexible microbenchmark. Our results show that there is no globally optimal scheme. When evaluating lockless synchronization, programmers and algorithm designers should thus carefully consider the data structure, the workload, and the execution environment, each of which can dramatically affect memory reclamation performanceProceedings 20th IEEE International Parallel & Distributed Processing Symposiummemory_management/2017-09-11T23:06:41.5357910162017-09-11T23:06:41.535791016|<7C>B	W

1GGInternet Security Glossary, Version 2<07>memory_management/2017-09-11T23:06:41.3583129882017-09-11T23:06:41.358312988
 	j <00>F<EFBFBD>F
a<02>=GGA wait-free queue as fast as fetch-and-add<07>Concurrent data structures that have fast and predictable performance are of critical importance for harnessing the power of multicore processors, which are now ubiquitous. Although wait-free objects, whose operations complete in a bounded number of steps, were devised more than two decades ago, wait-free objects that can deliver scalable high performance are still rare.
 In this paper, we present the first wait-free FIFO queue based on fetch-and-add (FAA). While compare-and-swap (CAS) based non-blocking algorithms may perform poorly due to work wasted by CAS failures, algorithms that coordinate using FAA, which is guaranteed to succeed, can in principle perform better under high contention. Along with FAA, our queue uses a custom epoch-based scheme to reclaim memory; on x86 architectures, it requires no extra memory fences on our algorithm's typical execution path. An empirical study of our new FAA-based wait-free FIFO queue under high contention on four different architectures with many hardware threads shows that it outperforms prior queue designs that lack a wait-free progress guarantee. Surprisingly, at the highest level of contention, the throughput of our queue is often as high as that of a microbenchmark that only performs FAA. As a result, our fast wait-free queue implementation is useful in practice on most multi-core systems today. We believe that our design can serve as an example of how to construct other fast wait-free objects.PPOPPnon_blocking_algorithms/2017-09-11T23:06:41.8958159182017-09-11T23:06:41.895815918<EFBFBD><12>E
[<02>=GGFlashNet: flash/network stack co-design<07>During the past decade, network and storage devices have undergone rapid performance improvements, delivering ultra-low latency and several Gbps of bandwidth. Nevertheless, current network and storage stacks fail to deliver this hardware performance to the applications, often due to the loss of IO efficiency from stalled CPU performance. While many efforts attempt to address this issue solely on either the network or the storage stack, achieving high-performance for networked-storage applications requires a holistic approach that considers both.
 In this paper, we present FlashNet, a software IO stack that unifies high-performance network properties with flash storage access and management. FlashNet builds on RDMA principles and abstractions to provide a direct, asynchronous, end-to-end data path between a client and remote flash storage. The key insight behind FlashNet is to co-design the stack's components (an RDMA controller, a flash controller, and a file system) to enable cross-stack optimizations and maximize IO efficiency. In micro-benchmarks, FlashNet improves 4kB network IOPS by 38.6% to 1.22M, decreases access latency by 43.5% to 50.4 <i>&#181;</i>secs, and prolongs the flash lifetime by 1.6--5.9&#215; for writes. We illustrate the capabilities of FlashNet by building a Key-Value store, and porting a distributed data store that uses RDMA on it. The use of FlashNet's RDMA API improves the performance of KV store by 2&#215;, and requires minimum changes for the ported data store to access remote flash devices.SYSTORnon_blocking_algorithms/2017-09-11T23:06:41.8256330572017-09-11T23:06:41.825633057

)
<EFBFBD>5
)<00><08>I
U<02>%
1GGJails: Confining the Omnipotent Root<07>The traditional UNIX security model is simple but inexpressive. Adding fine-grained access control improvest he expressiveness, but often dramatically increases both the cost of system management and implementation complexity.I nenvironments with a more complexman-agement model, with delegation of some management functions to parties under varying degrees of trust, the base UNIX model and most natural extensions are inappropriate at best. Where multiple mutually un-trusting parties are introduced, ''inappropriate''r apidly transitions to ''nightmarish'', especially with regards to data integrity and privacy protection. The FreeBSD ''Jail''facility provides the ability to partition the operating system environment, while maintaining the simplicity of the UNIX ''root''m odel. In Jail, users with privilege find that the scope of their requests is limited to the jail, allowing system administrators to delegate management capabilities for each virtual machine environment. Creating virtual machines in this manner has manyp otential uses; the most popular thus far has been for providing virtual machine services in Internet Service Provider environments.operating_systems/2017-09-11T23:06:42.1470319822017-09-11T23:06:42.147031982<EFBFBD>w<EFBFBD>H<00>7<02>1GGThe scalable commutativity rule: designing scalable software for multicore processors<07>Developing software that scales on multicore processors is an inexact science dominated by guesswork, measurement, and expensive cycles of redesign and reimplementation. Current approaches are workload-driven and, hence, can reveal scalability bottlenecks only for known workloads and available software and hardware. This paper introduces an <i>interface-driven</i> approach to building scalable software. This approach is based on the <i>scalable commutativity rule</i>, which, informally stated, says that whenever interface operations commute, they can be implemented in a way that scales. We formalize this rule and prove it correct for any machine on which conflict-free operations scale, such as current cache-coherent multicore machines. The rule also enables a better design process for scalable software: programmers can now reason about scalability from the earliest stages of interface definition through software design, implementation, and evaluation.SOSPoperating_systems/2017-09-11T23:06:42.0517180182017-09-11T23:06:42.051718018<EFBFBD>L<EFBFBD>G
[<02>=GGEfficient Lock-free Binary Search Trees<07>In this paper we present a novel algorithm for concurrent lock-free internal binary search trees (BST) and implement a Set abstract data type (ADT) based on that. We show that in the presented lock-free BST algorithm the amortized step complexity of each set operation - Add, Remove and Contains - is O(H(n) + c), where H(n) is the height of the BST with n number of nodes and c is the contention during the execution. Our algorithm adapts to contention measures according to read-write load. If the situation is read-heavy, the operations avoid helping the concurrent Remove operations during traversal, and adapt to interval contention. However, for the write-heavy situations we let an operation help a concurrent Remove, even though it is not obstructed. In that case, an operation adapts to point contention. It uses single-word compare-and-swap (CAS) operations. We show that our algorithm has improved disjoint-access-parallelism compared to similar existing algorithms. We prove that the presented algorithm is linearizable. To the best of our knowledge, this is the first algorithm for any concurrent tree data-structure in which the modify operations are performed with an additive term of contention measure.PODCnon_blocking_algorithms/2017-09-11T23:06:41.9749409182017-09-11T23:06:41.974940918

h
=<03>
h<00>%<25>L<00><02>sOGGFunctional Programming with Bananas, Lenses, Envelopes and Barbed Wire<07>We develop a calculus for lazy functional programming based on recursion operators associated with data type deenitions. For these operators we derive various algebraic laws that are useful in deriving and manipulating programs. We shall show that all example functions in Bird and Wadler's \Introduction to Functional Programming" can be expressed using these operators.FPCAparadigms/functional_programming/2017-09-11T23:06:42.7340910642017-09-11T23:06:42.734091064<EFBFBD>(<28>K<00>)<02>1GGSolaris Zones: Operating System Support for Consolidating Commercial Workloads<07>Server consolidation, which allows multiple workloads to run on the same system, has become increasingly important as a way to improve the utilization of computing resources and reduce costs. Consolidation is common in mainframe environments, where technology to support running multiple workloads and even multiple operating systems on the same hardware has been evolving since the late 1960's. This technology is now becoming an important differentiator in the UNIX and Linux server market as well, both at the low end (virtual web hosting) and high end (traditional data center server consolidation). This paper introduces Solaris Zones (zones), a fully realized solution for server consolidation projects in a commercial UNIX operating system. By creating virtualized application execution environments within a single instance of the operating system, the facility strikes a unique balance between competing requirements. On the one hand, a system with multiple workloads needs to run those workloads in isolation, to ensure that applications can neither observe data from other applications nor affect their operation. It must also prevent applications from over-consuming system resources. On the other hand, the system as a whole has to be flexible, manageable, and observable, in order to reduce administrative costs and increase efficiency. By focusing on the support of multiple application environments rather than multiple operating system instances, zones meets isolation requirements without sacrificing manageability.LISAoperating_systems/2017-09-11T23:06:42.4861159672017-09-11T23:06:42.486115967<EFBFBD>?<3F>J
O<02>1GGXen and the art of virtualization<07>Numerous systems have been designed which use virtualization to subdivide the ample resources of a modern computer. Some require specialized hardware, or cannot support commodity operating systems. Some target 100% binary compatibility at the expense of performance. Others sacrifice security or functionality for speed. Few offer resource isolation or performance guarantees; most provide only best-effort provisioning, risking denial of service.This paper presents Xen, an x86 virtual machine monitor which allows multiple commodity operating systems to share conventional hardware in a safe and resource managed fashion, but without sacrificing either performance or functionality. This is achieved by providing an idealized virtual machine abstraction to which operating systems such as Linux, BSD and Windows XP, can be <i>ported</i> with minimal effort.Our design is targeted at hosting up to 100 virtual machine instances simultaneously on a modern server. The virtualization approach taken by Xen is extremely efficient: we allow operating systems such as Linux and Windows XP to be hosted simultaneously for a negligible performance overhead --- at most a few percent compared with the unvirtualized case. We considerably outperform competing commercial and freely available solutions in a range of microbenchmarks and system-wide tests.SOSPoperating_systems/2017-09-11T23:06:42.3835139162017-09-11T23:06:42.383513916

:<02><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F>|qf[PE:/$<0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E>ti^SH=2'
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
w
l
a
V
K
@
5
*


	<0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C>zodYNC8-"
<0B><0B><0B><0B><0B><0B><0B><0B><0B><0B><0B>}rg\QF;0%
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
u
j
_
T
I
>
3
(


	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	x	m	b	W	L	A	6	+	 		
<08><08><08><08><08><08><08><08><08><08><08><08>{peZOD9.#
<07><07><07><07><07><07><07><07><07><07><07>~sh]RG<1&<06><06><06><06><06><06><06><06><06><06><06><06>vk`UJ?4)<05><05><05><05><05><05><05><05><05><05><05><05>yncXMB7,!<04><04><04><04><04><04><04><04><04><04><04>|qf[PE:/$<03><03><03><03><03><03><03><03><03><03><03>ti^SH=2'<02><02><02><02><02><02><02><02><02><02><02><02><08>fy
A<08>ex
@<08>dw
@<08>cv
@<08>bu
@<08>at
@<08>`s
@<08>_r
?<08>^g
?<08>]
?<08>\
	
><08>[q
><08>Zp
=<08>Yo
<<08>Xn
<<08>W
<01>
<<08>Vm
;<08>Ul
;<08>T
	
:<08>Sk
:<08>R
&
9<08>Qj
9<08>Pi
9<08>Oh
9<08>Ng
8<08>Mf
7<08>Le
7<08>Kd
7<08>J
<01>
6<08>I
<01>
5<08>Hc
4<08>Gb
3<08>Fa
2<08>E`
2<08>D_
1<08>C
	
0<08>B

0<08>A

0<08>@J
/<08>?
q
/<08>>H
/<08>=^
/<08><]
.<08>;\
-<08>:[
-<08>9Z
-<08>8Y
-<08>7X
,<08>6W
,<08>5<00>
+<08>4<00>
+<08>3V
+<08>2<00>
+<08>1U
*<08>0T
)<08>/S
)<08>.R
)<08>-Q
)<08>,P
)<08>+O
)<08>*N
)<08>)M
)<08>(L
)<08>'K
)<08>&
<01>
(<08>%J
(<08>$I
(<08>#H
(<08>"G
(<08>!F
(<08> E
(<08>D
'<08>C
'<08>B
'<08>A
'<08>@
&<08>
<01>
&<08>?
&<08>>
&<08>=
&<08><
&<08>;
%<08>:
%<08>9
%<08>8
%<08>7
%<08>6
%<08>5
%<08>4
%<08>
3
%<08>2
$<08>1
$<08>
0
$<08>	
|
$<08>/
$<08>.
$<08>-
$<08>,
$<08>+
$<08>*
#<08>)
#<08>
(
#<08>'
"<08>&
!<08>~%
!<08>}$
!<08>|#
!<08>{"
!<08>z!
 <08>y 
 <08>x<00>
<08>w
<08>v
<08>u
<08>t
<08>s
<08>r
<08>q
<08>p
<08>o
<08>n
<08>m
<08>l
<08>k
<08>j
<08>i
<08>h
<08>g
<08>f
<08>e

<08>d
<08>c
<08>b

<08>a	
<08>`
<08>_
<08>^
<08>]
<08>\
<08>[
<08>Z
<08>Y

<08>X
<08>W<02>
<08>V<02>
<08>U<02>
<08>T<02>
<08>S<02>
<08>R<02>
<08>Q<02>
<08>P<02>
<08>O<02>
<08>N<02>
<08>M<02>
<08>L<02>
<08>K<02>
<08>J<02>
<08>I<02>
<08>H<02>
<08>G<02>
<08>F<02>
<08>E<02>

<08>D<02>

<08>C<02>
<08>B<02>
<08>A<02>
<08>@<02>
<08>?<02>
<08>><02>
<08>=<02>
<08><<02>

<08>;<02>

<08>:<02>

<08>9<02>

<08>8<02>
	<08>7<02>
	<08>6<02>
<08>5<02>
<08>4<02>
<08>3<02>
<08>2<02>
<08>1<02>
<08>0<02>
<08>/<02>
<08>.<02>
<08>-
A
<08>,<02>
<08>+<02>
<08>*<02>
<08>)<02>
<08>(<02>

<08>'<02>

<08>&<02>

<08>%<02>
<08>$<02>
<08>#<02>
<08>"<02><00><08>!<02><00><08> <02><00><08><02><00><08><02><00><08><02><00><08><02><00><08><02><00><08><02><00><08><02><00><08><02><00><08><02><00><08><02><00><08><02><00><08><02><00><08><02><00><08><02><00><08><02><00><08><02><00><08><02><00><08><02><00><08>
<02><00><08><02><00><08><02><00><08>
<02><00><08>	<02><00><08><02><00><08><02><00><08><02><00><08><02><00><08><02><00><08><02><00><08><02><00><08>
<02><00><08><02><00><08><02><00><08>~<02><00><08>}<02><00><08>|<02><00><08>{<02><00><08>z<02><00><08>y<02><00><08>x<02><00><08>w<02><00><08>v<02><00><08>u<02><00><08>t<02><00><08>s3<00><08>r<02><00><08>q<02><00><08>p<02><00><08>o<02><00><08>n<02><00><08>m<02><00><08>l<02><00><08>k<02><00><08>j<02><00><08>i<02><00><08>h<02><00><08>g<02><00><08>f<02><00><08>e<02><00><08>d<02><00><08>c<02><00><08>b<02><00><08>a<02><00><08>`<02><00><08>_p<00><08>^<02><00><08>]<02><00><08>\<02><00><08>[<02><00><08>Z<02><00><08>Y<02><00><08>X<02><00><08>W<02><00><08>V<02><00><08>U<02><00><08>T<02><00><08>S<02><00><08>R<02><00><08>Q|<00><08>P<00><08>O<00><08>N~<00><08>M}<00><08>L|<00><08>K<00><08>Jx<00><08>Iw<00><08>H{<00><08>Gz<00><08>Fy<00><08>E<00><08>Dx<00><08>Cw<00><08>Bv<00><08>Au<00><08>@t<00><08>?s<00><08>>r<00><08>=q<00><08><p<00><08>;o<00><08>:n<00><08>9m<00><08>8l<00><08>7k<00><08>6j<00><08>5i<00><08>4h<00><08>3g<00><08>2f<00><08>1e<00><08>0d<00><08>/c<00><08>.b<00><08>-a<00>
<00>
<EFBFBD><00><00>v<EFBFBD>P
S<02>/GOEEOrganizing Programs Without Classes<07>All organizational functions carried out by classes can be accomplished in a simple and natural way by object inheritance in classless languages, with no need for special mechanisms. A single model—dividing types into prototypes and traits—supports sharing of behavior and extending or replacing representations. A natural extension, dynamic object inheritance, can model behavioral modes. Object inheritance can also be used to provide structured name spaces for well-known objects. Classless languages can even express " class-based " encapsulation. These stylized uses of object inheritance become instantly recognizable idioms, and extend the repertory of organizing principles to cover a wider range of programs.Lisp and Symbolic Computationparadigms/functional_programming/2017-09-11T23:06:43.125229982017-09-11T23:06:43.12522998<EFBFBD>i<EFBFBD>O
k<02>	EAGGJoint action: bodies and minds moving together.<07>The ability to coordinate our actions with those of others is crucial for our success as individuals and as a species. Progress in understanding the cognitive and neural processes involved in joint action has been slow and sparse, because cognitive neuroscientists have predominantly studied individual minds and brains in isolation. However, in recent years, major advances have been made by investigating perception and action in social context. In this article we outline how studies on joint attention, action observation, task sharing, action coordination and agency contribute to the understanding of the cognitive and neural processes supporting joint action. Several mechanisms are proposed that allow individuals to share representations, to predict actions, and to integrate predicted effects of own and others' actions.Trends in cognitive sciencesorganizational_simulation/2017-09-11T23:06:43.0203459472017-09-11T23:06:43.020345947<EFBFBD>m<EFBFBD>N
W<02>O=GGEnd-To-End Arguments in System Design<07>This paper presents a design principle that helps guide placement of functions among the modules of a distributed computer system. The principle, called the end-to-end argument, suggests that functions placed at low levels of a system may be redundant or of little value when compared with the cost of providing them at that low level. Examples discussed in the paper include bit error recovery, security using encryption, duplicate message suppression, recovery from system crashes, and delivery acknowledgement. Low level mechanisms to support these functions are justified only as performance enhancements.ACM Trans. Comput. Syst.networks/2017-09-11T23:06:42.9177758792017-09-11T23:06:42.917775879<EFBFBD><04>M<00>)<02>-OCCCrossing the gap from imperative to functional programming through refactoring<07>Java 8 introduces two functional features: lambda expressions and functional operations like map or filter that apply a lambda expression over the elements of a Collection. Refactoring existing code to use these new features enables explicit but unobtrusive parallelism and makes the code more succinct. However, refactoring is tedious: it requires changing many lines of code. It is also error-prone: the programmer must reason about the control-, data-flow, and side-effects. Fortunately, refactorings can be automated. We designed and implemented LambdaFicator, a tool which automates two refactorings. The first refactoring converts anonymous inner classes to lambda expressions. The second refactoring converts for loops that iterate over Collections to functional operations that use lambda expressions. Using 9 open-source projects, we have applied these two refactorings 1263 and 1709 times, respectively. The results show that LambdaFicator is useful: (i) it is widely applicable, (ii) it reduces the code bloat, (iii) it increases programmer productivity, and (iv) it is accurate.ESEC/SIGSOFT FSEparadigms/functional_programming/2017-09-11T23:06:42.85322292017-09-11T23:06:42.8532229
<08>	3#Z<0E>
<0A>
'}3
<EFBFBD><00>l<EFBFBD>{<02><0B>GGG<00>http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5350749Online Trajectory Generation: Basic Concepts for Instantaneous Reactions to Unforeseen Eventsrobotics/2017-09-11T23:06:16.0445410162017-09-11T23:06:16.044541016<EFBFBD>A<EFBFBD>t
<02>	]7GG<00>https://research.microsoft.com/en-us/um/people/nick/coqasm.pdfCoq: The world’s best macro assembler?program_verification/2017-09-11T23:06:16.0078759772017-09-11T23:06:16.007875977
<01><00>)<29>-GGhttp://www.kavrakilab.org/sites/default/files/kavraki1996prm-high-dim-conf.pdfProbablistic Roadmaps for Path Planning in High-Dimensional Configuration Spacesrobotics/2017-09-11T23:06:16.0445410162017-09-11T23:06:16.044541016
<01><00><0B>GGGhttp://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5350749Online Trajectory Generation: Basic Concepts for Instantaneous Reactions to Unforeseen Eventsrobotics<63>n<EFBFBD>|<02>)<29>-GG<00>http://www.kavrakilab.org/sites/default/files/kavraki1996prm-high-dim-conf.pdfProbablistic Roadmaps for Path Planning in High-Dimensional Configuration Spacesrobotics/2017-09-11T23:06:16.0445410162017-09-11T23:06:16.044541016<EFBFBD>&<26>z	YqGG<00>http://www.cs.washington.edu/node/4749The Dynamic Window Approach to Collision Avoidancerobotics/2017-09-11T23:06:16.0445410162017-09-11T23:06:16.044541016<EFBFBD>]<5D>y
s<>CGG<00>http://people.ee.duke.edu/~lcarin/Lihan4.21.06a.pdfDP-SLAM: Fast, Robust Simultaneous Localization and Mapping Without Predetermined Landmarksrobotics/2017-09-11T23:06:16.0445410162017-09-11T23:06:16.044541016<EFBFBD>N<EFBFBD>x
m<>+GG<00>http://www.roboticsproceedings.org/rss01/p36.pdfAdaptive Road Following using Self-Supervised Learning and Reverse Optical Flowrobotics/2017-09-11T23:06:16.0445410162017-09-11T23:06:16.044541016<EFBFBD>8<EFBFBD>w	a{1GG<00>https://arxiv.org/pdf/quant-ph/9605043.pdfA fast quantum mechanical algorithm for database searchquantum_computing/2017-09-11T23:06:16.0351330572017-09-11T23:06:16.035133057<EFBFBD>@<40>v
a<>	1GG<00>https://arxiv.org/pdf/quant-ph/9508027.pdfShors algorithm for polynomial time prime factorization (1995)quantum_computing/2017-09-11T23:06:16.0351330572017-09-11T23:06:16.035133057<EFBFBD>"<22>u	Mc1GG<00>https://arxiv.org/abs/1512.02900Advances in quantum machine learning (2015)quantum_computing/2017-09-11T23:06:16.0351330572017-09-11T23:06:16.035133057
<02><0B>h<02><00>"<22>S
a<02>#aGGFunctional reactive programming, continued<07>Functional Reactive Programming (FRP) extends a host programming language with a notion of time flow. Arrowized FRP (AFRP) is a version of FRP embedded in Haskell based on the arrow combinators. AFRP is a powerful synchronous dataflow programming language with hybrid modeling capabilities, combining advanced synchronous dataflow features with the higher-order lazy functional abstractions of Haskell. In this paper, we describe the AFRP programming style and our Haskell-based implementation. Of particular interest are the AFRP combinators that support dynamic collections and continuation-based switching. We show how these combinators can be used to express systems with an evolving structure that are difficult to model in more traditional dataflow languages.Haskell '02paradigms/functional_reactive_programming/2017-09-11T23:06:43.4610380862017-09-11T23:06:43.461038086<EFBFBD><11>R
-<02>'aGGEvent-Driven FRP<07>Functional Reactive Programming (FRP) is a high-level declarative language for programming reactive systems. Previous work on FRP has demonstrated its utility in a wide range of application domains, including animation, graphical user interfaces, and robotics. FRP has an elegant continuous-time denotational semantics. However, it guarantees no bounds on execution time or space, thus making it unsuitable for many embedded real-time applications. To alleviate this problem, we recently developed Real-Time FRP (RT-FRP), whose operational semantics permits us to formally guarantee bounds on both execution time and space. In this paper we present a formally verifiable compilation strategy from a new language based on RT-FRP into imperative code. The new language , called Event-Driven FRP (E-FRP), is more tuned to the paradigm of having multiple external events. While it is smaller than RT-FRP, it features a key construct that allows us to compile the language into efficient code. We have used this language and its compiler to generate code for a small robot controller that runs on a PIC16C66 micro-controller. Because the formal specification of compilation was crafted more for clarity and for technical convenience, we describe an implementation that produces more efficient code.PADLparadigms/functional_reactive_programming/2017-09-11T23:06:43.3178220212017-09-11T23:06:43.317822021<EFBFBD><EFBFBD>Q
a<02>?7OGGAn introduction to argumentation semantics<07>This paper presents an overview on the state of the art of semantics for abstract argumentation, covering both some of the most influential literature proposals and some general issues concerning semantics definition and evaluation. As to the former point the paper reviews Dung's original notions of complete, grounded, preferred, and stable semantics, as well as subsequently proposed notions like semi-stable, ideal, stage, and CF2 semantics, considering both the extension-based and the labelling-based approaches with respect to their definitions. As to the latter point the paper presents an extensive set of general properties for semantics evaluation and analyzes the notions of argument justification and skepticism. The final part of the paper is devoted to discuss some relationships between semantics properties and domain specific requirements.Knowledge Eng. Reviewparadigms/functional_programming/2017-09-11T23:06:43.2430190432017-09-11T23:06:43.243019043
;<02><0F>^<07><0E><0E>^<07>
<0A>
j
9<0C><0C>~U<0B>d(
<EFBFBD>
<EFBFBD>
<EFBFBD>
D^
	<09>j<02>	<09>	Q	4<08><02><08><08><06><06>m!B<05><05><05>s(<04><04>n<02>8<03><03>`,[On the Electrodynamics of Moving Bodies
<01>._Optimal Purely Functional Priority Queues
<01>6oPrediction in Joint Action: What, When, and Where
<01>>Part I: Transcendence of Values of Some Special Functions
t;yProgrammatic and direct manipulation, together at last<00>$M
Procedural modeling of buildings2B<04>Probabilistic Counting Algorithms for Data Base Applications
3iPrincipal Type-Schemes for Functional Programs<00>5o
Pregel: a system for large-scale graph processings?<04>

Practical byzantine fault tolerance and proactive recoveryq)UPractical Optional Types for Clojure<00>,[Polynomial-time theory of matrix groups<00>"I
Poisson surface reconstruction#J<04>
Piranha: A scalable architecture based on single-chip multiprocessing/c
Paxos made live: an engineering perspectivep/Paxos Made Simple
W"GPaxos Made Moderately Complex
Ud<04>IPastry: Scalable, distributed object location and routing for large-scale peer-to-peer systems
V*WParticle gibbs with ancestor sampling
#S<04>'Parallel generational-copying garbage collection with a block-structured heap<00>7s
Panorama weaving: fast and flexible seam processing51Out of the Tar Pit
2L<04>
Orleans: Distributed Virtual Actors for Programmability and Scalabilityo)UOn Proof and Progress in Mathematics
YL<04>Mesos: A Platform for Fine-Grained Resource Sharing in the Data Center
T<{MapReduce: Simplified Data Processing on Large Clusters
SW<04>/Oblivious Routing of Highly Variable Traffic in Service Overlays and IP Backbones
R!EOn the Calculus of Relations
N(SOrganizing Programs Without Classes<00>9
Optimistic replication_c<04>GOnline Trajectory Generation: Basic Concepts for Instantaneous Reactions to Unforeseen Events<00>;One VM to rule them all
2gOn the scalability of the Erlang term storage<00>3k
On the resemblance and containment of documentsJ<04>
On computable numbers with an application to the Entscheidungsproblem@<04>
On Understanding Types, Data Abstraction, and Polymorphism<00>D<04>
Omega: flexible, scalable schedulers for large compute clustersn'S
Object Space Silhouette AlgorithimsD<04>
No Silver Bullet: Essence and Accidents of Software Engineeringb"I
New directions in cryptographyE!
NTRU PrimeF;yMulticore profiling for Erlang programs using percept2<00>`<04>AMoviPill: improving medication compliance for elders using a mobile persuasive social game<00>L<04>Motion Planning 5.1 Motion Planning Concepts 5.1.1 Configuration Space<00>B<04>
Molecular computation of solutions to combinatorial problems.(U
Modularity and Scalability in CalvinWB<04>
MillWheel: Fault-Tolerant Stream Processing at Internet Scalek0e
Microreboot - A Technique for Cheap Recovery=F<04>
Metaobject protocols: Why we want them and what else they can do<00>0cMeta algorithms for hierarchical Web caches
n<04>]Message analysis-guided allocation and low-pause incremental garbage collection in a concurrent language<00>-_
Message Analysis for Concurrent Languages:V<04>-Megastore: Providing Scalable, Highly Available Storage for Interactive Services
)7qMediapolis Mediapolis popular Culture and the City
0e
Mathematical Aspects of Consciousness TheoryGG<04>
Mastering the game of Go with deep neural networks and tree search
N<04>
Map-reduce-merge: simplified relational data processing on large clusters^U<04>-
Managing Update Conflicts in Bayou, a Weakly Connected Replicated Storage System[K<04>
Making reliable distributed systems in the presence of software errors`

<08>
<00>Z<EFBFBD>U
w<02>oaGGAsynchronous functional reactive programming for GUIs<07>Graphical user interfaces (GUIs) mediate many of our interactions with computers. Functional Reactive Programming (FRP) is a promising approach to GUI design, providing high-level, declarative, compositional abstractions to describe user interactions and time-dependent computations. We present Elm, a practical FRP language focused on easy creation of responsive GUIs. Elm has two major features: simple declarative support for <i>Asynchronous FRP</i>; and purely functional graphical layout.
 Asynchronous FRP allows the programmer to specify when the global ordering of event processing can be violated, and thus enables efficient concurrent execution of FRP programs; long-running computation can be executed asynchronously and not adversely affect the responsiveness of the user interface.
 Layout in Elm is achieved using a purely functional declarative framework that makes it simple to create and combine text, images, and video into rich multimedia displays.
 Together, Elm's two major features simplify the complicated task of creating responsive and usable GUIs.PLDIparadigms/functional_reactive_programming/2017-09-11T23:06:43.6040219732017-09-11T23:06:43.604021973<EFBFBD><14>T
'<02>3aGGReal-Time FRP<07>Functional reactive programming (FRP) is a declarative programming paradigm where the basic notions are continuous, time-varying behaviors and discrete, event-based reactivity. FRP has been used successfully in many reactive programming domains such as animation, robotics, and graphical user interfaces. The success of FRP in these domains encourages us to consider its use in real-time applications, where it is crucial that the cost of running a program be bounded and known before run-time. But previous work on the semantics and implementation of FRP was not explicitly concerned about the issues of cost. In fact, the resource consumption of FRP programs in the current implementation is often hard to predict. As a first step towards addressing these concerns, this paper presents real-time FRP (RT-FRP), a statically-typed language where the time and space cost of each execution step for a given program is statically bounded. To take advantage of existing work on languages with bounded resources, we split RT-FRP into two parts: a reactive part that captures the essential ingredients of FRP programs, and a base language part that can be instantiated to any generic programming language that has been shown to be terminating and resource-bounded. This allows us to focus on the issues specific to RT-FRP, namely, two forms of recursion. After presenting the operational explanation of what can go wrong due to the presence of recursion, we show how the typed version of the language is terminating and resource-bounded. Most of our FRP programs are expressible directly in RT. The rest are expressible via a simple mechanism that integrates RT-FRP with the base language.ICFPparadigms/functional_reactive_programming/2017-09-11T23:06:43.4987548832017-09-11T23:06:43.498754883
)	<09>)<00>f<EFBFBD>X
[<02>+
aGGElm: Concurrent FRP for Functional GUIs<07>Graphical user interfaces (GUIs) mediate almost all of our interactions with computers, whether it is through web pages, phone apps, or desktop applications. Functional Reactive Programming (FRP) is a promising approach to GUI design. This thesis presents Elm, a concurrent FRP language focused on easily creating responsive GUIs. Elm has two major features: (1) purely functional graphical layout and (2) support for Concurrent FRP. Purely functional graphical layout is a high level framework for working with complex visual components. It makes it quick and easy to create and combine text, images, and video into rich multimedia displays. Concurrent FRP solves some of FRP's long-standing efficiency problems: global delays and needless recomputation. Together, Elm's two major features simplify the complicated task of creating responsive and usable graphical user interfaces. This thesis also includes a fully functional compiler for Elm, available at elm-lang.org. This site includes an interactive code editor that allows you to write and compile Elm programs online with no download or install.paradigms/functional_reactive_programming/2017-09-11T23:06:43.8252370612017-09-11T23:06:43.825237061<EFBFBD><13>W
_<02>saGGPush-pull functional reactive programming<07>Functional reactive programming (FRP) has simple and powerful semantics, but has resisted efficient implementation. In particular, most past implementations have used demand-driven sampling, which accommodates FRP's continuous time semantics and fits well with the nature of functional programming. Consequently, values are wastefully recomputed even when inputs don't change, and reaction latency can be as high as the sampling period. This paper presents a way to implement FRP that combines data- and demand-driven evaluation, in which values are recomputed only when necessary, and reactions are nearly instantaneous. The implementation is rooted in a new simple formulation of FRP and its semantics and so is easy to understand and reason about. On the road to a new implementation, we'll meet some old friends (monoids, functors, applicative functors, monads, morphisms, and improving values) and make some new friends (functional future values, reactive normal form, and concurrent "unambiguous choice").Haskellparadigms/functional_reactive_programming/2017-09-11T23:06:43.7586730962017-09-11T23:06:43.758673096<EFBFBD>R<EFBFBD>V
W<02>yaGGWormholes: introducing effects to FRP<07>Functional reactive programming (FRP) is a useful model for programming real-time and reactive systems in which one defines a <i>signal function</i> to process a stream of input values into a stream of output values. However, performing side effects (e.g. memory mutation or input/output) in this model is tricky and typically unsafe. In previous work, Winograd-Cort et al. [2012] introduced <i>resource types</i> and <i>wormholes</i> to address this problem.
 This paper better motivates, expands upon, and formalizes the notion of a wormhole to fully unlock its potential. We show, for example, that wormholes can be used to define the concept of causality. This in turn allows us to provide behaviors such as looping, a core component of most languages, without building it directly into the language. We also improve upon our previous design by making wormholes less verbose and easier to use.
 To formalize the notion of a wormhole, we define an extension to the simply typed lambda calculus, complete with typing rules and operational semantics. In addition, we present a new form of semantic transition that we call a <i>temporal</i> transition to specify how an FRP program behaves over time and to allow us to better reason about causality. As our model is designed for a Haskell implementation, the semantics are lazy. Finally, with the language defined, we prove that our wormholes indeed allow side effects to be performed safely in an FRP framework.Haskellparadigms/functional_reactive_programming/2017-09-11T23:06:43.6550139162017-09-11T23:06:43.655013916
<0B><07><00>)<29>\
a<02>I1GGThe operating system: should there be one?<07>Operating systems and programming languages are often informally evaluated on their conduciveness towards composition. We revisit Dan Ingalls' Smalltalk-inspired position that "an operating system is a collection of things that don't fit inside a language; there shouldn't be one", discussing what it means, why it appears not to have materialised, and how we might work towards the same effect in the postmodern reality of today's systems. We argue that the trajectory of the "file" abstraction through Unix and Plan 9 culminates in a Smalltalk-style object, with other filesystem calls as a primitive metasystem. Meanwhile, the key features of Smalltalk have many analogues in the fragmented world of Unix programming (including techniques at the library, file and socket level). Based on the themes of unifying OS- and language-level mechanisms, and increasing the expressiveness of the meta-system, we identify some evolutionary approaches to a postmodern realisation of Ingalls' vision, arguing that an operating system is still necessary after all.PLOS@SOSPoperating_systems/2017-09-11T23:06:44.3123640142017-09-11T23:06:44.312364014<EFBFBD>5<EFBFBD>[<00><02>S<EFBFBD>/CCA file undelete with Aho-Corasick algorithm in file recovery<07>In this research, a file undelete method is proposed by which the file recovery system retrieved the file metadata through a parsing process from the master file table (MFT) attributes. Using the Aho-Corasick algorithm, the process is then continued with a filtering process in which keywords are matched with file names. The result obtained shows that the proposed method is able to perform recovery of files that has been deleted from the file system. The experiment is performed four times with various file condition which had been overwritten 0%, 18.98%, 32.21% and 59.77% from their original size. The rate of the average file recovery success is 87.50% and the average time required is 0.32 second for string matching on file names.2016 International Conference on Informatics and Computing (ICIC)pattern_matching/2017-09-11T23:06:44.16709792017-09-11T23:06:44.1670979<EFBFBD><0C>Z	m
/GGHigh-Performance Graphics in Racket with DirectX<07>ICA3PPpattern_matching/2017-09-11T23:06:44.0379279792017-09-11T23:06:44.037927979<EFBFBD>j<EFBFBD>Y<00>
<02>
YGGMetaobject protocols: Why we want them and what else they can do<07>All rights reserved. No part of this book may be reproduced in any form by any electronic or mechanical means (including photocopying, recording, or information storage and retrieval) without permission in writing from the publisher. Originally conceived a s a n e at idea that could help solve problems in the design and implementation of CLOS, the metaobject protocol framework now appears to have applicability to a wide range of problems that come up in high-level languages. This chapter sketches this wider potential, by drawing an analogy to ordinary language design, by presenting some early design principles, and by presenting an overview of three new metaobject protcols we have designed that, respectively, control the semantics of Scheme, the compilation of Scheme, and the static parallelization of Scheme programs.paradigms/object_oriented_programming/2017-09-11T23:06:43.9484040532017-09-11T23:06:43.948404053
k<00><0F><0F><0F>b><0E><0E><0E><0E>nD(
<0A>
<0A>
<0A>
<0A>
Q
3
<0C><0C><0C>lJ%<0B><0B><0B><0B>vV5
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
^
8
	<09>	<09>	<09>	v	\	8	<08><08><08>rV8<07><07><07><07>jJ.<06><06><06>rR'<05><05><05><05>{U.<04><04><04>mH.<03><03><03><03>fJ*<02><02><02>`:
<01>
<01>

]
9
<00><00><1C>n%Alex De JongAlexDeJong<19>m!
Ole AgesenOleAgesen<1B>l#
Keith AdamsKeithAdams!<21>k)
Oliver RiordanOliverRiordan<1F>j'
Svante JansonSvanteJanson#<23>i+
Béla BollobásBélaBollobás6<73>h?Guilherme Horta TravassosGuilhermeHortaTravassos2<73>g;%Ana Candida Cruz NataliAnaCandida CruzNatali$<24>f-Paula Gomes MianPaulaGomesMian#<23>e+
Jorge BiolchiniJorgeBiolchini(<28>d1Laurie A. WilliamsLaurieA.Williams%<25>c-#
Thirumalesh BhatThirumaleshBhat.<2E>b7!E. Michael MaximilienE.MichaelMaximilien+<2B>a3!
Nachiappan NagappanNachiappanNagappan<15>`
Rob PikeRobPike<1D>_%
Peter BailisPeterBailis<19>^!
Kexin RongKexinRong<1D>]%
Anupam GuptaAnupamGupta#<23>\+
Sanjoy DasguptaSanjoyDasgupta<1F>['
Daniel SundayDanielSunday<1B>Z#
Andrew HumeAndrewHume<1F>Y'
Mario SzegedyMarioSzegedy<1D>X%
Yossi MatiasYossiMatias<17>W
Noga AlonNogaAlon"<22>V+G. Nigel MartinG.NigelMartin'<27>U/
Philippe FlajoletPhilippeFlajolet&<26>T/J. Strother MooreJ.StrotherMoore"<22>S+Robert S. BoyerRobertS.Boyer<1F>R'
Andrew TurpinAndrewTurpin$<24>Q-William F. SmythWilliamF.Smyth$<24>P-Simon J. PuglisiSimonJ.Puglisi#<23>O+
Jean-Paul HatonJean-PaulHaton<19>N!
Yifan GongYifanGong<19>M!
Haizhou LiHaizhouLi%<25>L-
Stefan BurkhardtStefanBurkhardt<1F>K'
Peter SandersPeterSanders'<27>J/
%Juha KärkkäinenJuhaKärkkäinen(<28>I1Daniel P. W. EllisDanielP. W.Ellis<1D>H%
Martin CookeMartinCooke<1C>G%J. P. BarkerJ.P.Barker!<21>F)
Michael RileyyMichaelRileyy'<27>E/
Fernando PereirazFernandoPereiraz!<21>D)
Mehryar MohriyMehryarMohriy(<28>C1Lawrence R RabinerLawrenceRRabiner<19>B!
Dieter FoxDieterFox<1D>A%
Xiaofeng RenXiaofengRen<1B>@#
Evan HerbstEvanHerbst#<23>?+
Michael KraininMichaelKrainin<1B>>#
Peter HenryPeterHenry)<29>=1!
Przemyslaw WegrzynPrzemyslawWegrzyn<1D><%
Dhiru KholiaDhiruKholia<1D>;%
Angelo PradoAngeloPrado<1B>:#
Neal HarrisNealHarris<19>9!
Yoel GluckYoelGluck<1B>8#
Stefan FreiStefanFrei+<2B>73
%Thomas DuebendorferThomasDuebendorfer!<21>6)
Byung-Gon ChunByung-GonChun+<2B>53%
Jayanthkumar KannanJayanthkumarKannan%<25>4-
Alberto DainottiAlbertoDainotti!<21>3)
Robert BeverlyRobertBeverly<17>2
Lance AltLanceAlt&<26>1/Steven M. LavalleStevenM.Lavalle'<27>0/
Sebastian ThrunyzSebastianThrunyz%<25>/-
Wolfram BurgardyWolframBurgardy<1B>.#
Dieter FoxyDieterFoxy&<26>-/Friedrich M. WahlFriedrichM.Wahl#<23>,+
Torsten KrögerTorstenKröger<1F>+'
Jayadev MisraJayadevMisra<1B>*#
Ronald ParrRonaldParr&<26>)/Austin I. EliazarAustinI.Eliazar#<23>(+
Sebastian ThrunSebastianThrun)<29>'1
#Andrew LookingbillAndrewLookingbill<19>&!
David LiebDavidLieb<1E>%'Lov K. GroverLovK.Grover<1D>$%
Ákos SeressÁkosSeress<1D>#%
Robert BealsRobertBeals!<21>")
László BabaiLászlóBabai<1F>!'
Conor McbrideConorMcbride <20> )C. A. R. HoareC.A. R.Hoare#<23>+
Hans-J. BriegelHans-J.Briegel"<22>+Jacob M. TaylorJacobM.Taylor<1F>'
Vedran DunjkoVedranDunjko3<6F>;-
Pierre-Évariste DagandPierre-ÉvaristeDagand,<2C>5Jonas Braband JensenJonasBrabandJensen<1B>#
Nick BentonNickBenton!<21>)
Andrew KennedyAndrewKennedy<1D>%
Robin MilnerRobinMilner<1B>#
Luís DamasLuísDamas-<2D>5#
Christopher StracheyChristopherStrachey<1D>%
Andrej BauerAndrejBauer<1F>'
Steven AwodeyStevenAwodey<1D>%
Peter WegnerPeterWegner<1F>'
Luca CardelliLucaCardelli <20>)Jean E. SammetJeanE.Sammet<19>!
Mike FaganMikeFagan'<27>/
!Robert CartwrightRobertCartwright<1B>#
Edwin BradyEdwinBrady<1B>
#
Weimin ChenWeiminChen<1F>'
Matthew FlattMatthewFlatt <20>)John W. BackusJohnW.Backus<1D>
%
Stephen KellStephenKell,<2C>	5Romi Fadillah RahmatRomiFadillahRahmat!<21>)
Andrew HandokoAndrewHandoko*<2A>3Opim Salim SitompulOpimSalimSitompul#<23>+
Antoine BossardAntoineBossard!<21>)
Michael AshleyMichaelAshley$<24>-Daniel G. BobrowDanielG.Bobrow
<02> <02><00>e<EFBFBD>^
w<02>QGGComposable and compilable macros: : you want it when?<07>Many macro systems, especially for Lisp and Scheme, allow macro transformers to perform general computation. Moreover, the language for implementing compile-time macro transformers is usually the same as the language for implementing run-time functions. As a side effect of this sharing, implementations tend to allow the mingling of compile-time values and run-time values, as well as values from separate compilations. Such mingling breaks programming tools that must parse code without executing it. Macro implementors avoid harmful mingling by obeying certain macro-definition protocols and by inserting phase-distinguishing annotations into the code. However, the annotations are fragile, the protocols are not enforced, and programmers can only reason about the result in terms of the compiler's implementation. MzScheme---the language of the PLT Scheme tool suite---addresses the problem through a macro system that separates compilation without sacrificing the expressiveness of macros.ICFPplt/2017-09-11T23:06:45.0909450682017-09-11T23:06:45.090945068<EFBFBD>\<5C>]<00>[<02>S#CCCan Programming Be Liberated From the von Neumann Style? A Functional Style and its Algebra of Programs<07>Conventional programming languages are growing ever more enormous, but not stronger. Inherent defects at the most basic level cause them to be both fat and weak: their primitive word-at-a-time style of programming inherited from their common ancestor&#8212;the von Neumann computer, their close coupling of semantics to state transitions, their division of programming into a world of expressions and a world of statements, their inability to effectively use powerful combining forms for building new programs from existing ones, and their lack of useful mathematical properties for reasoning about programs.
An alternative functional style of programming is founded on the use of combining forms for creating programs. Functional programs deal with structured data, are often nonrepetitive and nonrecursive, are hierarchically constructed, do not name their arguments, and do not require the complex machinery of procedure declarations to become generally applicable. Combining forms can use high level programs to build still higher level ones in a style not possible in conventional languages.
Associated with the functional style of programming is an algebra of programs whose variables range over programs and whose operations are combining forms. This algebra can be used to transform programs and to solve equations whose &#8220;unknowns&#8221; are programs in much the same way one transforms equations in high school algebra. These transformations are given by algebraic laws and are carried out in the same language in which programs are written. Combining forms are chosen not only for their programming power but also for the power of their associated algebraic laws. General theorems of the algebra give the detailed behavior and termination conditions for large classes of programs.
 A new class of computing systems uses the functional programming style both in its programming language and in its state transition rules. Unlike von Neumann languages, these systems have semantics loosely coupled to states&#8212;only one state transition occurs per major computation.Commun. ACMplt/2017-09-11T23:06:44.47247292017-09-11T23:06:44.4724729
<05>"<05><00>[<5B>`<00><02>GGProgramming and reasoning with algebraic effects and dependent types<07>One often cited benefit of pure functional programming is that pure code is easier to test and reason about, both formally and informally. However, real programs have side-effects including state management, exceptions and interactions with the outside world. Haskell solves this problem using <i>monads</i> to capture details of possibly side-effecting computations --- it provides monads for capturing state, I/O, exceptions, non-determinism, libraries for practical purposes such as CGI and parsing, and many others, as well as <i>monad transformers</i> for combining multiple effects.
 Unfortunately, useful as monads are, they do not compose very well. Monad transformers can quickly become unwieldy when there are lots of effects to manage, leading to a temptation in larger programs to combine everything into one coarse-grained state and exception monad. In this paper I describe an alternative approach based on handling <i>algebraic effects</i>, implemented in the IDRIS programming language. I show how to describe side effecting computations, how to write programs which compose multiple fine-grained effects, and how, using dependent types, we can use this approach to reason about states in effectful programs.ICFPplt/2017-09-11T23:06:45.2051931152017-09-11T23:06:45.205193115<EFBFBD>Z<EFBFBD>_
K<02>o
GGEfficient Predicate Dispatching<07>The speed of method dispatching is an important issue in the overall performance of object-oriented programs. We have developed an algorithm for constructing efficient dispatch functions for the general predicate dispatching model, which generalizes single dispatching, multiple dispatching, predicate classes and classifiers, and pattern-matching. Our algorithm generates a lookup DAG each of whose nodes represents an N-way test of the class or value of a formal or other expression. Our algorithm implements each of these N-way tests with a binary decision tree blending class identity tests, class range tests, and table lookups. Our algorithm exploits any available static information (from type declarations or class analysis) to prune unreachable paths from the lookup DAG, and uses any available dynamic profile information to minimize the expected time to traverse the binary decision trees. We measure the effectiveness of our dispatching algorithms on a collection of large Cecil and Java programs, compiled by the Vortex optimizing compiler, showing improvements of up to 40% over already heavily optimized baseline versions.plt/2017-09-11T23:06:45.1499150392017-09-11T23:06:45.149915039
<07><00>G<EFBFBD>b
_<02>#GGProgramming Languages: History and Future<07>This paper discusses both the history and future of programming languages ( = higher level languages). Some of the difficulties in writing such a history are indicated. A key part of the paper is a tree showing the chronological development of languages and their interrelationships. Reasons for the proliferation of languages are given. The major languages are listed with the reasons for their importance. A section on chronology indicates the happenings of the significant previous time periods and the major topics of 1972. Key concepts other than specific languages are discussed.Commun. ACMplt/2017-09-11T23:06:45.3825258792017-09-11T23:06:45.382525879<EFBFBD><1E>a
#<02>GGSoft Typing<07>Type systems are designed to prevent the improper use of program operations. They can be classified as either static or dynamic depending on when they detect type errors. Static type systems detect potential type errors at compile-time and prevent program execution. Dynamic type systems detect type errors at run-time and abort program execution. Static type systems have two important advantages over dynamic type systems. First, they help programmers detect a large class of program errors before exe-cut ion. Second, the y extract information that a compiler can exploit to produce more efficient code. The price paid for these advantages, however, is a loss of expressiveness, generality, and semantic simplicity. This paper presents a generalization of static and dynamic typing—called soft typing-that combines the best features of both approaches, The key idea underlying soft typing is that a static type checker need not reject programs that contain potential type errors. Instead, the type checker can insert explicit run-time checks around " suspect " arguments of p~imitive operations , converting dynamically typed programs into statically type-correct form. The inserted run-time checks identify program phrases that may be erroneous. For soft typing to be effective, the type system must avoid inserting unnecessary run-time checks. To accomplish this objective, we have developed an extension of the ML type system supporting union types and recursive types that assigns types to a wider class *The work of both authors was partially supported by NSF and DARPA. Permission to copy without fee ell or part of this material is granted provided that the copies are not made or distributed for direct commercial advantege, the ACM copyright notice and the title of the publication and its date appear, and notice is given that copying is by permission of the Association for Computing Machinery. To copy otherwise, or to republish, requires a fee and/or specific permission.PLDIplt/2017-09-11T23:06:45.2972180182017-09-11T23:06:45.297218018
<00>e<00><00>(<28>d
7<02>
+GGPropositions as Types<07>Image factorizations in regular categories are stable under pull-backs, so they model a natural modal operator in dependent type theory. This unary type constructor [A] has turned up previously in a syntactic form as a way of erasing computational content, and formalizing a notion of proof irrelevance. Indeed, semantically, the notion of a support is sometimes used as surrogate proposition asserting inhab-itation of an indexed family. We give rules for bracket types in dependent type theory and provide complete semantics using regular categories. We show that dependent type theory with the unit type, strong extensional equality types, strong dependent sums, and bracket types is the internal type theory of regular categories, in the same way that the usual dependent type theory with dependent sums and products is the internal type theory of locally cartesian closed categories. We also show how to interpret first-order logic in type theory with brackets, and we make use of the translation to compare type theory with logic. Specifically, we show that the propositions-as-types interpretation is complete with respect to a certain fragment of intuitionistic first-order logic. As a consequence, a modified double-negation translation into type theory (without bracket types) is complete for all of classical first-order logic.J. Log. Comput.plt/2017-09-11T23:06:45.4839860842017-09-11T23:06:45.483986084<EFBFBD><17>c<00>
<02>/GGOn Understanding Types, Data Abstraction, and Polymorphism<07>Our objective is to understand the notion of <I>type</I> in programming languages, present a model of typed, polymorphic programming languages that reflects recent research in type theory, and examine the relevance of recent research to the design of practical programming languages.
Object-oriented languages provide both a framework and a motivation for exploring the interaction among the concepts of type, data abstraction, and polymorphism, since they extend the notion of type to data abstraction and since type inheritance is an important form of polymorphism. We develop a &#955;-calculus-based model for type systems that allows us to explore these interactions in a simple setting, unencumbered by complexities of production programming languages.
The evolution of languages from untyped universes to monomorphic and then polymorphic type systems is reviewed. Mechanisms for polymorphism such as overloading, coercion, subtyping, and parameterization are examined. A unifying framework for polymorphic type systems is developed in terms of the typed &#955;-calculus augmented to include binding of types by quantification as well as binding of values by abstraction.
The typed &#955;-calculus is augmented by universal quantification to model generic functions with type parameters, existential quantification and packaging (information hiding) to model abstract data types, and bounded quantification to model subtypes and type inheritance. In this way we obtain a simple and precise characterization of a powerful type system that includes abstract data types, parametric polymorphism, and multiple inheritance in a single consistent framework. The mechanisms for type checking for the augmented &#955;-calculus are discussed.
The augmented typed &#955;-calculus is used as a programming language for a variety of illustrative examples. We christen this language Fun because fun instead of &#955; is the functional abstraction keyword and because it is pleasant to deal with.
Fun is mathematically simple and can serve as a basis for the design and implementation of real programming languages with type facilities that are more powerful and expressive than those of existing programming languages. In particular, it provides a basis for the design of strongly typed object-oriented languages.ACM Comput. Surv.plt/2017-09-11T23:06:45.3974719242017-09-11T23:06:45.397471924
<03><03><00><10>f
i<02>5GGPrincipal Type-Schemes for Functional Programs<07>Permission to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage, the ACM copyright notice and the title of its publication and date appear, and notice is given that copying is by permission of the Association for Computing Machinery. To copy otherwise, or to republish, requires a fee and/or specific permission.POPLplt/2017-09-11T23:06:45.8772209472017-09-11T23:06:45.877220947<EFBFBD>v<EFBFBD>e
g<02>AWGGFundamental Concepts in Programming Languages<07>This paper forms the substance of a course of lectures given at the International Summer School in Computer Programming at Copenhagen in August, 1967. The lectures were originally given from notes and the paper was written after the course was finished. In spite of this, and only partly because of the shortage of time, the paper still retains many of the shortcomings of a lecture course. The chief of these are an uncertainty of aim—it is never quite clear what sort of audience there will be for such lectures—and an associated switching from formal to informal modes of presentation which may well be less acceptable in print than it is natural in the lecture room. For these (and other) faults, I apologise to the reader. There are numerous references throughout the course to CPL [1–3]. This is a programming language which has been under development since 1962 at Cambridge and London and Oxford. It has served as a vehicle for research into both programming languages and the design of compilers. Partial implementations exist at Cambridge and London. The language is still evolving so that there is no definitive manual available yet. We hope to reach another resting point in its evolution quite soon and to produce a compiler and reference manuals for this version. The compiler will probably be written in such a way that it is relatively easy to transfer it to another machine, and in the first instance we hope to establish it on three or four machines more or less at the same time. The lack of a precise formulation for CPL should not cause much difficulty in this course, as we are primarily concerned with the ideas and concepts involved rather than with their precise representation in a programming language. Any discussion on the foundations of computing runs into severe problems right at the start. The difficulty is that although we all use words such as 'name', 'value', 'program', 'expression' or 'command' which we think we understand, it often turns out on closer investigation that in point of fact we all mean different things by these words, so that communication is at best precarious. These misunderstandings arise in at least two ways. The first is straightforwardly incorrect or muddled thinking. An investigation of the meanings of these basic terms is undoubtedly an exercise in mathematical logic and neither to the taste nor within the field of …Higher-Order and Symbolic Computationplt/2017-09-11T23:06:45.5873330082017-09-11T23:06:45.587333008
u<0B><06><04>u<00><0E>k<00><02>
GGThe Derivative of a Regular Type is its Type of One-Hole Contexts<07>Polymorphic regular types are tree-like datatypes generated by polynomial type expressions over a set of free variables and closed under least fixed point. The 'equal-ity types' of Core ML can be expressed in this form. Given such a type expression T with x free, this paper shows a way to represent the one-hole contexts for elements of x within elements of T, together with an operation which will plug an element of x into the hole of such a context. One-hole contexts are given as inhabitants of a regular type @ x T, computed generically from the syntactic structure of T by a mechanism better known as partial differentiation. The relevant notion of containment is shown to be appropriately characterized in terms of derivatives and plugging in. The technology is then exploited to give the one-hole contexts for sub-elements of recursive types in a manner similar to Huet's 'zippers'[Hue97].plt/2017-09-11T23:06:46.5005700682017-09-11T23:06:46.500570068<EFBFBD><05>j
Q<02>#!GGCommunicating Sequential Processes<07>This paper suggests that input and output are basic primitives of programming and that parallel composition of communicating sequential processes is a fundamental program structuring method. When combined with a development of Dijkstra's guarded command, these concepts are surprisingly versatile. Their use is illustrated by sample solutions of a variety of a familiar programming exercises.Commun. ACMprocesses/2017-09-11T23:06:46.4216379392017-09-11T23:06:46.421637939<EFBFBD>i	y

GGProgramming languages - application and interpretation<07>plt/2017-09-11T23:06:46.2821640622017-09-11T23:06:46.282164062<EFBFBD>j<EFBFBD>h
O<02>Y;1;;Quantum-enhanced machine learning<07>The emerging field of quantum machine learning has the potential to substantially aid in the problems and scope of artificial intelligence. This is only enhanced by recent successes in the field of classical machine learning. In this work we propose an approach for the systematic treatment of machine learning, from the perspective of quantum information. Our approach is general and covers all three main branches of machine learning: supervised, unsupervised, and reinforcement learning. While quantum improvements in supervised and unsupervised learning have been reported, reinforcement learning has received much less attention. Within our approach, we tackle the problem of quantum enhancements in reinforcement learning as well, and propose a systematic scheme for providing improvements. As an example, we show that quadratic improvements in learning efficiency, and exponential improvements in performance over limited time periods, can be obtained for a broad class of learning problems.Physical review lettersquantum_computing/2017-09-11T23:06:46.2382017-09-11T23:06:46.238<EFBFBD>|<7C>g
Y<02>{7GGCoq: the world's best macro assembler?<07>We describe a Coq formalization of a subset of the x86 architecture. One emphasis of the model is brevity: using dependent types, type classes and notation we give the x86 semantics a makeover that counters its reputation for baroqueness. We model bits, bytes, and memory concretely using functions that can be computed inside Coq itself; concrete representations are mapped across to mathematical objects in the SSReflect library (naturals, and integers modulo 2<sup><i>n</i></sup>) to prove theorems. Finally, we use notation to support conventional assembly code syntax inside Coq, including lexically-scoped labels. Ordinary Coq definitions serve as a powerful "macro" feature for everything from simple conditionals and loops to stack-allocated local variables and procedures with parameters. Assembly code can be assembled within Coq, producing a sequence of hex bytes. The assembler enjoys a correctness theorem relating machine code in memory to a separation-logic formula suitable for program verification.PPDPprogram_verification/2017-09-11T23:06:46.1270610352017-09-11T23:06:46.127061035
<00>Z<0F><0F><0F><0F><0F><0F>tm[G5 <0E><0E><0E>U<0E><0E><0E><0E><0E>{jX@)	
<0A>e
<0A><08>
<0A><08>
<0A>
<0A>
<0A>
<0A>
<0A>
tN
h
Y
D
-

<0C><0C>u<0C><0C><08><0C><0C><0C>As`<08>bSA(<0B><0B><0B><0B><0B><0B>zcQ5 
<EFBFBD>
<EFBFBD><02>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
t
c
S
B
"
	<09>	<09>	<09>	<09>	<09><02>	<09>	~	g	M<02>)	2			Z<02><08><08><08>=(<07><07><07><07><07><07>miU@+<06><06><06><06><06><06>t^I1<05><05><05><05><05><05>wfTD1
<04><04><04><04><04><04><02>|iU<02>A)
<03><03><03><03><03><03><03>'Mathias Payer<05>1Michael A. Nielsen<05>)Matija Pretnar<05>/Mohana Ramaratnam<05>+Marco Scandurra<05>1Mosharaf Chowdhury<05>)Martin Odersky<05>+Martin A. Keane<05>#Mu Y Thomas<05>%Mark Purcell<05>1Marvin D. Tretkoff<05>M. Tada<05>%M. Matsuyama<05>+M. V. KabrawalapM. Sawadaf-N. L. H. BekkaliaN. Hüser!N. Göschlc%N. Demanzini<03>%N. Al Hajjar<04>)Márk Jelasity
<01>9Mustansir Hatim Pancha9Muralidhar Subramanian<00>1Murali S. Kodialamh+
Muhammad Naveed)Morteza Khayat'Moran Tzafrir<00>1Moisés Goldszmidt"GMohammad Ali Akhavan-Behabadi/Mitchell Spradlin#Miron Livny
<01>'Mircea Oancea<00>

Min Wu9!Milo Polte<03>%Mikel Larrea<03>'
Mike SharplesR'Mike Paterson<03>!Mike Fagan<02>%Mike Burrows{#Mihai Budiu
<01>'Miguel Castro
d+Michal H. Palka<00>)Michael Wimmer<00>'Michael WelzlI'Michael Stumm
<01>/Michael Steinbach%)Michael Rileyy<02>1
Michael M. Kazhdanc-Michael L. Scott<00>1Michael L. Roberts
<01>+Michael Krainin<02>-Michael Kaminsky<00>3Michael J. Freedman<00>3Michael J. Franklin
1Michael J. Fischer<03>-Michael J. Carey
<01>/Michael I. Jordan))Michael Hammer
-Michael F. Cohen<00>-Michael D. Ernst

+Michael Curtiss
<01>+Michael Burrows
|)Michael Ashley<02>-Michael Armbrust
15Michael Abd-El-Malek
\/Michael A. Bender #Micah Sherr<03>-Mendel Rosenblumx'Mehul A. Shah
s)Mehryar Mohriy<02>+Mauro Cherubini
<01>+Maurice Herlihy<00>+Matti Pitkänen<00>1Matthew H. Austern
k!M. C. SulzHM. HaradaA1M. A. D’assuncao9#M. J. Bruno5-M. Van Der Voort2#M. Shiffman)M. Kang'Matthew Flatt<02>+
Matthew Bolithod#Matt Tolton<00>'Matei Zaharia
:-Masumi Shirakawa
<01>7Massimiliano Giacominv5Martin Farach-Colton!/Martin E. Hellman<00>%Martin Cooke<02>+Martin Caminadau5
Marta Z. Kwiatkowska7/Marshall C. Pease
~)Markus Völter<02>#Markus Lipp<00>+Markus H. Gross<00>'Marko Vukolic<00>AMarko C. J. D. Van Eekelen<03>#Mark Robson<03>!Mark Klein
<01>#Mark Hayden
<01>%
Mark HartnerT'Mario Wolczko<02>'Mario Szegedy<02>1Marcos K. Aguilera
q)Marco Serafini<03>%Marc Shapiro
 /Marc Schuilenburg<02>!
Marc LevoyZ%
Marc Lanctot#+Manos Kapritsos
<01>9Manon J. N. L. Benders
<01>%Manoj Plakal}/Malte Schwarzkopf
['Mahadev Konar<03>-Magnus O. Myreen<00>-Maged M. Michael<00>5Magdalena Balazinska
/Madhukar Korupolu
G+
Madeleine Leach*'Madan Jampani5/Maarten Van Steen
<01>3Maarten M. Fokkingad%M. Čarapina<03>M. Yousef<04>#M. Yalınay!M. Traunerj7M. Surendranath Reddy)M. Steinberger?
M. Silva<04>+M. Sharaf-Eldin<04>!M. Schoder`!M. S. Choi<04>
M. Rocha<04>7M. Peck-RadosavljevickM. Parola<03>/M. Papatheodoridi<04>+M. O. Mavlikeev$M. Nakura<03>M. Min%M. Mandorfere
M. Lu
M. Li@%M. L. RinconS
M. Kraus<04>M. Kenzel@3M. K. K. Neijenhuis.
M. Iancu=/M. Gravito-SoaresxM. Gordan;#M. Giuricin<03>/M. Frans Kaashoek
C1M. Feldner-Busztinb%M. El Gharib<04>#M. Diermayra!M. Di Maso<04>M. Danila<03>'M. D. De JuanN'M. CelikbilekC
M. Cejnag!M. Cardoso<04>#M. C. Hogan0M. Bilzer<04>%M. B. Afonso<03>!M. Attalla<04>+M. Abd El-Kader<04>%M. A. Titova()M. A. Munteanu9%M. A. Eljakyq)M. A. El Zahry<04>)László Babai<02>'Lyle Frankling7Luís E. T. Rodrigues
<01>#Luís Damas<02>'Lukas Stadler<02>3Luiz André Barrosoz
<00>
<01><0F><0F><0F><0F><0F><0F><0F>vgSJ6
<0E><0E><0E><0E><0E><0E><0E><0E>vaJA&
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
t
e
R
E
2
#



<0C><0C><0C><0C><0C><0C><0C><0C>yg]SJ7.<0B><0B><0B><0B><0B><0B><0B><0B><0B>ypXF+"
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
{
g
^
S
>
1
'

	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	l	V	B	9	0			<08><08><08><08><08><08><08><08><08><08>{ocXD3'<07><07><07><07><07><07><07><07><07><07><07>tkW7'<06><06><06><06><06><06><06><06>wjWH?2&<05><05><05><05><05><05><05><05><05>ypg]R@7"<04><04><04><04><04><04><04><04><04><04>veOC)<03><03><03><03><03><03><03>yp[OC-$<02><02><02><02><02><02><02>{eNE;'

<01><12>'+process crashes<14>&/reliable delivery<0C>%synchrony<11>$)cryptocurrency<07>#coin<06>"pow<14>!/in-depth analysis<13> -relational model<1F>Elarge-scale software systems	<09>crisis
<EFBFBD>bitcoin
<EFBFBD>backend<17>5support transactions<15>1snapshot isolation<06>psi<15>1causal consistency<0B>bigtable<06>ity<13>-atomic multicast	<09>parity	<09>stripe<12>+storage systems<06>vdf<0F>%object store<06>dos<13>-complex problems<0C>
lsm-trees<06>vfs<14>/different systems<1E>
Cperformance and consistency<12>	+data management<08>dbmss<0C>datastore<17>5high-level operators	<09>tiling<13>-expression graph<0E>#input array
<EFBFBD>spartan
<EFBFBD>
napster<0F>%unstructured<06>dht<06>~fds<0B>}locality
<EFBFBD>|dilemma<07>{cpus<06>zhdf	<09>ydynamo<17>x5eventual consistency
<0A>w!amazon.com<07>vpnut<12>u+google bigtable<06>tgfs<0F>s%google, inc.<08>rpmcmc<07>qmcmc<06>psmc<06>opga<06>nssm<17>m5theoretical research<12>l+database theory<06>kory<06>jlca<10>i'constant time<0B>hancestor<06>grmq<0F>f%eavesdropper
<0A>e!encryption<0B>dtime pad<06>cpri	<09>bcustom
<EFBFBD>atestbed<06>`dsg<0C>_developed<10>^'system design
<EFBFBD>]classic<13>\-computer systems
<0A>[!networking<07>Zhint<12>Y+virtual machine<0C>Xpractical	<09>Witself	<09>Vsqueak
<0A>U!translator<18>T7language capabilities<08>Schess<0B>Rfootnote
<0A>Q!conceptnet<1D>PAtree augmented naive bayes<11>O)tan classifier<06>Nmdl
<EFBFBD>Mtribute<06>Lbnc<10>K'documentation<0B>Jsubclass<06>Ilru<06>Hlce<06>Glcd<08>Fchunk<0E>E#crazy stone<0E>D#tree search<08>Csucce<06>Buct<0C>Agame tree<0E>@#spectrogram	<09>?shazam<0E>>#fingerprint<11>=)fingerprinting<08><radio	<09>;editor	<09>:mbeddr<06>9ast<06>8pes
<EFBFBD>7hotspot<15>61partial evaluation
<EFBFBD>5truffle<08>4guest<07>3trap<06>2i/o<06>1vmm<06>0e.g<13>/-phase transition
<EFBFBD>.special	<09>-bollob<0F>,%random graph<06>+ibm<06>*tdd<11>))defect density<13>(-development team<12>'+code inspection<0C>&embedding<0B>%subspace<08>$lemma
<0A>#!well-known<18>"7johnson-lindenstrauss<0E>!#boyer-moore
<0A> !compromise
<EFBFBD>toolkit<18>7boyer moore algorithm<07>fast<07>pass
<EFBFBD>seminal<12>+streaming model<08>cient<06>ams<11>)relative error
<EFBFBD>counter<17>5approximate counting<13>-frequency moment<14>/non-negative data<07>hash<0E>#fm sketches<07>pcsa<19>9probabilistic counting<0F>%morris-pratt<06>
kmp<18>7boyer-moore algorithm<0F>%knuth-morris<15>
1matching algorithm<06>	bwt<19>9construction algorithm	<09>suffix<0E>#linear time<11>)data structure<0B>length n<08>motif<06>pre<07>
ence<06>con<07>dhmm<06>~asr<06>}isa<14>|/scaling procedure<06>{alg<10>z'rgb-d mapping<06>yicp<07>xrgbd<07>wslam<0F>v%rgb-d camera<0E>u#source-code<14>t/generic technique
<EFBFBD>sdropbox	<09>rchrome
<EFBFBD>qbrowser<08>popera<12>o+mozilla firefox<0F>n%installation<07>mdisk<07>lport	<09>kproach<07>jhard<0C>idegreaser<10>h'goal position
<EFBFBD>gplanner<10>f'path planning<0C>egeometric<12>d+motion planning<16>c3collision avoidance<08>blocal<15>a1obstacle avoidance
<EFBFBD>`mission<06>_dwa<07>^void<0F>]%mobile robot<12>\+motion dynamics
<EFBFBD>[command
<EFBFBD>Zelocity<18>Y7trajectory generation<06>Xdof<14>W/motion trajectory<12>V+state of motion<06>Uotg<08>Tlaser<11>S)slam algorithm
<EFBFBD>Rdp-slam<0B>Qgrid map<13>P-state estimation
<EFBFBD>Oroadway<08>Ndarpa<0F>M%optical flow<11>L)traversability<0F>K%road surface<14>J/quantum computing<11>I)famous example<06>Hbad<11>G)quantum search<0C>Ffactoring	<09>Eoracle<0F>D%matrix group<0B>Cquotient<08>Boccam	<09>Amalism)<29>@Ycsp communicating sequential processes<07>?loto<0E>>#ccs and csp
<00><02><0F><0F>J<0F><0F><0F><04><0F><0F><0F>xmaV<03>;<07>/#<03><0E><<0E><04>!<0E><0E>x<08><0E><0E><0E><06><0E>WS<0E><0E>ygSB<03>9g<08>,<06>"	<07><02>
<0A>
<0A>E<"<06><03>\<03>
<0A><08>
<0A><08>
<0A>
<0A>
<0A>
w<05>{
`
RW
B
6o<05>
-<07>

<07>l<05>=
<0C><0C><0C><0C><0C>D<05><0C><05>.<0C>x<0C><04>ui`TK<0'2<0B><06><0B>.<0B><0B><06><06>l<0B>i<0B>Y=<0B><0B><04><0B>rr<08>W<05>HE<07><08>6X<07><07>b<07>,#$<07><04><04>-<04><04>

<EFBFBD>
<EFBFBD>
<EFBFBD><06>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
~<06>
l
X<06>

@
5
<04>
'<03>	<09>%	<09>	<09><03><08>	<09>	<09><02>	<09>
	<09>	<09>	<09>-	y	j<04>	`	R	D	8	/	$		
splicing<04>vulzwarxvictimv
vanadiums
tutorialr'test instancem)square patternbtoma	trie`1time-varying value\+virtual networkQ#side-effectI$Ksoftware engineering principlesFvmwareA!starvation>
stack=#shared data7
sparsity1sparse0sixties.
thinking,/single individual*snr'
stant&1source and channel%tmi"+sequence number ues!widespread	sinktarzantor	undp
un women
violence
unfpa9senders and recipients
ssion<03>/understandability<03>$Ksynchronous distributed systems<03>tla<03>-traffic analysis<03>+storage service<03>1strong consistency<03>/synchronous model<03>3synchronous systems<03>
sumption<03>;transactions per second<03>+traffic changes<03>vlb<03>synchrony<03>5support transactions<03>1snapshot isolation<03>stripe<03>+storage systems<03>vdf<03>vfs<03>tiling<03>spartan<03>%unstructured<03>smcpssmn5theoretical researchm
time paddtestbeda'system design^+virtual machineYsqueakV!translatorUAtree augmented naive bayesP)tan classifierOtributeM
subclassJ#tree searchD
succeCuctB#spectrogram@shazam?truffle5	trap3vmm1special.tdd*
subspace%!well-known#toolkitseminal+streaming modelsuffix	slam<02>#source-code<02>	void<02>7trajectory generation<02>+state of motion<02>)slam algorithm<02>-state estimation<02>)traversability<02>zookeeper
<01>	yarn
^
yampa<02>xenj
writing\
wormhole<02>
workflow"	wild[wide-area
,wep<00>;web page classification<00>-weak consistency
6	weak

wait-free]vservero	
voxelbvms
<01>vll
)virtualizationpvirtual
<01>;viewstamped replication
<01>

viewerl3
video stabilization])vertices of g.;%vector field<00>varH3
vandalism detection?

vandal<'user activity
<01>
urevuptime<00>upgrade<00>	unix<02>%unit testing<00>!unikernels
<01>unicorn
<01>typing<02>
turen	tsdf<00>treadmill
<01>%transparency
u7transactional support<00>-train algorithms
<01>
tpc-c

)
topic modelingA#
topic model@tod<02>timestamp
5	ties
<01>ticast
<01>3theoretical results
<01>#theoretical<00>3text classification<00>tes<00>
tensionXtemporale
<01>tem}techni
Otcp
<01>tation
'task duration
<01>
tance<00>	talk<00>;synchronous replication
K#synchronous
<01>?synchronization primitive<00>	sync
M	swim
<01>

swiftness8svm
suc<02>subtyping<02>sts
<01>street<00>!streamline<00>

streamingd/stream processing
estereo<00>5statistical database-statistical datastatic<02>?state machine replication
o	stat
Jsql
spreading
<01>
split<00>	spel
<01>
specularq	spdyZspacing#som
<01>#soft typing<02>)social support
<01>%social graph
<01>
soap,
soa(sns
<01>smr
q!
smartphone%small subset
	slocx	slabT%skin surface<00>%
single photoz
sinfonia
|-
simple 3d shapes|silver
E
shutter_
shingleT7shared representation

shadowm
shadingp

shaderi
sgs3sgd>+serializability
<01>!sequence x?)
sensitive data&senior
<01>sender
<01>
semantic

5
security and privacy$
<04>Y<07><04><00>X<EFBFBD>n
{<02>1GGA Fast Quantum Mechanical Algorithm for Database Search<07>An unsorted database contains N records, of which just one satisfies a particular property. The problem is to identify that one record. Any classical algorithm, deter-ministic or probabilistic, will clearly take O (N) steps since on the average it will have to examine a large fraction of the N records. Quantum mechanical systems can do several operations simultaneously due to their wave like properties. This paper gives an O (JN) step quantum mechanical algorithm for identifying that record. It is within a constant factor of the fastest possible quantum mechanical algorithm.STOCquantum_computing/2017-09-11T23:06:47.3355559082017-09-11T23:06:47.335555908<EFBFBD><13>m	S
O!GGA Calculus of Communicating Systems<07>Lecture Notes in Computer Scienceprocesses/2017-09-11T23:06:47.0309509282017-09-11T23:06:47.030950928<EFBFBD>#<23>l
[<02>M1GGPolynomial-time theory of matrix groups<07>We consider matrix groups, specified by a list of generators, over finite fields. The two most basic questions about such groups are membership in and the order of the group. Even in the case of abelian groups it is not known how to answer these questions without solving hard number theoretic problems (factoring and discrete log); in fact, constructive membership testing in the case of 1 &#215; 1 matrices is precisely the discrete log problem. So the reasonable question is whether these problems are solvable in randomized polynomial time using number theory oracles. Building on 25 years of work, including remarkable recent developments by several groups of authors, we are now able to determine the order of a matrix group over a finite field of odd characteristic, and to perform constructive membership testing in such groups, in randomized polynomial time, using oracles for factoring and discrete log. One of the new ingredients of this result is the following. A group is called semisimple if it has no abelian normal subgroups. For matrix groups over finite fields, we show that the order of the largest semisimple quotient can be determined in randomized polynomial time (no number theory oracles required and no restriction on parity). As a by-product, we obtain a natural problem that belongs to BPP and is not known to belong either to RP or to coRP. No such problem outside the area of matrix groups appears to be known. The problem is the decision version of the above: Given a list A of nonsingular d &#215; d matrices over a finite field and an integer N, does the group generated by A have a semisimple quotient of order &gt; N? We also make progress in the area of constructive recognition of simple groups, with the corollary that for a large class of matrix groups, our algorithms become Las Vegas.STOCquantum_computing/2017-09-11T23:06:46.6702900392017-09-11T23:06:46.670290039

L
<EFBFBD>{
L<00>A<EFBFBD>r<00>G<02>GCCOnline Trajectory Generation: Basic Concepts for Instantaneous Reactions to Unforeseen Events<07>This paper introduces a new method for motion-trajectory generation of mechanical systems with multiple degrees of freedom (DOFs). The key feature of this new concept is that motion trajectories are generated online, i.e., within every control cycle, typically every millisecond. This enables systems to react instantaneously to unforeseen and unpredictable (sensor) events at any time instant and in any state of motion. As a consequence, (multi)sensor integration in robotics, in particular the development of control systems enabling sensor-guided and sensor-guarded motions, becomes greatly simplified. We introduce a class of online trajectory-generation algorithms and present the mathematical basics of this new approach. The algorithms presented here consist of three steps: calculation of the minimum synchronization time for all DOFs, synchronization of all DOFs, and calculation of output values. The theory is followed by real-world experimental results indicating new possibilities in robot-motion control.IEEE Transactions on Roboticsrobotics/2017-09-11T23:06:48.50897292017-09-11T23:06:48.5089729g<EFBFBD>q	I

GGTheory in Programming Practice<07>plt/2017-09-11T23:06:48.2364719242017-09-11T23:06:48.236471924<EFBFBD>
<EFBFBD>p<00>C<02>AGGDP-SLAM: Fast, Robust Simultaneous Localization and Mapping Without Predetermined Landmarks<07>A fundamental task for reasoning with preferences is the following: given input preference information from a user, and outcomes α and β, should we infer that the user will prefer α to β? For CP-nets and related comparative preference formalisms, inferring a preference of α over β using the standard definition of derived preference appears to be extremely hard, and has been proved to be PSPACE-complete in general for CP-nets. Such inference is also rather conservative, only making the assumption of transitivity. This paper defines a less conservative approach to inference which can be applied for very general forms of input. It is shown to be efficient for expressive comparative preference languages, allowing comparisons between arbitrary partial tuples (including complete assignments), and with the preferences being ceteris paribus or not.IJCAIrobotics/2017-09-11T23:06:47.8539838872017-09-11T23:06:47.853983887<EFBFBD>s<EFBFBD>o<00>+<02>{GGGAdaptive Road Following using Self-Supervised Learning and Reverse Optical Flow<07>— The majority of current image-based road following algorithms operate, at least in part, by assuming the presence of structural or visual cues unique to the roadway. As a result, these algorithms are poorly suited to the task of tracking unstructured roads typical in desert environments. In this paper, we propose a road following algorithm that operates in a self-supervised learning regime, allowing it to adapt to changing road conditions while making no assumptions about the general structure or appearance of the road surface. An application of optical flow techniques, paired with one-dimensional template matching, allows identification of regions in the current camera image that closely resemble the learned appearance of the road in the recent past. The algorithm assumes the vehicle lies on the road in order to form templates of the road's appearance. A dynamic programming variant is then applied to optimize the 1-D template match results while enforcing a constraint on the maximum road curvature expected. Algorithm output images, as well as quantitative results, are presented for three distinct road types encountered in actual driving video acquired in the California Mojave Desert.Robotics: Science and Systemsrobotics/2017-09-11T23:06:47.4168659672017-09-11T23:06:47.416865967



<00>h<EFBFBD>s
q<02>[
GGThe Dynamic Window Approach to Collision Avoidance<07>This paper describes the dynamic window a p proach t o reactive collision avoidance for mobile robots equipped with synchro-drives. The a p proach i s d erived directly from the motion dynamics of the robot and i s t herefore particularly well-suited for robots o perating a t high speed. It diiers from previous approaches in that t he search for commands controlling t he translational a n d rotational velocity o f t he robot is carried out directly in the space of velocities. The advantage of our approach i s t hat it correctly and in an elegant w ay incorporatesthe dynamics of the robot. This is done by r e d ucing t he search space to t he dynamic window, which consists o f t he v elocities reachable within a short time i n terval. Within the dynamic window t he a p proach only considers admissible velocities yielding a trajectory on which t he robot is able to s t op safely. Among t hesevelocities the combination of translational and rotational velocity is chosen by m aximizing an objective f u nction. The objective f u nction includes a measure of progress towards a goal location, the forward velocity o f t he robot, and the d i s t ance to t he n ext obstacle on the trajectory. In extensive experiments t he approach presented here has been found t o safely control our mobile robot RHINO with speeds of up to 95 cmmsec, in populated and dynamic environments.robotics/2017-09-11T23:06:48.8430349122017-09-11T23:06:48.843034912


<00>u<EFBFBD>u
_<02>}GGUncovering network tarpits with degreaser<07>Network tarpits, whereby a single host or appliance can masquerade as many fake hosts on a network and slow network scanners, are a form of defensive cyber-deception. In this work, we develop <i>degreaser</i>, an efficient fingerprinting tool to remotely detect tarpits. In addition to validating our tool in a controlled environment, we use <i>degreaser</i> to perform an Internet-wide scan. We discover tarpits of non-trivial size in the wild (prefixes as large as/16), and characterize their distribution and behavior. We then show how tarpits pollute existing network measurement surveys that are tarpit-na&#239;ve, e.g. Internet census data, and how <i>degreaser</i> can improve the accuracy of such surveys. Lastly, our findings suggest several ways in which to advance the realism of current network tarpits, thereby raising the bar on tarpits as an operational security mechanism.ACSACsecurity/2017-09-11T23:06:49.1113100592017-09-11T23:06:49.111310059<EFBFBD>p<EFBFBD>t<00><02>A
GGMotion Planning 5.1 Motion Planning Concepts 5.1.1 Configuration Space<07>A fundamental robotics task is to plan collision-free motions for complex bodies from a start to a goal position among a collection of static obstacles. Although relative simple, this geometric path planning problem is provably computationally hard [84]. Extensions of this formulation take into account additional constraints that are inherited from mechanical and sensor limitations of real robots such as uncertainties, feedback and differential constraints, which further complicate the development of automated planners. Modern algorithms have been fairly successful in addressing hard instances of the basic geometric problem and a lot of effort is devoted to extend their capabilities to more challenging instances. These algorithms have had widespread success in applications beyond robotics, such as computer animation, virtual prototyping, and computational biology. There are many available surveys [36, 70, 91] and books [23, 57, 60] that cover modern motion planning techniques and applications. This chapter first provides a formulation of the geometric path planning problem in Section 5.1 and then introduces sampling-based planning in Section 5.2. Sampling-based planners are general techniques applicable to a wide set of problems and have been successful in dealing with hard planning instances. For specific, often simpler planning instances, alternative approaches exist and are presented in Section 5.3. These approaches provide theoretical guarantees and for simple planning instances they outperform sampling-based planners. Section 5.4 considers problems that involve differential constraints , while Section 5.5 overviews several other extensions of the basic problem formulation and proposed solutions. Finally, Section 5.7 addresses some important and more advanced topics related to motion planning. This section provides a description of the fundamental motion planning problem or else the geometric path planning problem. Extensions of this basic formulation to more complicated instances will be discussed later in the chapter and they will be revisited throughout this book. In path planning, a complete description of the geometry of a robot A and of a workspace W is provided. The workspace W = R N , in which N = 2 or N = 3, is a static environment populated with obstacles. The goal is to find a collision-free path for A to move from an initial position and orientation to a goal position and orientation. To achieve that, a complete specification of the location of every point on the robot geometry, or a configuration q, must be provided. The configuration space, or C-space (q ∈ C), is the space of all …robotics/2017-09-11T23:06:48.9938930662017-09-11T23:06:48.993893066
<02>
k<07>_<02>
G<02>GGLooking Inside the (Drop) Box<07>Dropbox is a cloud based file storage service used by more than 100 million users. In spite of its widespread popularity, we believe that Dropbox as a platform hasn't been analyzed extensively enough from a security standpoint. Also, the previous work on the security analysis of Dropbox has been heavily censored. Moreover, the existing Python bytecode reversing techniques are not enough for reversing hardened applications like Dropbox. This paper presents new and generic techniques, to reverse engineer frozen Python applications, which are not limited to just the Dropbox world. We describe a method to bypass Dropbox's two factor authentication and hijack Dropbox accounts. Additionally, generic techniques to intercept SSL data using code injection techniques and monkey patching are presented. We believe that our biggest contribution is to open up the Dropbox platform to further security analysis and research. Dropbox will / should no longer be a black box. Finally, we describe the design and implementation of an open-source version of Dropbox client (and yes, it runs on ARM too).WOOTsecurity/2017-09-11T23:06:49.4029409182017-09-11T23:06:49.402940918o<EFBFBD>x	O

GGBreach: Reviving the Crime Attack<07>security/2017-09-11T23:06:49.3726870122017-09-11T23:06:49.372687012<EFBFBD><16>w
O<02>Y
GGWhy Silent Updates Boost Security<07>Security fixes and feature improvements don't benefit the end user of software if the update mechanism and strategy is not effective. In this paper we analyze the effectiveness of different Web browsers update mechanisms; from Google Chrome's silent update mechanism to Opera's update requiring a full re-installation. We use anonymized logs from Google's world wide distributed Web servers. An analysis of the logged HTTP user-agent strings that Web browsers report when requesting any Web page is used to measure the daily browser version shares in active use. To the best of our knowledge, this is the first global scale measurement of Web browser update effectiveness comparing four different Web browser update strategies including Google Chrome. Our measurements prove that silent updates and little dependency on the underlying operating system are most effective to get users of Web browsers to surf the Web with the latest browser version. However, there is still room for improvement as we found. Google Chrome's advantageous silent update mechanism has been open sourced in April 2009. We recommend any software vendor to seriously consider deploying silent updates as this benefits both the vendor and the user, especially for widely used attack-exposed applications like Web browsers and browser plug-ins.security/2017-09-11T23:06:49.2888759772017-09-11T23:06:49.288875977<EFBFBD><11>v<00><02>GGMaking Programs Forget: Enforcing Lifetime for Sensitive Data<07>This paper introduces guaranteed data lifetime, a novel system property ensuring that sensitive data cannot be retrieved from a system beyond a specified time. The trivial way to achieve this is to " reboot " ; however, this is disruptive from the user's perspective, and may not even eliminate disk copies. We discuss an alternate approach based on state reincarnation where data expiry is completely transparent to the user, and can be used even if the system is not designed a priori to provide the property.HotOSsecurity/2017-09-11T23:06:49.1867839362017-09-11T23:06:49.186783936

<04>
<00>q<EFBFBD>|<00>1<02>
3GGA Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition<07>Although initially introduced and studied in the late 1960s and early 1970s, statistical methods of Markov source or hidden Markov modeling have become increasingly popular in the last several years. There are two strong reasons why this has occurred. First the models are very rich in mathematical structure and hence can form the theoretical basis for use in a wide range of applications. Second the models, when applied properly, work very well in practice for several important applications. In this paper we attempt to carefully and methodically review the theoretical aspects of this type of statistical modeling and show how they have been applied to selected problems in machine recognition of speech.speech_recognition/2017-09-11T23:06:49.5427060552017-09-11T23:06:49.542706055<EFBFBD><0B>{
<00>

GGRapidly-Exploring Random Trees: A New Tool for Path Planning<07>robotics/2017-09-11T23:06:49.5197680662017-09-11T23:06:49.519768066<EFBFBD>]<5D>z<00>+<02>
GGRGB-D Mapping: Using Depth Cameras for Dense 3D Modeling of Indoor Environments<07>1 Problem Statement and Related Work RGB-D cameras are novel sensing systems that capture RGB images along with per-pixel depth information. RGB-D cameras rely on either structured light patterns combined with stereo sensing [6, 10] or time-of-flight laser sensing [1] to generate depth estimates that can be associated with RGB pixels. Very soon, small, high-quality RGB-D cameras developed for computer gaming and home entertainment applications will become available at cost below $100. In this paper we investigate how such cameras can be used in the context of robotics, specifically for building dense 3D maps of indoor environments. Such maps have applications in robot navigation, manipulation, semantic mapping, and telepresence. The robotics and computer vision communities have developed a variety of techniques for 3D mapping based on laser range scans [8, 11], stereo cameras [7], monocular cameras [3], and unsorted collections of photos [4]. While RGB-D cameras provide the opportunity to build 3D maps of unprecedented richness, they have drawbacks that make their application to 3D mapping difficult: They provide depth only up to a limited distance (typically less than 5m), depth values are much noisier than those provided by laser scanners, and their field of view (∼ 60 •) is far more constrained than that of specialized cameras or laser scanners typically used for 3D mapping (∼ 180 •). In our work, we use a camera developed by PrimeSense [10]. The key insights of this investigation are: first, that existing frame matching techniques are not sufficient to provide robust visual odometry with these cameras; second, that a tight integration of depth and color information can yield robust frame matching and loop closure detection; third, that building on best practice techniques in SLAM and computer graphics makes it possible to build and visualize accurate and extremely rich 3D maps with such cameras; and, fourth, that it will be feasible to build complete robot navigation and interaction systems solely based on cheap depth cameras. Following best practice in robot mapping, our RGB-D mapping technique consists of three key components: first, the spatial alignment of consecutive data frames; second, the detection of loop closures; and, third, the globally consistent alignment of the complete data sequence. Alignment between successive frames is computed by jointly optimizing over both appearance and shape matching. Appearance-based alignment is done with RANSAC over SIFT features annotated with 3D position. The 3D SIFT matching requires no initial estimate of the …ISERrobotics/2017-09-11T23:06:49.4637119142017-09-11T23:06:49.463711914


n
n<00><0E>}
{<02>	
3GGWeighted Finite-state Transducers in Speech Recognition<07>We survey the weighted finite-state transducer (WFST) approach to speech recognition developed at AT&T over the last several years. We show that WFSTs provide a common and natural representation for HMM models, context-dependency, pronunciation dictionaries, grammars, and alternative recognition outputs. Furthermore, general finite-state operations combine these representations flexibly and efficiently. Weighted determinization and minimization algorithms optimize their time and space requirements , and a weight pushing algorithm distributes the weights along the paths of a weighted transducer optimally for speech recognition. As an example, we describe a North American Business News (NAB) recognition system built using these techniques that combines the HMMs, full crossword triphones, a lexicon of forty thousand words, and a large trigram grammar into a single weighted transducer that is only somewhat larger than the trigram word grammar and that runs NAB in real-time on a very simple decoder. In another example, we show that the same techniques can be used to optimize lattices for second-pass recognition. In a third example , we show how finite-state operations can be used to assemble lattices from different recognizers to improve recognition performance .speech_recognition/2017-09-11T23:06:49.9094309082017-09-11T23:06:49.909430908
`<05>`<00>/<2F>
W<02>q%GGLinear work suffix array construction<07>Suffix trees and suffix arrays are widely used and largely interchangeable index structures on strings and sequences. Practitioners prefer suffix arrays due to their simplicity and space efficiency while theoreticians use suffix trees due to linear-time construction algorithms and more explicit structure. We narrow this gap between theory and practice with a simple linear-time construction algorithm for suffix arrays. The simplicity is demonstrated with a C&plus;&plus; implementation of 50 effective lines of code. The algorithm is called DC3, which stems from the central underlying concept of <i>difference cover</i>. This view leads to a generalized algorithm, DC, that allows a space-efficient implementation and, moreover, supports the choice of a space--time tradeoff. For any <i>v</i> &#8712; &lsqb;1,<i>&nradic;</i>&rsqb;, it runs in O(<i>vn</i>) time using O(<i>n</i>/<i>&vradic;</i>) space in addition to the input string and the suffix array. We also present variants of the algorithm for several parallel and hierarchical memory models of computation. The algorithms for BSP and EREW-PRAM models are asymptotically faster than all previous suffix tree or array construction algorithms.J. ACMstringology/2017-09-11T23:06:50.2790629882017-09-11T23:06:50.279062988<EFBFBD>i<EFBFBD>~
m<02>)53EEDecoding speech in the presence of other sources<07>The statistical theory of speech recognition introduced several decades ago has brought about low word error rates for clean speech. However, it has been less successful in noisy conditions. Since extraneous acoustic sources are present in virtually all everyday speech communication conditions, the failure of the speech recognition model to take noise into account is perhaps the most serious obstacle to the application of ASR technology. Approaches to noise-robust speech recognition have traditionally taken one of two forms. One set of techniques attempts to estimate the noise and remove its effects from the target speech. While noise estimation can work in low-to-moderate levels of slowly-varying noise, it fails completely in louder or more variable conditions. A second approach utilises noise models and attempts to decode speech taking into account thei presence. Again, model-based techniques can work for simple noises, but they are computationally complex under realistic conditions and require models for all sources present in the signal. In this paper, we propose a statistical theory of speech recognition in the presence of other acoustic sources. Unlike earlier model-based approaches, our framework makes no assumptions about the noise background, although it can exploit such information if it is available. It does not require models for background sources, nor an estimate of their number. The new approach extends statistical ASR by introducing a segregation model in addition to the conventional acoustic and language models. While the conventional statistical ASR problem is to find the most likely sequence of speech models which generated a given observation sequence, the new approach additionally determines the most likely set of signal fragments which make up the speech signal. Although the framework is completely general, we provide one interpretation of the segregation model based on missing-data theory. We derive an efficient HMM decoder which searches both across subword state and across alternative segregations of the signal between target and interference. We call this modified system the speech fragment decoder. The value of the speech fragment decoder approach has been verified through experiments on small-vocabulary tasks in high-noise conditions. For instance, in a noise-corrupted connected digit task, the new approach decreases the word error rate in the condition of factory noise at 5 dB SNR from over 59% for a standard ASR system to less than 22%.Speech Communicationspeech_recognition/2017-09-11T23:06:50.119114992017-09-11T23:06:50.11911499
<02>E<02><00>#<23>

q<02>)/%GGA taxonomy of suffix array construction algorithms<07>In 1990, Manber and Myers proposed suffix arrays as a space-saving alternative to suffix trees and described the first algorithms for suffix array construction and use. Since that time, and especially in the last few years, suffix array construction algorithms have proliferated in bewildering abundance. This survey paper attempts to provide simple high-level descriptions of these numerous algorithms that highlight both their distinctive features and their commonalities, while avoiding as much as possible the complexities of implementation details. New hybrid algorithms are also described. We provide comparisons of the algorithms' worst-case time complexity and use of additional space, together with results of recent experimental test runs on many of their implementations.ACM Comput. Surv.stringology/2017-09-11T23:06:50.4408369142017-09-11T23:06:50.440836914<EFBFBD>7<EFBFBD>
m<02>e
7GGEM Algorithms for Probabilistic Mapping Networks<07>The Expectation-Maximization (EM) algorithm is a general technique for maximum likelihood estimation (MLE). In this paper we present several of the important theoretical and practical issues associated with Gaussian mixture mod-eling (GMM) within the EM framework. First, we propose an EM algorithm for estimating the parameters of a special GMM structure, named a probablistic mapping network (PMN), where the Gaussian probability density function is realized as an internal node. In this way, the EM algorithm is extended to deal with the supervised learning of a multicategory classiication problem and serve as a parameter estimator of the neural network Gaussian classiier. Then, a generalized EM (GEM) algorithm is developed as an alternative to the MLE problem of PMN. This is followed by a discussion on the computational considerations and algorithmic comparisons. It is shown that GEM converges faster than EM to the same solution space. The computational eeciency and the numerical stability of the training algorithm beneet from the well-established EM framework. The eeectiveness of the proposed PMN architecture and developed EM algorithms are assessed by conducting a set of speaker recognition experiments. INRIA Apprentissage de RRseaux Probabilistes par Algorithmes EM RRsumm : L'algorithme "Expectation-Maximisation" (EM) est une technique gg-nnrale pour l'estimation par maximum de vraisemblance. Ce document prrsente quelques aspects thhoriques et pratiques importants liis la moddlisation par mm-langes de gaussienne (GMM) dans le cadre EM. Nous proposons d'abord un algo-rithme EM pour estimer le parammtres d'un moddle GMM particulier, appell PMN ("probabilistic mapping network"), dans lequel la fonction de densitt de probabilitt gaussienne est calculle par un noeud interne du rrseau. Nons prrsentons ensuite un algorithm EM ggnnraliss (GEM) comme une solution alternative l'estimation par maximum de vraisemblance d'un PMN. Cette prrsentation est complltte par une discussion sur les aspects calculatoires comparrs des deux algorithmes EM et GEM. Nous montrons en particulier que GEM converge plus vite que EM vers le mmme espace de solutions. L'eecacitt pratique de l'architecture PMN et des algo-rithmes EM proposss est valuue travers un ensemble d'exemples pratiques dans le domaine de la reconnaissance de locuteurs.sublinear_algorithms/2017-09-11T23:06:50.3626389162017-09-11T23:06:50.362638916
	<09><08><05>0<00><15>
7<02>?7%GGFast String Searching<07>SUMMARY Since the Boyer-Moore algorithm was described in 1977, it has been the standard benchmark for the practical string search literature. Yet this yardstick compares badly with current practice. We describe two algorithms that perform 47% fewer comparisons and are about 4.5 times faster across a wide range of architectures and compilers. These new variants are members of a family of algorithms based on the skip loop structure of the preferred , but often neglected, fast form of Boyer-Moore. We present a taxonomy for this family, and describe a toolkit of components that can be used to design an algorithm most appropriate for a given set of requirements.Softw., Pract. Exper.stringology/2017-09-11T23:06:50.9340639652017-09-11T23:06:50.934063965<EFBFBD>(<28><00><02>77==The Space Complexity of Approximating the Frequency Moments<07>The frequency moments of a sequence containing m i elements of type i, for 1 ≤ i ≤ n, are the numbers F k = n i=1 m k i. We consider the space complexity of randomized algorithms that approximate the numbers F k , when the elements of the sequence are given one by one and cannot be stored. Surprisingly, it turns out that the numbers F 0 , F 1 and F 2 can be approximated in logarithmic space, whereas the approximation of F k for k ≥ 6 requires n Ω(1) space. Applications to data bases are mentioned as well.J. Comput. Syst. Sci.streaming_algorithms/2017-09-11T23:06:50.88652017-09-11T23:06:50.8865<EFBFBD><10>
s<02>{#7GGCounting Large Numbers of Events in Small Registers<07>It is possible to use a small counter to keep approximate counts of large numbers. The resulting expected error can be rather precisely controlled. An example is given in which 8-bit counters (bytes) are used to keep track of as many as 130,000 events with a relative error which is substantially independent of the number <italic>n</italic> of events. This relative error can be expected to be 24 percent or less 95 percent of the time (i.e. <italic>&sgr;</italic> = <italic>n</italic>/8). The techniques could be used to advantage in multichannel counting hardware or software used for the monitoring of experiments or processes.Commun. ACMstreaming_algorithms/2017-09-11T23:06:50.8459160162017-09-11T23:06:50.845916016<EFBFBD>,<2C>
<00>
77GGProbabilistic Counting Algorithms for Data Base Applications<07>J. Comput. Syst. Sci.streaming_algorithms/2017-09-11T23:06:50.7595449222017-09-11T23:06:50.759544922<EFBFBD>\<5C>
O<02>I#%GGA Fast String Searching Algorithm<07>An algorithm is presented that searches for the location, &#8220;<italic>i</italic>l&#8221; of the first occurrence of a character string, &#8220;<italic>pat</italic>,&#8221; in another string, &#8220;<italic>string</italic>.&#8221; During the search operation, the characters of <italic>pat</italic> are matched starting with the last character of <italic>pat</italic>. The information gained by starting the match at the end of the pattern often allows the algorithm to proceed in large jumps through the text being searched. Thus the algorithm has the unusual property that, in most cases, not all of the first <italic>i</italic> characters of <italic>string</italic> are inspected. The number of characters actually inspected (on the average) decreases as a function of the length of <italic>pat</italic>. For a random English pattern of length 5, the algorithm will typically inspect <italic>i</italic>/4 characters of <italic>string</italic> before finding a match at <italic>i</italic>. Furthermore, the algorithm has been implemented so that (on the average) fewer than <italic>i</italic> + <italic>patlen</italic> machine instructions are executed. These conclusions are supported with empirical evidence and a theoretical analysis of the average behavior of the algorithm. The worst case behavior of the algorithm is linear in <italic>i</italic> + <italic>patlen</italic>, assuming the availability of array space for tables linear in <italic>patlen</italic> plus the size of the alphabet.
3~Commun. ACMstringology/2017-09-11T23:06:50.5578278812017-09-11T23:06:50.557827881
9
<0A><07>9<00><1D>	
i<02>/-GGSqueak: a language for communicating with mice<07>Graphical user interfaces are difficult to implement because of the essential concurrency among multiple interaction devices, such as mice, buttons, and keyboards. <i>Squeak</i> is a user interface implementation language that exploits this concurrency rather than hiding it, helping the programmer to express interactions using multiple devices. We present the motivation, design and semantics of <i>squeak</i>. The language is based on concurrent programming constructs but can be compiled into a conventional sequential language; our implementation generates C code. We discuss how <i>squeak</i> programs can be integrated into a graphics system written in a conventional language to implement large but regular user interfaces, and close with a description of the formal semantics.SIGGRAPHuser_interfaces/2017-09-11T23:06:51.3414318852017-09-11T23:06:51.341431885<EFBFBD><1B><00>G<02>]%EEASAP: Automatic Smoothing for Attention Prioritization in Streaming Time Series Visualization<07>Time series visualization of streaming telemetry (i.e., charting of key metrics such as server load over time) is increasingly prevalent in recent application deployments. Existing systems simply plot the raw data streams as they arrive, potentially obscuring large-scale deviations due to local variance and noise. We propose an alternative: to better prioritize attention in time series exploration and monitoring visualizations, smooth the time series as much as possible to remove noise while still retaining large-scale structure. We develop a new technique for automatically smoothing streaming time series that adaptively optimizes this trade-off between noise reduction (i.e., variance) and outlier retention (i.e., kurtosis). We introduce metrics to quantitatively assess the quality of the choice of smoothing parameter and provide an efficient streaming analytics operator, ASAP, that optimizes these metrics by combining techniques from stream processing, user interface design, and signal processing via a novel autocorrelation-based pruning strategy and pixel-aware preaggregation. We demonstrate that ASAP is able to improve users' accuracy in identifying significant deviations in time series by up to 38.4% while reducing response times by up to 44.3%. Moreover, ASAP delivers these results several orders of magnitude faster than alternative optimization strategies.ArXivtime_series/2017-09-11T23:06:51.274002932017-09-11T23:06:51.27400293<EFBFBD><03><00><02>/?7GGAn elementary proof of a theorem of Johnson and Lindenstrauss<07>A result of Johnson and Lindenstrauss [13] shows that a set of n points in high dimensional Euclidean space can be mapped into an O(log n/⑀ 2)-dimensional Euclidean space such that the distance between any two points changes by only a factor of (1 Ϯ ⑀). In this note, we prove this theorem using elementary probabilistic techniques.Random Struct. Algorithmssublinear_algorithms/2017-09-11T23:06:51.0103601072017-09-11T23:06:51.010360107
 <0B> <00>p<EFBFBD>
s<02>1?%GGThe phase transition in inhomogeneous random graphs<07>The 'classical' random graph models, in particular G(n, p), are 'homogeneous', in the sense that the degrees (for example) tend to be concentrated around a typical value. Many graphs arising in the real world do not have this property, having, for example, power-law degree distributions. Thus there has been a lot of recent interest in defining and studying 'inhomogeneous' random graph models. One of the most studied properties of these new models is their 'robust-ness', or, equivalently, the 'phase transition' as an edge density parameter is varied. For G(n, p), p = c/n, the phase transition at c = 1 has been a central topic in the study of random graphs for well over 40 years. Many of the new inhomogeneous models are rather complicated; although there are exceptions, in most cases precise questions such as determining exactly the critical point of the phase transition are approachable only when there is independence between the edges. Fortunately, some models studied have this property already, and others can be approximated by models with independence. Here we introduce a very general model of an inhomogeneous random graph with (conditional) independence between the edges, which scales so that the number of edges is linear in the number of vertices. This scaling corresponds to the p = c/n scaling for G(n, p) used to study the phase transition; also, it seems to be a property of many large real-world graphs. Our model includes as special cases many models previously studied. We show that, under one very weak assumption (that the expected number of edges is 'what it should be'), many properties of the model can be determined, in particular the critical point of the phase transition, and the size of the giant component above the transition. We do this by relating our random graphs to branching processes, which are much easier to analyze. We also consider other properties of the model, showing, for example, that when there is a giant component, it is 'stable': for a typical random graph, no matter how we add or delete o(n) edges, the size of the giant component does not change by more than o(n).Random Struct. Algorithmstime_series/2017-09-11T23:06:51.6054809572017-09-11T23:06:51.605480957<EFBFBD><00>	_

1GGSystematic Review in Software Engineering<07>systematic_review/2017-09-11T23:06:51.5809460452017-09-11T23:06:51.580946045<EFBFBD>d<EFBFBD>
<00>k<02>I%GGRealizing quality improvement through test driven development: results and experiences of four industrial teams<07>Test-driven development (TDD) is a software development practice that has been used sporadically for decades. With this practice, a software engineer cycles minute-by-minute between writing failing unit tests and writing implementation code to pass those tests. Test-driven development has recently re-emerged as a critical enabling practice of agile software development methodologies. However, little empirical evidence supports or refutes the utility of this practice in an industrial context. Case studies were conducted with three development teams at Microsoft and one at IBM that have adopted TDD. The results of the case studies indicate that the pre-release defect density of the four products decreased between 40% and 90% relative to similar projects that did not use the TDD practice. Subjectively, the teams experienced a 15–35% increase in initial development time after adopting TDD.Empirical Software Engineeringtesting/tdd/2017-09-11T23:06:51.5162580572017-09-11T23:06:51.516258057

[
<EFBFBD>
gW
[<00>x<EFBFBD>
C<02>
'-GGProjecting a Modular Future<07>Two innovations are enhancing programming languages' capabilities. First, modularity lets you combine independently developed languages without changing their respective definitions. A language is no longer a fixed quantity; you can extend it with domain-specific constructs as needed. Second, projectional editing lets you build editors and IDEs that don't require parsers. Such editors and IDEs support a range of tightly integrated notations, including textual, symbolic, tabular, and graphical notations. In addition, by avoiding parsers, they avoid grammar composition's well-known limitations. Three examples illustrate how these two innovations affect programming-language design. A set of modular extensions of C for embedded programming enables efficient code generation and formal analysis. A language for requirements engineering flexibly combines structured and unstructured (prose) data. Finally, a language for defining insurance rules uses mathematical notation. These examples all rely on the open source JetBrains MPS (Meta Programming System) language workbench. This article is part of a special issue on Software Architecture.IEEE Softwareuser_interfaces/2017-09-11T23:06:52.3004499512017-09-11T23:06:52.300449951<EFBFBD><0C>
;<02>?/EEOne VM to rule them all<07>Building high-performance virtual machines is a complex and expensive undertaking; many popular languages still have low-performance implementations. We describe a new approach to virtual machine (VM) construction that amortizes much of the effort in initial construction by allowing new languages to be implemented with modest additional effort. The approach relies on abstract syntax tree (AST) interpretation where a node can rewrite itself to a more specialized or more general node, together with an optimizing compiler that exploits the structure of the interpreter. The compiler uses speculative assumptions and deoptimization in order to produce efficient machine code. Our initial experience suggests that high performance is attainable while preserving a modular and layered architecture, and that new high-performance language implementations can be obtained by writing little more than a stylized interpreter.Onward!virtual_machines/2017-09-11T23:06:52.217760012017-09-11T23:06:52.21776001<EFBFBD><06>	q

+GGMediapolis Mediapolis popular Culture and the City<07>audio_comp_sci/2017-09-11T23:06:52.1904099122017-09-11T23:06:52.190409912<EFBFBD><0B>
<00><02>Y/GGA comparison of software and hardware techniques for x86 virtualization<07>Until recently, the x86 architecture has not permitted classical trap-and-emulate virtualization. Virtual Machine Monitors for x86, such as VMware &#174; Workstation and Virtual PC, have instead used binary translation of the guest kernel code. However, both Intel and AMD have now introduced architectural extensions to support classical virtualization.We compare an existing software VMM with a new VMM designed for the emerging hardware support. Surprisingly, the hardware VMM often suffers lower performance than the pure software VMM. To determine why, we study architecture-level events such as page table updates, context switches and I/O, and find their costs vastly different among native, software VMM and hardware VMM execution.We find that the hardware support fails to provide an unambiguous performance advantage for two primary reasons: first, it offers no support for MMU virtualization; second, it fails to co-exist with existing software techniques for MMU virtualization. We look ahead to emerging techniques for addressing this MMU virtualization problem in the context of hardware-assisted virtualization.ASPLOSvirtual_machines/2017-09-11T23:06:52.0347871092017-09-11T23:06:52.034787109
j<00><0F><0F><0F>nF$<0E><0E><0E>vT0
<0A>
<0A>
<0A>
<0A>
n
@
<0C><0C><0C><0C>g9<0B><0B><0B><0B>]2

<EFBFBD>
<EFBFBD>
<EFBFBD>
a
6
	<09>	<09>	<09>	W	3<08><08><08><08>mI3<07><07>yR8<06><06><06>~^7
<05><05><05>kK
<04><04><04>vV1<03><03><03><03>`J*<02><02><02><02>mN*

<01>
<01>
<01>
~
W
2
<00>+<2B>X3
Alexander ReinefeldAlexanderReinefeld<1F>W'
Kathrin PeterKathrinPeter"<22>V+Andrew W. LeungAndrewW.Leung$<24>U-Russell C. SearsRussellC.Sears#<23>T+
Vadim YushprakhVadimYushprakh#<23>S+
Alexander LloydAlexanderLloyd<15>R
Yawei LiYaweiLi%<25>Q-#
Jean-Michel LeonJean-MichelLeon<1D>P%
James LarsonJamesLarson!<21>O)
Andrey KhorlinAndreyKhorlin<1C>N%J. J. FurmanJ.J.Furman$<24>M-James C. CorbettJamesC.Corbett<19>L!
Chris BondChrisBond<1B>K#
Jason BakerJasonBaker<19>J!
Jinyang LiJinyangLi<1B>I#
Jorge OrtizJorgeOrtiz<1F>H'
Russell PowerRussellPower<1D>G%
Zhaoguo WangZhaoguoWang<13>F
Qi ChenQiChen%<25>E-!
Chien-Chin HuangChien-ChinHuang$<24>D-Theodore W. HongTheodoreW.Hong<1F>C'
Brandon WileyBrandonWiley!<21>B)
Oskar SandbergOskarSandberg<19>A!
Ian ClarkeIanClarke<1D>@%
Yutaka SuzueYutakaSuzue"<22>?+Owen S. HofmannOwenS.Hofmann<1D>>%
Jinliang FanJinliangFan<1D>=%
Jeremy ElsonJeremyElson.<2E><7#Edmund B. NightingaleEdmundB.Nightingale<1F>;'
Werner VogelsWernerVogels!<21>:)
Peter VosshallPeterVosshall;<3B>9C#
+Swaminathan SivasubramanianSwaminathanSivasubramanian<1D>8%
Alex PilchinAlexPilchin%<25>7-
Avinash LakshmanAvinashLakshman1<6E>69#
!Gunavardhan KakulapatiGunavardhanKakulapati<1F>5'
Madan JampaniMadanJampani!<21>4)
Deniz HastorunDenizHastorun'<27>3/
Giuseppe DecandiaGiuseppeDecandia$<24>2-Robert E. GruberRobertE.Gruber<1D>1%
Andrew FikesAndrewFikes!<21>0)
Tushar ChandraTusharChandra(<28>/1Deborah A. WallachDeborahA.Wallach"<22>.+Wilson C. HsiehWilsonC.Hsieh#<23>-+
Sanjay GhemawatSanjayGhemawat<1D>,%
Jeffrey DeanJeffreyDean<17>+
Fay ChangFayChang$<24>*-Thomas B. SchönThomasB.Schön&<26>)/Michael I. JordanMichaelI.Jordan%<25>(-
Fredrik LindstenFredrikLindsten6<6E>'?'Christos H. PapadimitriouChristosH.Papadimitriou<17>&
Xiao YangXiaoYang<13>%
Shan HeShanHe<13>$
Zhen JiZhenJi!<21>#)
Yongpeng ZhangYongpengZhang<19>"!
Zexuan ZhuZexuanZhu-<2D>!5
'Martin Farach-ColtonMartinFarach-Colton&<26> /Michael A. BenderMichaelA.Bender<13>
Ian DeyIanDey8<79>A!Chandra Shekhar ChandrakarChandraShekharChandrakar!<21>)
Morteza KhayatMortezaKhayat><3E>G-Mohammad Ali Akhavan-BehabadiMohammadAliAkhavan-Behabadi <20>)Raed M. KafafyRaedM.Kafafy"<22>+Hesham A. RakhaHeshamA.Rakha"<22>+Waleed F. FarisWaleedF.Faris.<2E>7%M. Surendranath ReddyM.SurendranathReddy(<28>1Venkata Rami ReddyVenkataRamiReddy!<21>)
Ketaki SolankiKetakiSolanki0<69>9Mustansir Hatim PanchaMustansirHatimPancha(<28>1Sunil Kumar ShindeSunilKumarShinde$<24>-By C. E. ShannonByC. E.Shannon%<25>-
Łukasz JuszczykŁukaszJuszczyk(<28>1Butler W. LarnpsonButlerW.Larnpson<1F>'
Torben ThraneTorbenThrane<15>
Alan KayAlanKay<1F>'
Scott WallaceScottWallace<1D>
%
John MaloneyJohnMaloney<1B>#
Ted KaehlerTedKaehler<1B>#
Dan IngallsDanIngalls!<21>
)
Oluwafemi OshoOluwafemiOsho+<2B>	3
Francisca OgwuelekaFranciscaOgwueleka$<24>-Lauretta O. OshoLaurettaO.Osho"<22>+Nils J. NilssonNilsJ.Nilsson)<29>1
!Moisés GoldszmidtMoisésGoldszmidt<19>!
Dan GeigerDanGeiger<1D>%
Nir FriedmanNirFriedman"<22>+Joshua J. BlochJoshuaJ.Bloch+<2B>3
#Ioannis StavrakakisIoannisStavrakakis<1F>
'
Sofia SyntilaSofiaSyntila)<29>1
Nikolaos LaoutarisNikolaosLaoutaris<1D>%
Rémi CoulomRémiCoulom<19>~!
Avery WangAveryWang<19>}!
Bernd KolbBerndKolb<19>|!
Jos WarmerJosWarmer!<21>{)
Markus VölterMarkusVölter<1F>z'
Mario WolczkoMarioWolczko<19>y!
Doug SimonDougSimon#<23>x+
Gregor RichardsGregorRichards#<23>w+
Christian HumerChristianHumer!<21>v)
Gilles DuboscqGillesDuboscq<1F>u'
Lukas StadlerLukasStadler<1F>t'
Andreas WößAndreasWöß%<25>s-
Christian WimmerChristianWimmer)<29>r1
#Thomas WürthingerThomasWürthinger<15>q
Part OnePartOne!<21>p)
Jeroen BeltmanJeroenBeltman'<27>o/
%Marc SchuilenburgMarcSchuilenburg
<00>bZ<00><00>\<5C>
c<02>IGGMeta algorithms for hierarchical Web caches<07>— Large scale hierarchical caches for web content have been deployed widely in an attempt to reduce delivery delays and bandwidth consumption and also to improve the scalability of content dissemination through the world wide web. Irrespectively of the specific replacement algorithm employed in each cache, a de facto characteristic of contemporary hierarchical caches is that a hit for a document at an ¢-level cache leads to the caching of the document in all intermediate caches (levels ¢ ¤ £ ¦ ¥ ¨ § © © © § ¥) on the path towards the leaf cache that received the initial request. This paper presents various algorithms that revise this standard behavior and attempt to be more selective in choosing the caches that get to store a local copy of the requested document. As these algorithms operate independently of the actual replacement algorithm running in each individual cache, they are referred to as meta algorithms. Three new meta algorithms are proposed and compared against the de facto one and a recently proposed one1] by means of synthetic and trace-driven simulations. The best of the new meta algorithms appears to be able to lead to improved performance under most simulated scenarios, especially under a low availability of storage. The latter observation makes the presented meta algorithms particularly favorable for the handling of large data objects such as stored music files or short video clips. Additionally, a simple load balancing algorithm that is based on the concept of meta algorithms is proposed and evaluated. The algorithm is shown to be able to provide for an effective balancing of load thus possibly addressing the recently discovered " filtering-effect " in hierarchical web caches (C. Williamson [2]).IPCCCcaching/2017-09-11T23:06:52.6400639652017-09-11T23:06:52.640063965<EFBFBD><04><00><02>'3=GGEfficient Selectivity and Backup Operators in Monte-Carlo Tree Search<07>Monte-Carlo evaluation consists in estimating a position by averaging the outcome of several random continuations, and can serve as an evaluation function at the leaves of a min-max tree. This paper presents a new framework to combine tree search with Monte-Carlo evaluation , that does not separate between a min-max phase and a Monte-Carlo phase. Instead of backing-up the min-max value close to the root, and the average value at some depth, a more general backup operator is defined that progressively changes from averaging to min-max as the number of simulations grows. This approach provides a fine-grained control of the tree growth, at the level of individual simulations, and allows efficient selectivity methods. This algorithm was implemented in a 9 × 9 Go-playing program, Crazy Stone, that won the 10th KGS computer-Go tournament.Computers and Gamesartificial_intelligence/2017-09-11T23:06:52.5558491212017-09-11T23:06:52.555849121<EFBFBD><1A>
g<02>3+GGAn Industrial Strength Audio Search Algorithm<07>We have developed and commercially deployed a flexible audio search engine. The algorithm is noise and distortion resistant, computationally efficient, and massively scalable, capable of quickly identifying a short segment of music captured through a cellphone microphone in the presence of foreground voices and other dominant noise, and through voice codec compression, out of a database of over a million tracks. The algorithm uses a combinatorially hashed time-frequency constellation analysis of the audio, yielding unusual properties such as transparency, in which multiple tracks mixed together may each be identified. Furthermore, for applications such as radio monitoring, search times on the order of a few milliseconds per query are attained, even on a massive music database.ISMIRaudio_comp_sci/2017-09-11T23:06:52.4696230472017-09-11T23:06:52.469623047

:<02><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F>}rg\QF;0%<0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E>vk`UJ?4)
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
y
n
c
X
M
B
7
,
!


<0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C>|qf[PE:/$<0B><0B><0B><0B><0B><0B><0B><0B><0B><0B><0B><0B>uj_TI>3(
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
x
m
b
W
L
A
6
+
 


	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	{	p	e	Z	O	D	9	.	#		
	<08><08><08><08><08><08><08><08><08><08><08>~sh]RG<1'<07><07><07><07><07><07><07><07><07><07><07><07>wlaVK@5*	<06><06><06><06><06><06><06><06><06><06><06><06>zodYNC8-"
<05><05><05><05><05><05><05><05><05><05><05>}rg\QF;0%<04><04><04><04><04><04><04><04><04><04><04><04>uj_TI>3(<03><03><03><03><03><03><03><03><03><03><03><03>xmbWLA6+ 
<02><02><02><02><02><02><02><02><02><02><02><02><08>$<02>
d<08>#
:
d<08>"
d<08>!+
d<08> 
d<08>
d<08>
b<08>
b<08>
b<08>
<01>
b<08>{
b<08>
b<08>
b<08>
b<08>
b<08>
b<08>
a<08>
a<08>
a<08>

a<08>
a<08><00>
`<08>
`<08>


`<08><03>
`<08><03>
`<08>


_<08>		
_<08>
_<08>
_<08>
_<08>
^<08>
^<08>
^<08>
<01>
^<08>

^<08>

]<08>
]<08>~<03>
]<08>}<03>
]<08>|<03>
]<08>{
<01>
\<08>z<00>
\<08>y

\<08>x<03>
\<08>w<03>
\<08>v<03>
\<08>u

\<08>t<03>
[<08>s
d
[<08>r
'
[<08>q<03>
[<08>p

[<08>o<03>
Y<08>n<03>
Y<08>m<03>
Y<08>l<03>
Y<08>k<03>
Y<08>j<03>
W<08>i
<01>
W<08>h

W<08>g<00>
W<08>f<03>
U<08>e

U<08>d
^
T<08>c<03>
T<08>b<03>
T<08>a<03>
T<08>`<03>
T<08>_
]
T<08>^

T<08>]<03>
S<08>\<03>
S<08>[<03>
S<08>Zt
S<08>Y<03>
S<08>X<03>
Q<08>W<03>
Q<08>V<03>
Q<08>U<03>
Q<08>T

Q<08>S

P<08>R
<01>
P<08>Q
<01>
P<08>P<03>
P<08>OX
P<08>N<03>
P<08>M<03>
P<08>L<03>
O<08>K<03>
O<08>J

O<08>I<03>
O<08>H<03>
O<08>G<03>
M<08>F
<01>
M<08>E<03>
M<08>D
M<08>C<03>
M<08>B<03>
L<08>A<03>
L<08>@<03>
L<08>?
L<08>><03>
L<08>=
<01>
K<08><<00>
K<08>;
K<08>:<03>
K<08>9<03>
K<08>8<03>
I<08>7
<01>
G<08>6
<01>
G<08>5<03>
G<08>4<03>
G<08>3<03>
G<08>2<03>
F<08>1<03>
F<08>0<03>
F<08>/<03>
F<08>.<03>
F<08>-E
E<08>,<00>
E<08>+<03>
E<08>*<03>
E<08>)<03>
E<08>(<03>
E<08>'<03>
E<08>&<03>
E<08>%<03>
E<08>$<03>
D<08>#<03>
D<08>"<03>
D<07>!
U
D<08> <03>
D<08><03>
C<08>
<01>
C<08><03>
C<08><03>
C<08><03>
C<08><03>
B<08><03>
B<08>
<01>
B<08><03>
B<08><03>
B<08>F
@<08><03>
@<08><03>
@<08>z
@<08><03>
?<08><03>
?<08><03>
?<08>
<01>
?<08>
<03>
?<08>
<01>
=<08><03>
=<08>
<03>
=<08>	
<01>
=<08><03>
=<08><03>
<<08>

<<08><03>
<<08><03>
<<08><03>
<<08>
:<08>
<03>
:<08>
:<08><03>
:<08>~<03>
9<08>}<03>
9<08>|<03>
9<08>{<03>
9<08>z<03>
9<08>y<00>
8<08>x<03>
8<08>w<00>
8<08>v<03>
8<08>u<03>
8<08>t<03>
6<08>s<03>
6<08>r<03>
6<08>q
o
5<08>p<03>
5<08>o<03>
3<08>n<03>
3<08>m<03>
3<08>l<03>
3<08>k<03>
3<08>j<03>
2<08>i<03>
2<08>h<03>
2<08>g<02>
2<08>f<03>
1<08>e<03>
0<08>d

0<08>c
 
0<08>b<03>
0<08>a<00>
0<08>`

/<08>_<03>
/<08>^<02>
/<08>]<03>
/<08>\<03>
/<08>[
M
.<08>Z

.<08>Y
5
.<08>X<03>
.<08>W<03>
.<08>V<03>
-<08>U

-<08>T<03>
,<08>S<03>
,<08>R<03>
,<08>Q
b
,<08>P<03>
+<08>O<03>
+<07>N
.
+<08>M<03>
+<08>L

+<08>K

*<08>J<02>
*<08>I<03>
*<08>H<03>
*<08>G<03>
*<08>F<03>
*<08>E<03>
*<08>D<03>
*<08>C<03>
*<08>B

)<08>A

)<08>@

)<08>?
x
)<08>><03>
)<08>=<03>
(<08><<03>
(<08>;}
(<08>:<03>
(<08>9<03>
(<08>8<03>
(<08>7<03>
'<08>6
<01>
'<08>5<03>
'<08>4
'<08>3
X
'<08>2~
&<08>1<02>
&<08>0}
&<08>/
<01>
&<08>.|
&<08>-{
&<08>,
x
&<08>+z
&<08>*

&<08>)

%<08>(y
%<08>'x
%<08>&w
%<08>%

%<08>$v
$<08>#u
$<08>"t
$<08>!s
$<08> 

$<08>r
#<08>q
#<08>p
#<08>o
#<08>n
#<08>m
"<08>l
"<08>k
"<08>j
 <08>i
 <08>h
 <08>g
 <08>
 <08>f
<08>e
<08>d
<08>
<01>
<08>c
<08>
b
<08>a
<07>
(
<08>
`
<08>	_
<08>^
<08>]
<08>\
<08>[
<08>Z
<08>Y
<08>X
<08>
W
<08>V
<08>U
<08>~T
<08>}+
<08>|S
<08>{R
<08>zQ
<08>yP
<08>xO
<08>wN
<08>vM
<08>uL
<08>t<00>
<07>s
)
<08>rK
<08>q<00>
<08>pJ
<08>oI
<08>nH
<08>mG
<08>l
<01>
<08>kF
 names start falling into place, you're on the right track.</li><li><b>Names matter.</b> Strive for intelligibility, consistency, and symmetry. Every API is a little language, and people must learn to read and write it. If you get an API right, code will read like prose.</li><li><b>When in doubt, leave it out.</b> If there is a fundamental theorem of API design, this is it. It applies equally to functionality, classes, methods, and parameters. Every facet of an API should be as small as possible, but no smaller. You can always add things later, but you can't take them away.</li><li><b>Minimizing <i>conceptual weight</i> is more important than class- or method-count.</b></li><li><b>Keep APIs free of implementations details.</b> They confuse users and inhibit the flexibility to evolve. It isn't always obvious what's an implementation detail: Be wary of overspecification.</li><li><b>Minimize mutability.</b> Immutable objects are simple, thread-safe, and freely sharable.</li><li><b>Documentation matters.</b> No matter how good an API, it won't get used without good documentation. Document every exported API element: every class, method, field, and parameter.</li><li><b>Consider the performance consequences of API design decisions,</b> but don't warp an API to achieve performance gains. Luckily, good APIs typically lend themselves to fast implementations.</li><li><b>APIs must coexist peacefully with the platform, so do what is customary.</b> It is almost always wrong to "transliterate" an API from one platform to another.</li><li><b>Minimize accessibility; when in doubt, make it private.</b> This simplifies APIs and reduces coupling.</li><li><b>Subclass only if you can say with a straight face that every instance of the subclass is an instance of the superclass.</b> Exposed classes should never subclass just to reuse implementation code.</li><li><b>Design and document for inheritance or else prohibit it.</b> This documentation takes the form of self-use patterns: how methods in a class use one another. Without it, safe subclassing is impossible.</li><li><b>Don't make the client do anything the library could do.</b> Violating this rule leads to boilerplate code in the client, which is annoying and error-prone.</li><li><b>Obey the principle of least astonishment.</b> Every method should do the least surprising thing it could, given its name. If a method doesn't do what users think it will, bugs will result.</li><li><b>Fail fast.</b> The sooner you report a bug, the less damage it will do. Compile-time is best. If you must fail at run-time, do it as soon as possible.</li><li><b>Provide programmatic access to all data available in string form.</b> Otherwise, programmers will be forced to parse strings, which is painful. Worse, the string forms will turn into de facto APIs.</li><li><b>Overload with care.</b> If the behaviors of two methods differ, it's better to give them different names.</li><li><b>Use the right data type for the job.</b> For example, don't use string if there is a more appropriate type.</li><li><b>Use consistent parameter ordering across methods.</b> Otherwise, programmers will get it backwards.</li><li><b>Avoid long parameter lists,</b> especially those with multiple consecutive parameters of the same type.</li><li><b>Avoid return values that demand exceptional processing.</b> Clients will forget to write the special-case code, leading to bugs. For example, return zero-length arrays or collections rather than nulls.</li><li><b>Throw exceptions only to indicate exceptional conditions</b>. Otherwise, clients will be forced to use exceptions for normal flow control, leading to programs that are hard to read, buggy, or slow.</li><li><b>Throw unchecked exceptions unless
c<02>{-#GGHow to design a good API and why it matters<07>In lieu of a traditional , I've tried to distill the essence of the talk into a collection of maxims:<ul><li><b>All programmers are API designers.</b> Good programs are modular, and intermodular boundaries define APIs. Good modules get reused.</li><li><b>APIs can be among your greatest assets or liabilities.</b> Good APIs create long-term customers; bad ones create long-term support nightmares.</li><li><b>Public APIs, like diamonds, are forever.</b> You have one chance to get it right so give it your best.</li><li><b>APIs should be easy to use and hard to misuse.</b> It should be easy to do simple things; possible to do complex things; and impossible, or at least difficult, to do wrong things.</li><li><b>APIs should be self-documenting:</b> It should rarely require documentation to read code written to a good API. In fact, it should rarely require documentation to write it.</li><li><b>When designing an API, first gather requirements - with a healthy degree of skepticism.</b> People often provide solutions; it's your job to ferret out the underlying problems and find the best solutions.</li><li><b>Structure requirements as use-cases:</b> they are the yardstick against which you'll measure your API.</li><li><b>Early drafts of APIs should be short,</b> typically one page with class and method signatures and one-line descriptions. This makes it easy to restructure the API when you don't get it right the first time.</li><li><b>Code the use-cases against your API before you implement it</b>, even before you specify it properly. This will save you from implementing, or even specifying, a fundamentally broken API.</li><li><b>Maintain the code for uses-cases as the API evolves.</b> Not only will this protect you from rude surprises, but the resulting code will become the examples for the API, the basis for tutorials and tests.</li><li><b>Example code should be exemplary.</b> If an API is used widely, its examples will be the archetypes for thousands of programs. Any mistakes will come back to haunt you a thousand fold.</li><li><b>You can't please everyone so aim to displease everyone equally.</b> Most APIs are overconstrained.</li><li><b>Expect API-design mistakes due to failures of imagination.</b> You can't reasonably hope to imagine everything that everyone will do with an API, or how it will interact with every other part of a system.</li><li><b>API design is not a solitary activity.</b> Show your design to as many people as you can, and take their feedback seriously. Possibilities that elude your imagination may be clear to others.</li><li><b>Avoid fixed limits on input sizes.</b> They limit usefulness and hasten obsolescence.</li><li><b>If it's hard to find good names, go back to the drawing board.</b> Don't be afraid to split or merge an API, or embed it in a more general setting. If<00>
<05>5<08><05>
]<02>o
QGGAxiomatic Basis for Computer Programming<07>This paper considers a formal method, known as axiomatic semantics, used to prove the correctness of a computer program. This formal method extracts, using some proof rules, the mathematical verification conditions from a computer program. The axioms of program flow, including, sequential flow, iteration, and alternation flows are presented. Using the axiomatic basis the completeness of two variants of integer multiplication program is proved. Results show that computer programs can actually be verified sufficiently for correctness without necessarily testing them, or more practically put, to complement their testing.comp_sci_fundamentals_and_history/2017-09-11T23:06:53.1634179692017-09-11T23:06:53.163417969<EFBFBD>@<40><00><02>)
QGGThe Quest for Artificial Intelligence a History of Ideas and Achievements<07>In the second full paragraph of page 21, change George A. Miller's dates from " (1920—) " to " (1920—2012) " In the last full paragraph of page 33, replace " The claim that these " in the sentence " The claim that these two ... " by " That these " and eliminate the parenthetical sentence following that sentence, (" The claim has not. .. "). Move footnote #51 to occur along with footnote #50.comp_sci_fundamentals_and_history/2017-09-11T23:06:52.8973090822017-09-11T23:06:52.897309082<EFBFBD>G<EFBFBD>
E<02>-=GGBayesian Network Classifiers<07>Recent work in supervised learning has shown that a surprisingly simple Bayesian classifier with strong assumptions of independence among features, called naive Bayes, is competitive with state-of-the-art classifiers such as C4.5. This fact raises the question of whether a classifier with less restrictive assumptions can perform even better. In this paper we evaluate approaches for inducing classifiers from data, based on the theory of learning Bayesian networks. These networks are factored representations of probability distributions that generalize the naive Bayesian classifier and explicitly represent statements about independence. Among these approaches we single out a method we call Tree Augmented Naive Bayes (TAN), which outperforms naive Bayes, yet at the same time maintains the computational simplicity (no search involved) and robustness that characterize naive Bayes. We experimentally tested these approaches, using problems from the University of California at Irvine repository, and compared them to C4.5, naive Bayes, and wrapper methods for feature selection.Machine Learningartificial_intelligence/2017-09-11T23:06:52.7979379882017-09-11T23:06:52.797937988
<00>z<07><0F><0F><0F><07><08><0F><0F><0F>*wn<08>XI<07>?2'
<0E><08><0E><08><07><0E><0E><0E><06>Z<0E><0E>q<0E><08><0E><06><07><0E>sj<08>]N6(<07>E
<0A>
<0A>
<0A>t<08>
<0A>
<0A>
|
q
g
^
R<06>
I<06>
2

<0C><0C>N<0C><0C><0C><0C><0C><0C><0C>tb<07>YIA8<06><06>."
<0B><0B><0B>B<0B><0B><0B>wgQ?&z<06>Z
<EFBFBD>
<EFBFBD>
<EFBFBD>+<07>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD><07>
v
Y
P
>
+
!


<08>	<09>	<09>	<09>z	<09>	<09>	<09>	<09>	<09> 	<09>	<09>	j	\	E	7	*			<08>g)rough estimate~+quantum channeln!relativityd5reactive programming[
reactiveH
pre-copyC	qemuB'pop operation?5potential antecedent<	safe51personal computing/reduct#quorum!popularsecrecy!provenance<03>poincar<03>+paxos algorithm<03>3resource allocation<03>pig<03>!repository<03>!percolator<03>	rati<03>	prob<03>predicate<03>
ramcloud<03>%registration<03>5replication protocol<03>+process crashes<03>/reliable delivery<03>pow<03>-relational model<03>psi<03> Cperformance and consistency<03>	pnutv
pmcmcrpgaormqgpricpracticalX	seam<00>
sdd-1
*scheduler
jschedul
lsch rli
F
scanning<00>/scaling procedure<02>
scalable
<01>-sampling service
<01>!
same topicD
salsa	saa
Q	rush
rus<00>
run-time<02>rpc<02>)ros production<00>roadway<02>%road surface<02>
rithm
'ripemd<00>	rime<00>	rgbd<02>'rgb-d mapping<02>%rgb-d camera<02>rfs:=
rest architectural style+1resource discovery
Aresilient overlay networks
<01>!resilience
<01>#
resemblanceS!reputation
<01>replica

repli
<01>

renderingh
relevant<00>)relative error3relational database
'
reinforcement/-regular category<02>#
reflectanceo1
reference database1reference counting
<01>+reference count
<01>#refactoringwrecursionu=reconstruction algorithm<00>#reclamationWrecent
reboot<00>
realismg	read<00>rcuU
rbfw#
ray tracingkray<00>%randomforest9)random testing!%random graph,random
<01>
radio<
radiance<00>racket)race condition<00>
quotient<02>!quickcheck
queue<00>-query processing
+)quantum search<02>/quantum computing<02>qos
<01>puzzle<00>put
B	push
<01>
pulse<00>;public-key cryptosystem<00>!public-key<00>!psychology<02>=prototype-based language<02>/programming model
d%programmatic$9probabilistic countingproach<02>

privilege1priority inversion<00>primitive
<01>primary
<01>prfpreterm
<01>preterDpre!powergraph
z
posixg	port<02>#polymorphic<02>9
poisson reconstructionupointer
<01>
pmvx%plementation<00>plementzplanner<02>
plaid
Ipitfall
<01>	ping
<01>!
photograph{-phase transition/pes8pertur/personal computer<00>1persistent storage<00>&Operformance and energy efficiency<00>pen<00>	pcsa)paxos protocol
<01>
 @<00><0B><0B>
<0A>x]
<0A>$
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
u
)	<09>K	}	R	><08><08>rM<0E>*<07><07><07>N<0E><06><06>x<00>J<05><05><04><04>^
<0A>M<03><03><03><0F>T=	<02><02>S6
<01>
<01>
7<00><00><0F><0F>P"k provenance
]?Secure network provenance
]@<04>
The BUDS Language for Distributed Bayesian Machine Learning9uTesting ecological models: the meaning of validation<00>L<04>Techniques for Automated Generation of Testbed Infrastructures for SOA
P<04>!Teaching Garbage Collection without Implementing Compilers or Interpreters<00>._Systematic Review in Software Engineering
1eSymbolic Representation and Natural Language
;Support-vector networks<00>J<04>Structural asymmetries of perisylvian regions in the preterm newborn<00>>Stronger Semantics for Low-Latency Geo-Replicated Storage
\+YStasis: Flexible Transactional Storage
*3iSqueak: a language for communicating with mice
	/Spherical hashing
D=}Spartan: A Distributed Array Framework with Smart Tiling
(0e
Sparrow: distributed, low latency schedulingv4kSpanner: Google's globally-distributed database
.T<04>)Solaris Zones: Operating System Support for Consolidating Commercial Workloads<00>#Soft Typing<00>G<04>
Sinfonia: A new paradigm for building scalable distributed systemstV<04>/
Simple, Fast, and Practical Non-Blocking and Blocking Concurrent Queue Algorithms@<40>
<04>Simple Testing Can Prevent Most Critical Failures: An Analysis of Production Failures in Distributed Data-Intensive Systems<00><{Signal/Collect: Graph Algorithms for the (Semantic) Web
[N<04>
Shape Grammars and the Generative Specification of Painting and Sculpture/=}Self-stabilizing Systems in Spite of Distributed Control
Z-_
Security Concerns in Android mHealth AppsL<04>ScatterAlloc: Massively parallel dynamic memory allocation for the GPU<00>/c
Safety Verification of Deep Neural NetworksX<04>1SWIM: Scalable Weakly-consistent Infection-style Process Group Membership Protocol<00>L<04>	Reverend Bayes on Inference Engines: A Distributed Hierarchical ApproachA
Resilient Overlay Networksw=
Replication, history, and grafting in the Ori file systemu1eRemoving gamification from an enterprise SNS<00>"GReflections on Trusting Trust<00>$KRecent SRI work in verification
Xu<04>kRealizing quality improvement through test driven development: results and experiences of four industrial teams

'Real-Time FRP<00>B<04>Rapidly-Exploring Random Trees: A New Tool for Path Planning<00>)Random Forests<00>*Y
RRB-Trees: Efficient Immutable VectorsIU<04>+RGB-D Mapping: Using Depth Cameras for Dense 3D Modeling of Indoor Environments<00>U<04>+RADOS: a scalable, reliable storage service for petabyte-scale storage clusters
+K<04>QuickCheck: a lightweight tool for random testing of Haskell programs<00>*WQuickCheck Testing for Fun and Profit<00>&OQuantum-enhanced machine learning<00>?Qualitative data analysis
!
PushPull++-._Push-pull functional reactive programming<00>8sPurely functional lazy nondeterministic programming<00>7Propositions as Types<00> CProjecting a Modular Future
;yProgramming languages - application and interpretation<00>J<04>Programming and reasoning with algebraic effects and dependent types<00>
<01>Programming Languages: History and Future<00>;yProgrammatic and direct manipulation, together at last<00>$M
Procedural modeling of buildings2B<04>Probabilistic Counting Algorithms for Data Base Applications
3iPrincipal Type-Schemes for Functional Programs<00>5o
Pregel: a system for large-scale graph processings?<04>

Practical byzantine fault tolerance and proactive recoveryq)UPracticaASoK: Eternal War in Memory
<01>7Propositions as types
<01>4kProgramming with algebraic effects and handlers
<01>1eQuantum vacuum pressure on a conducting slab
<01>E<04>RAY: Integrating Rx and Async for Direct-Style Reactive Streams
<01>c<04>GRewriting nation-state: borderland literatures of India and the question of state sovereignty
},[Reducing Garbage Collector Cache Misses
k-_
The Dangers of Replication and a SolutiondD<04>
The Chubby Lock Service for Loosely-Coupled Distributed Systemsx0e
The Case for Determinism in Database SystemsO"I
The Byzantine Generals Problemy/Sparse Partitions
_
<04><07><04><00> <20>
e
<0A>)
QGGSymbolic Representation and Natural LanguageThe n o t ion of s y m bolizability is taken as the second requisite of comp u t a tion (the first being 'a l g o r i t h m i z a b i l i t y '), and it is shown that symbols, qua symbols, are not symbolizable. This has farreaching consequences for the computational study of language and for Al-research in language understanding. The representation hypothesis is formulated, and its various assumptions and goals are examined. A research strategy for the computational study of natural language u n d erstanding is outlined.comp_sci_fundamentals_and_history/2017-09-11T23:06:53.3767080082017-09-11T23:06:53.376708008<EFBFBD>i<EFBFBD><00>-<02>m
QGGBack to the future: the story of Squeak, a practical Smalltalk written in itself<07>Squeak is an open, highly-portable Smalltalk implementation whose virtual machine is written entirely in Smalltalk, making it easy to debug, analyze, and change. To achieve practical performance, a translator produces an equivalent C program whose performance is comparable to commercial Smalltalks. Other noteworthy aspects of Squeak include: a compact object format that typically requires only a single word of overhead per object; a simple yet efficient incremental garbage collector for 32-bit direct pointers; efficient bulk-mutation of objects; extensions of BitBlt to handle color of any depth and anti-aliased image rotation and scaling; and real-time sound and music synthesis written entirely in Smalltalk. It includes platform-independent support for color, sound, and image processing. Originally developed on the Macintosh, members of its user community have since ported it to numerous platforms including Windows 95 and NT, Windows CE, all common flavors of UNIX, and the Acorn. Squeak stands alone as a practical Smalltalk in which a researcher, professor, or motivated student can examine source code for every part of the system, including graphics primitives and the virtual machine itself, and make changes immediately and without needing to see or deal with any language other than Smalltalk. It also runs bit-identical images across its wide portability base. Three strands weave through this paper:. 1 the design of the Squeak virtual machine, which differs in several interesting ways from the implementation presented in the Smalltalk "Blue Book" [Gold83] and explored in the "Green Book" [Kras83];. 2 an implementation strategy based on writing the Squeak virtual machine in Smalltalk and translating it into C, using an existing Smalltalk for bootstrapping until Squeak was able to debug and generate its own virtual machine; and. 3 the incremental development process through which Squeak was created and evolved over the course of a year.comp_sci_fundamentals_and_history/2017-09-11T23:06:53.3192250982017-09-11T23:06:53.319225098

<05><05>
M<02>%
QGGHints for Computer System Design<07>A b s t r a c t Experience with the design and implementation of a number of computer systems, and study of many other systems , has led to some general hints for system design which are described here. They are illustrated by a number of examples, ranging from hardware such as the Alto and the Dorado to applications programs such as Bravo and Star. Designing a computer system is very different from designing an algorithm: The external interface (i.e., the requirement) is more complex, less precisely defined, and more subject to change. The system has much more internal structure, and hence many internal interfaces. The measure of success is much less clear. The designer usually finds himself floundering in a sea of possibilities, unclear about how one choice will limit his freedom to make other choices, or affect the size and performance of the entire system. There probably isn't a best way to build the system, or even any major part of it; much more important is to avoid choosing a terrible way, and to have clear division of responsibilities among the parts. I have designed and built a number of computer systems, some that worked and some that didn't. I have also used Permission to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage, the ACM copyright notice and the title of the publication and its date appear, and notice is given that copying is by permission of the Association for Computing Machinery. To copy otherwise, or to republish, requires a fee and/or specific permission. and studied many other systems, both successful and unsuccessful. From this experience come some general hints for designing successful systems. I claim no originality for them; most are part of the folk wisdom of experienced designers. Nonetheless, even the expert often forgets, and after the second system [6] comes the fourth one. Disclaimer'. These are not novel (with a few exceptions), foolproof recipes, laws of system design or operation, precisely formulated, consistent, always appropriate, approved by all the leading experts, or guaranteed to work; they are just hints. Some are quite general and vague; others are specific techniques which are more widely applicable than many people know. Both the hints and the illustrative examples are necessarily oversimplified. Many are controversial. I have tried to avoid exhortations to …comp_sci_fundamentals_and_history/2017-09-11T23:06:53.6186210942017-09-11T23:06:53.618621094
n<04>vk<>	?

'GGQualitative data analysis<07>data_science/2017-09-11T23:06:54.4604838872017-09-11T23:06:54.460483887y<EFBFBD>	W


/GGCompressors with Vanes-Based Diffuserdata_replication/2017-09-11T23:06:54.3325910642017-09-11T23:06:54.332591064y<EFBFBD>	[

'GGCommunication Theory of Secrecy Systems<07>cryptography/2017-09-11T23:06:54.2032370612017-09-11T23:06:54.203237061<EFBFBD><0E><00><02>i
3GGTechniques for Automated Generation of Testbed Infrastructures for SOA<07>Service-oriented architecture (SOA), as
c<02>{##GGDatabase metatheory: asking the big queries<07>Is " database theory " an oxymoron? Or is ata platitude? What is the fitness measure that decides the surviva! of ideas (and areas) in mathematics, in applted science, and in computer science? Which ideas from database theory during the past twenty-five years have influenced research in other fields of computer science? How many were encapsulated in actual products? Was the rela-tional model the on[y true paradigm sh@ m computer science ? Is applicability the only and ultimate justification of theoretical research in an applied science? Are applicability pressures rea!ly exogenous and unwelcome? Are negattve results appropriate goals of theoretical research in an appiied science —or are they the on[y pos-sibie such research goals? If scientific theories must be refutab!e, what are the " hard facts " that provide the possibility of refutation in the case of database theory?SIGACT Newsdatastores/2017-09-11T23:06:55.1269331052017-09-11T23:06:55.126933105<EFBFBD>'<27>!
g<02>C/GGHigh-throughput DNA sequence data compression<07>The exponential growth of high-throughput DNA sequence data has posed great challenges to genomic data storage, retrieval and transmission. Compression is a critical tool to address these challenges, where many methods have been developed to reduce the storage size of the genomes and sequencing data (reads, quality scores and metadata). However, genomic data are being generated faster than they could be meaningfully analyzed, leaving a large scope for developing novel compression algorithms that could directly facilitate data analysis beyond data transfer and storage. In this article, we categorize and provide a comprehensive review of the existing compression methods specialized for genomic data and present experimental results on compression ratio, memory usage, time for compression and decompression. We further present the remaining challenges and potential directions for future research.Briefings in Bioinformaticsdata_compression/2017-09-11T23:06:55.0235319822017-09-11T23:06:55.023531982<EFBFBD><19> 
?<02>W-GGThe LCA Problem Revisited<07>We present a very simple algorithm for the Least Common Ancestor problem. We thus dispel the frequently held notion that an optimal LCA computation is unwieldy and unimplementable. Interestingly, this algorithm is a sequentialization of a previously known PRAM algorithm of Berkman, Breslauer,LATINdata_structures/2017-09-11T23:06:54.9059260252017-09-11T23:06:54.905926025<EFBFBD>j<EFBFBD>
-<02>
-EEIdeal Hash Trees<07>Hash Trees with nearly ideal characteristics are described. These Hash Trees require no initial root hash table yet are faster and use significantly less space than chained or double hash trees. Insert, search and delete times are small and constant, independent of key set size, operations are O(1). Small worst-case times for insert, search and removal operations can be guaranteed and misses cost less than successful searches. Array Mapped Tries(AMT), first described in Fast and Space Efficient Trie Searches, Bagwell [2000], form the underlying data structure. The concept is then applied to external disk or distributed storage to obtain an algorithm that achieves single access searches, close to single access inserts and greater than 80 percent disk block load factors. In addition two further applications of AMTs are briefly described, namely, Class/Selector dispatch tables and IP Routing tables. Each of the algorithms has a performance and space usage that is comparable to contemporary implementations but simpler.data_structures/2017-09-11T23:06:54.591232912017-09-11T23:06:54.59123291

<01>
<EFBFBD><06>
<01><00>I<EFBFBD>%
o<02>#GGDynamo: amazon's highly available key-value store<07>Reliability at massive scale is one of the biggest challenges we face at Amazon.com, one of the largest e-commerce operations in the world; even the slightest outage has significant financial consequences and impacts customer trust. The Amazon.com platform, which provides services for many web sites worldwide, is implemented on top of an infrastructure of tens of thousands of servers and network components located in many datacenters around the world. At this scale, small and large components fail continuously and the way persistent state is managed in the face of these failures drives the reliability and scalability of the software systems.
 This paper presents the design and implementation of Dynamo, a highly available key-value storage system that some of Amazon's core services use to provide an "always-on" experience. To achieve this level of availability, Dynamo sacrifices consistency under certain failure scenarios. It makes extensive use of object versioning and application-assisted conflict resolution in a manner that provides a novel interface for developers to use.SOSPdatastores/2017-09-11T23:06:55.4775620122017-09-11T23:06:55.477562012<EFBFBD>c<EFBFBD>$<00>
<02>=#GGBigtable: A Distributed Storage System for Structured Data<07>Bigtable is a distributed storage system for managing structured data that is designed to scale to a very large size: petabytes of data across thousands of commodity servers. Many projects at Google store data in Bigtable, including web indexing, Google Earth, and Google Finance. These applications place very different demands on Bigtable, both in terms of data size (from URLs to web pages to satellite imagery) and latency requirements (from backend bulk processing to real-time data serving). Despite these varied demands, Bigtable has successfully provided a flexible, high-performance solution for all of these Google products. In this article, we describe the simple data model provided by Bigtable, which gives clients dynamic control over data layout and format, and we describe the design and implementation of Bigtable.ACM Trans. Comput. Syst.datastores/2017-09-11T23:06:55.3095371092017-09-11T23:06:55.309537109<EFBFBD>s<EFBFBD>#
W<02>9U-EEParticle gibbs with ancestor sampling<07>Particle Markov chain Monte Carlo (PMCMC) is a systematic way of combining the two main tools used for Monte Carlo statistical inference: sequential Monte Carlo (SMC) and Markov chain Monte Carlo (MCMC). We present a new PMCMC algorithm that we refer to as particle Gibbs with ancestor sampling (PGAS). PGAS provides the data analyst with an off-the-shelf class of Markov kernels that can be used to simulate, for instance, the typically high-dimensional and highly autocorrelated state trajectory in a state-space model. The ancestor sampling procedure enables fast mixing of the PGAS kernel even when using seemingly few particles in the underlying SMC sampler. This is important as it can significantly reduce the computational burden that is typically associated with using SMC. PGAS is conceptually similar to the existing PG with backward simulation (PGBS) procedure. Instead of using separate forward and backward sweeps as in PGBS, however, we achieve the same effect in a single forward sweep. This makes PGAS well suited for addressing inference problems not only in state-space models, but also in models with more complex dependencies, such as non-Markovian, Bayesian nonparametric, and general probabilistic graphical models.Journal of Machine Learning Researchdata_structures/2017-09-11T23:06:55.170247072017-09-11T23:06:55.17024707

0<0B>~
0<00>J<EFBFBD>(
}<02>KQ#GGSpartan: A Distributed Array Framework with Smart Tiling<07>Application programmers in domains like machine learning, scientific computing, and computational biology are accustomed to using powerful, high productivity array languages such as MatLab, R and NumPy. Distributed array frameworks aim to scale array programs across machines. However, maximizing the locality of access to distributed arrays is an unsolved problem; such locality is critical for high performance. This paper presents Spartan, a distributed array framework that automatically determines how to best partition (aka " tile ") n-dimensional arrays and to co-locate data with computation to maximize locality. Spartan combines a lazy-evaluation based, optimizing frontend with a distributed tiled array backend. Central to Spartan's design is a small number of carefully chosen parallel high-level operators, which form the expression graph captured by Spartan's frontend during runtime. These operators simplify the programming of distributed applications. More importantly , their well-defined semantics allow Spartan's runtime to calculate the costs of different tiling strategies and pick the best one for evaluating the entire expression graph. Using Spartan, we have implemented 12 applications from a variety of domains including machine learning and scientific computing. Our evaluations show that Spartan's automatic tiling mechanism leads to good and scalable performance while eliminating the need for manual tiling.USENIX Annual Technical Conferencedatastores/2017-09-11T23:06:56.6635939942017-09-11T23:06:56.663593994<EFBFBD><11>'<00><02><03>
#GGFreenet: A Distributed Anonymous Information Storage and Retrieval System<07>We describe Freenet, an adaptive peer-to-peer network application that permits the publication, replication, and retrieval of data while protecting the anonymity of both authors and readers. Freenet operates as a network of identical nodes that collectively pool their storage space to store data les and cooperate to route requests to the most likely physical location of data. No broadcast search or centralized location index is employed. Files are referred to in a location-independent manner, and are dynamically replicated in locations near requestors and deleted from locations where there is no interest. It is infeasible to discover the true origin or destination of a le passing through the network, and diicult for a node operator to determine or be held responsible for the actual physical contents of her own node.Workshop on Design Issues in Anonymity and Unobservabilitydatastores/2017-09-11T23:06:55.9057900392017-09-11T23:06:55.905790039<EFBFBD>i<EFBFBD>&
;<02>#GGFlat Datacenter Storage<07>Flat Datacenter Storage (FDS) is a high-performance, fault-tolerant, large-scale, locality-oblivious blob store. Using a novel combination of full bisection bandwidth networks, data and metadata striping, and flow control, FDS multiplexes an application's large-scale I/O across the available throughput and latency budget of every disk in a cluster. FDS therefore makes many optimizations around data locality unnecessary. Disks also communicate with each other at their full bandwidth, making recovery from disk failures extremely fast. FDS is designed for datacenter scale, fully distributing metadata operations that might otherwise become a bottleneck. FDS applications achieve single-process read and write performance of more than 2 GB/s. We measure recovery of 92 GB data lost to disk failure in 6.2 s and recovery from a total machine failure with 655 GB of data in 33.7 s. Application performance is also high: we describe our FDS-based sort application which set the 2012 world record for disk-to-disk sorting.OSDIdatastores/2017-09-11T23:06:55.6546130372017-09-11T23:06:55.654613037
<02><0C><06><02><00>n<EFBFBD>+<00>+<02>#GGRADOS: a scalable, reliable storage service for petabyte-scale storage clusters<07>Brick and object-based storage architectures have emerged as a means of improving the scalability of storage clusters. However, existing systems continue to treat storage nodes as passive devices, despite their ability to exhibit significant intelligence and autonomy. We present the design and implementation of RADOS, a reliable object storage service that can scales to many thousands of devices by leveraging the intelligence present in individual storage nodes. RADOS preserves consistent data access and strong safety semantics while allowing nodes to act semi-autonomously to self-manage replication, failure detection, and failure recovery through the use of a small cluster map. Our implementation offers excellent performance, reliability, and scalability while providing clients with the illusion of a single logical object store.PDSWdatastores/2017-09-11T23:06:58.1716298832017-09-11T23:06:58.171629883<EFBFBD><1E>*
Y<02>S#GGStasis: Flexible Transactional Storage<07>An increasing range of applications requires robust support for atomic, durable and concurrent transactions. Databases provide the default solution, but force applications to interact via SQL and to forfeit control over data layout and access mechanisms. We argue there is a gap between DBMSs and file systems that limits designers of data-oriented applications.
 Stasis is a storage framework that incorporates ideas from traditional write-ahead logging algorithms and file systems. It provides applications with flexible control over data structures, data layout, robustness, and performance. Stasis enables the development of unforeseen variants on transactional storage by generalizing write-ahead logging algorithms. Our partial implementation of these ideas already provides specialized (and cleaner) semantics to applications.
 We evaluate the performance of a traditional transactional storage system based on Stasis, and show that it performs favorably relative to existing systems. We present examples that make use of custom access methods, modified buffer manager semantics, direct log file manipulation, and LSN-free pages. These examples facilitate sophisticated performance optimizations such as zero-copy I/O. These extensions are composable, easy to implement and significantly improve performance.OSDIdatastores/2017-09-11T23:06:58.0458588872017-09-11T23:06:58.045858887<EFBFBD>x<EFBFBD>)<00>-<02>1#GGMegastore: Providing Scalable, Highly Available Storage for Interactive Services<07>Megastore is a storage system developed to meet the requirements of today's interactive online services. Megas-tore blends the scalability of a NoSQL datastore with the convenience of a traditional RDBMS in a novel way, and provides both strong consistency guarantees and high availability. We provide fully serializable ACID semantics within fine-grained partitions of data. This partitioning allows us to synchronously replicate each write across a wide area network with reasonable latency and support seamless failover between datacenters. This paper describes Megastore's semantics and replication algorithm. It also describes our experience supporting a wide range of Google production services built with Megastore.CIDRdatastores/2017-09-11T23:06:57.0791010742017-09-11T23:06:57.079101074

<01>A<07><04>
<01><00><1D>/
m<02>=#GGTransactional storage for geo-replicated systems<07>We describe the design and implementation of Walter, a key-value store that supports transactions and replicates data across distant sites. A key feature behind Walter is a new property called <i>Parallel Snapshot Isolation</i> (PSI). PSI allows Walter to replicate data asynchronously, while providing strong guarantees within each site. PSI precludes write-write conflicts, so that developers need not worry about conflict-resolution logic. To prevent write-write conflicts and implement PSI, Walter uses two new and simple techniques: preferred sites and counting sets. We use Walter to build a social networking application and port a Twitter-like application.SOSPdatastores/2017-09-11T23:06:58.4117089842017-09-11T23:06:58.411708984<EFBFBD>{<7B>.
k<02>w#GGSpanner: Google's globally-distributed database<07>Spanner is Google&#8217;s scalable, multiversion, globally distributed, and synchronously replicated database. It is the first system to distribute data at global scale and support externally-consistent distributed transactions. This article describes how Spanner is structured, its feature set, the rationale underlying various design decisions, and a novel time API that exposes clock uncertainty. This API and its implementation are critical to supporting external consistency and a variety of powerful features: nonblocking reads in the past, lock-free snapshot transactions, and atomic schema changes, across all of Spanner.SYSTORdatastores/2017-09-11T23:06:58.3364541022017-09-11T23:06:58.336454102<EFBFBD>K<EFBFBD>-<00>
<02>w!#GGBuilding global and scalable systems with atomic multicast<07>The rise of worldwide Internet-scale services demands large distributed systems. Indeed, when handling several millions of users, it is common to operate thousands of servers spread across the globe. Here, replication plays a central role, as it contributes to improve the user experience by hiding failures and by providing acceptable latency. In this work, we claim that atomic multicast, with strong and well-defined properties, is the appropriate abstraction to efficiently design and implement globally scalable distributed systems. We substantiate our claim with the design of two modern online services atop atomic multicast, a strongly consistent key-value store and a distributed log.Middlewaredatastores/2017-09-11T23:06:58.2859409182017-09-11T23:06:58.285940918<EFBFBD>;<3B>,<00>'<02>3#GGConsistency and fault tolerance for erasure-coded distributed storage systems<07>One challenge in applying erasure codes (or error-correcting codes) to distributed storage systems is to maintain consistency between data and redundancy blocks in the face of crashing servers. We present two access protocols that provide sequential consistency and maximum distance separable fault tolerance at the same time. The protocols use sequence numbers to recover a consistent version in the presence of failures or partial writes. The first (pessimistic) PSW protocol uses a master per stripe to execute updates in sequence. The second (optimistic) OCW protocol allows concurrent writes to blocks in the same stripe to happen in parallel at the cost of additional buffer space.
 We present empirical performance results for PSW and OCW and compare them to other protocols. Our results show that OCW is as fast as simple replication while providing better fault tolerance and/or reduced storage overhead. This demonstrates that erasure coding can be used as a space-efficient alternative to replication in distributed storage systems.DICT@HPDCdatastores/2017-09-11T23:06:58.2233759772017-09-11T23:06:58.223375977
M<00>
<01>9
A'<0C>

<0C>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
o
W
F
4
#
	<09>	<09>	<09>	<09>	<09>	<09>	{	f	V	D	4	%		<08><08><08><08><08><08><08>lXE<0C>0
<07><07><07><07><07><07><07><07>l[
-L<,
<06><06><06><06><06><06><06>|iUD0
<05><05><05><05><05><05>s]M9%<0C><0C><04><04><04><04><04><04>v`OA>+<03><0B><03><03><03><03><03>weTB/<0B><02><02><02>}<02><02><02>mUB5%
<01>
<01>
<01>
<01>
<01><0C>
<01>
<01><0F><0F><0F><0F><0F><0F><0F>yj[H6#
<0E><0E><0E><0E><0E><0B><0E><0E>n^<0B>M;+<0C>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
w
i
PkWR. FreiF%R. E. Castro<03>R. Coelho<04>R. Casale<04>#R. Carvalho<04>R. Bansal<03>!R. Araújo<04>Qiong Fei<03>)
Qingxiong Yangl!Qiang YangQi ChenF)
Pushmeet Kohlis1Przemyslaw Wegrzyn<02>-
Prasad Kawthekar/#Pranay Jain
<01>'Prakash Linga<03>/Poul-Henning KampX'Pietro Baronit;Pierre-Évariste Dagand<02>+Phillip Rogaway<00>/Philippe Flajolet<02>-Philippas TsigasV'Philip Wadler%Philip Stutz<03>#Philip Shao<00>%Philip S. Yu#'Philip Pronin
<01>3Philip A. Bernstein
%Phil Bagwell<00>)Petra S. Huppi
<01>3Peter-Pike J. Sloan<00>#Peter Wonka<00>%Peter Wegner<02>)Peter Vosshall:%Peter Sewell<00>'Peter Sanders<02>#Peter Marksa#Peter Henry<02>-Peter G. Neumann<03>)Peter Druschel<03>5Peter Boehler Bishope%Peter Bailis<02>#Perry Cheng
<01>+Per-Åke Larson<00>/Pedro M. Domingos9Pedro J. Muñoz Merino<03>-Paula Gomes Mian<02>)Paul R. Wilson
Z)Paul Nordstrom
T!Paul Hudak-Paul F. Syverson<03>-Paul E. MckenneyE#Paul BarhamZ/Paul A. Beardsley<00>+Patrick Wendell
{)Patrick StuediM-
Patrick Mcdaniel%Patrick Hunt<03>/Patrick E. O'neil
.3
Patrick D. Mcdaniel
)Pat Stephenson|#Pat Helland<00>)Pascal Müller<00>'Parveen Patel
%
Part One<02>7Parisa Jalili MarandiZ+Parantap Lahiri
#%Paolo Viotti<00>'P. T. Kroener6
P. Sousa<04>!P. SchwabldP. Radu<04>#P. QueirósZ#P. Pontisso<03>!P. Pockros$!P. Pereira<04>P. OtazuaM#P. Ministro<04>+P. M. Rodrigues<03>'P. J. Giraudi<03>'P. Invernizzi#
P. Geyer<04>
P. Fomin	'P. Figueiredo|#P. Buggisch<04>%P. Azimzadeh-#P. Andreone)P. Alexandrino<04>%P. A. Mircea>+Owen S. Hofmann?)
Otmar Hilligesp)Oskar SandbergB-Oscar Nierstrasz
)3Opim Salim Sitompul<02>)Oluwafemi Osho
)Oliver Riordan<02>'Oleg Kiselyov!Ole Agesen<02>#O. PlehutsaO. Negm<04>O. Bochar%Nuria Oliver
<01>Noga Alon<02>!Nir Shavit<00>%Nir Friedman!Ning Zhang
<01>+Nils J. Nilsson+Nikolas IoannouK1Nikolaos Laoutaris+Nicolas Schipero)Nick Mathewson<03>#Nick Benton<02>1Nicholas Smallbone<00>-Nhan Nguyen DangU'Neha Narkhede
?#Neal Harris<02>%Navendu Jain
<01>#Naty Leiser
o1Nathanael Schärli
*)Nathan Goodman
)Natalie Sebanzm3Naohiro Hayashibara
<01>)Nancy A. Lynchg-
Nal Kalchbrenner'-Naga Rekha Malae<00>3Nachiappan Nagappan<02>#N. Sakiyama

N. Rosso<03>%N. Pfisterer)N. Muscatiello<04>nN. Machida<04>N. Hüser!N. Göschlc%N. Demanzini<03>%N. Al Hajjar<04>)Márk Jelasity
<01>9Mus%Peter Wittek<05>-Randy L. Buckner<05>+Ramana M. Idury<05>)Philipp Haller<05>'Raouf Boutaba<05>!EProofreader Jennifer Mcclain<05>-Peter J. Bentley<05>)Robert Beverly<02>%Robert Beals<02>)Pooja Aggarwal<05>'Owen Callanan<05>!Ravi Kumar<05>)Paula B. Cohen<05>)Paula Tretkoff<05>R. Daegon<05>#N. Sasahira<05>#N. Yamamoto}#N. TakaharazR. Uchinoy)P. N. N. DesaioN. Ohashij3Robbert Van Renesse
<01>
Rob Pike<02>!Rob Arthan<00>%Rilla Khaled
<01>+Richard Steigerf+Richard Mortier
<01>/Richard L. Hudson
<01>-Richard Carlsson<00>3
Richard A. Newcomber!Reuven Lax
Q'Rean Griffith
2!Ravi Chugh	'
Raunaq Rewari0#Rasmus Pagh<00>!Randy Katz
;'Randy H. Katz
4)
Randolph LopezG!Rami Yared
<01>9
Rafael Pérez Y PérezQ)Raed M. Kafafy+Radek Vingralek<00>-Rachid Guerraoui<00>'Rachel Jewkes<03>%R.l.d. Sirli<03>'R. T. Marinho<04>%R. Sydorchuk'R. Slim Karam<04>R. ShireyCR. Sayegh<04>!R. Quispel1!R. Masetti<04>#R. Lupusoru<03>
R. LiU3R. Ha-Vinh Leuchter
<01>'R. Gonçalves<04>R. Gaspar<04>!R. G. Mare<03>
j<00><0F><0F><0F>a<<0E><0E><0E><0E><0E>b3

<0A>
<0A>
<0A>
y
;

<0C><0C><0C><0C>T8<0B><0B><0B>zK
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
z
R
4
	<09>	<09>	<09>	<09>	z	X	0	<08><08><08><08>^><07><07><07><07>eG)
<06><06><06>qN'<05><05><05><05>^>$<04><04><04>qD<03><03><03>|^B<02><02><02><02>b@

<01>
<01>
<01>
R
<00>'<27>B/
!Srecko JoksimovicSreckoJoksimovic:<3A>AC%José A. Ruipérez ValienteJoséA. RuipérezValiente8<65>@A%Marko C. J. D. Van EekelenMarkoC. J. D. VanEekelen2<6E>?;Achilleas L. D. BuismanAchilleasL. D.Buisman!<21>>)
Marco SerafiniMarcoSerafini$<24>=-Benjamin C. ReedBenjaminC.Reed0<64><9Flavio Paiva JunqueiraFlavioPaivaJunqueira<1F>;'
Mahadev KonarMahadevKonar<1D>:%
Patrick HuntPatrickHunt*<2A>93Gregory V. ChocklerGregoryV.Chockler<1D>8%
Harris HymanHarrisHyman$<24>7-Paul F. SyversonPaulF.Syverson!<21>6)
Nick MathewsonNickMathewson%<25>5-
!Roger DingledineRogerDingledine<19>4!
James LangJamesLang<1B>3#
Tim RoselliTimRoselli<1F>2'
Rachel JewkesRachelJewkes'<27>1/
Stephanie MiedemaStephanieMiedema<1B>0#
Xian WarnerXianWarner<17>/
Emma FuluEmmaFulu<1B>.#
David PelegDavidPeleg#<23>-+
Baruch AwerbuchBaruchAwerbuch*<2A>,3Jeroen Van De GraafJeroenVan DeGraaf%<25>+-
Christian FranckChristianFranck<1B>*#
Micah SherrMicahSherr<1E>)'Boon Thau LooBoonThauLoo'<27>(/
Andreas HaeberlenAndreasHaeberlen<1F>''
Arjun NarayanArjunNarayan<17>&
Qiong FeiQiongFei<1D>%%
Wenchao ZhouWenchaoZhou$<24>$-William W. CohenWilliamW.Cohen'<27>#/
Abraham BernsteinAbrahamBernstein<1D>"%
Philip StutzPhilipStutz(<28>!1Edsger W. DijkstraEdsgerW.Dijkstra*<2A> 3William P. ThurstonWilliamP.Thurston$<24>-Peter G. NeumannPeterG.Neumann <20>)Karl N. LevittKarlN.Levitt!<21>)
Peter DruschelPeterDruschel#<23>+
Antony RowstronAntonyRowstron'<27>/
#Deniz AltinbükenDenizAltinbüken<19>!
Ali GhodsiAliGhodsi%<25>-
Benjamin HindmanBenjaminHindman<1B>#
Frank DabekFrankDabek<1B>#
Daniel PengDanielPeng<1D>%
Diego OngaroDiegoOngaro<1F>'
Alfred TarskiAlfredTarski<1F>'
Prakash LingaPrakashLinga<1F>'
Mike PatersonMikePaterson(<28>1Michael J. FischerMichaelJ.Fischer%<25>-
Ernesto JiménezErnestoJiménez<1D>%
Mikel LarreaMikelLarrea%<25>-
Cristian MartínCristianMartín!<21>)
Brannon BatsonBrannonBatson <20>
)Eric A. BrewerEricA.Brewer<19>!
Milo PolteMiloPolte <20>)K. Mani ChandyK.ManiChandy!<21>
)
Keith MarzulloKeithMarzullo%<25>	-
Özalp BabaoğluÖzalpBabaoğlu<1F>'
Sung-Eui YoonSung-EuiYoon<1F>'
Shih-Fu ChangShih-FuChang<19>!
Junfeng HeJunfengHe<1F>'
Youngwoon LeeYoungwoonLee<1B>#
Jae-Pil HeoJae-PilHeo<1B>#
Dogan EnginDoganEngin<1B>#
Mark RobsonMarkRobson<1B>
#
Sharad GoelSharadGoel%<25>-
Chandan ShanbhagChandanShanbhag<1B>#
Saul JaspanSaulJaspan<1F>~'
Donald BeaverDonaldBeaver<1D>}%
Manoj PlakalManojPlakal!<21>|)
!Pat StephensonPatStephenson<1D>{%
Mike BurrowsMikeBurrows*<2A>z3Luiz André BarrosoLuizAndréBarroso,<2C>y5Benjamin H. SigelmanBenjaminH.Sigelman%<25>x-
Mendel RosenblumMendelRosenblum(<28>w1!John K. OusterhoutJohnK.Ousterhout<1D>v%
Sachin KattiSachinKatti<1F>u'
Ryan StutsmanRyanStutsman&<26>t/Stephen M. RumbleStephenM.Rumble<19>s!
Asaf CidonAsafCidon*<2A>r3!Larry J. StockmeyerLarryJ.Stockmeyer)<29>q1
%Deniz AltınbükenDenizAltınbüken<1D>p%
Wenbing ZhaoWenbingZhao#<23>o+
Nicolas SchiperNicolasSchiper<11>n
Chi HoChiHo<15>m
S KabbajSKabbaj<19>l!
S BouchibaSBouchiba;<3B>kC#
+Venugopalan RamasubramanianVenugopalanRamasubramanian <20>j)James B. OrlinJamesB.Orlin <20>i)T. V. LakshmanT.V.Lakshman(<28>h1Murali S. KodialamMuraliS.Kodialam <20>g)Nancy A. LynchNancyA.Lynch#<23>f+
Richard SteigerRichardSteiger,<2C>e5Peter Boehler BishopPeterBoehlerBishop<1B>d#
Carl HewittCarlHewitt<15>c
Dirk FoxDirkFox<1B>b#
Ryan FarellRyanFarell<1B>a#
Peter MarksPeterMarks<1B>`#
Ben MoseleyBenMoseley)<29>_1
#Stefan DziembowskiStefanDziembowski<1B>^#
Yair SovranYairSovran"<22>]+Brian F. CooperBrianF.Cooper'<27>\/
Benoît GarbinatoBenoîtGarbinato#<23>[+
Fernando PedoneFernandoPedone.<2E>Z7Parisa Jalili MarandiParisaJaliliMarandi<1B>Y#
Samuel BenzSamuelBenz
X
<EFBFBD>X<00>*<2A>2
1<02>#
GGOut of the Tar Pit<07>Complexity is the single major difficulty in the successful development of large-scale software systems. Following Brooks we distinguish accidental from essential difficulty, but disagree with his premise that most complexity remaining in contemporary systems is essential. We identify common causes of complexity and discuss general approaches which can be taken to eliminate them where they are accidental in nature. To make things more concrete we then give an outline for a potential complexity-minimizing approach based on functional programming and Codd's relational model of data.design/2017-09-11T23:06:58.5830649412017-09-11T23:06:58.583064941<EFBFBD>#<23>1
M<02>yy/GGIntroduction to Cryptocurrencies<07>We provide a research-oriented introduction to the cryptographic currencies. We start with a description of Bitcoin and its main design principles. We then discuss some of its weaknesses, and show some ideas for dealing with them. We also talk about the mechanics of the mining pools and ideas for discouraging the mining pool creation. We provide an introduction to the smart contracts, and give some examples of them, including the multiparty lotteries.
 We then present alternative currencies that were designed to remedy some of the problems of Bitcoin. In particular, we talk about the Litecoin, the Primecoin, the Permacoin, the Zerocoin, the Proofs of Stake and the Proofs of Space. We also discuss the most important research challenges in this area.ACM Conference on Computer and Communications Securitydigital_currency/2017-09-11T23:06:58.5634689942017-09-11T23:06:58.563468994<EFBFBD>O<EFBFBD>0<00><02>#GGWarp: Lightweight Multi-Key Transactions for Key-Value Stores<07>Traditional NoSQL systems scale by sharding data across multiple servers and by performing each operation on a small number of servers. Because transactions on multiple keys necessarily require coordination across multiple servers, NoSQL systems often explicitly avoid making transactional guarantees in order to avoid such coordination. Past work on transactional systems control this coordination by either increasing the granularity at which transactions are ordered, sacrificing serializability, or by making clock synchronicity assumptions. This paper presents a novel protocol for providing serializable transactions on top of a sharded data store. Called acyclic transactions, this protocol allows multiple transactions to prepare and commit simultaneously, improving concurrency in the system, while ensuring that no cycles form between concurrently-committing transactions. We have fully implemented acyclic transactions in a document store called Warp. Experiments show that Warp achieves 4× higher throughput than Sinfo-nia's mini-transactions on the standard TPC-C benchmark with no aborts. Further, the system achieves 75% of the throughput of the non-transactional key-value store it builds upon.ArXivdatastores/2017-09-11T23:06:58.5182739262017-09-11T23:06:58.518273926
g<04>g<00>j<EFBFBD>4
<02>[W/GGBitcoin<07>kamoto veröffentlichten digitalen Zahlungssystems Bitcoin [2] ist eigentlich irreführend – „digitale Münzen“ gibt es in Bitcoin nämlich nicht. Zumindest technisch gesehen ist Bitcoin kein digitales Geld wie beispielsweise DigiCash [1]. Technisch ähnelt Bitcoin eher einem großen, öffentlichen Haushaltsbuch: In einer immer länger werdenden Liste (Blockchain) werden Transaktionen (Blocks) aneinandergereiht, deren Höhe in „Bitcoin“-Einheiten bemessen wird. Damit stellen die Teilnehmer sich gegenseitig gewissermaßen „Schuldscheine“ aus, in denen sie sich zur Zahlung virtueller <00><><1F>3
a<02>I
/GGAn Analysis of the Cryptocurrency Industry<07>INTRODUCTION The cryptocurrency market has evolved erratically and at unprecedented speed over the course of its short lifespan. Since the release of the pioneer anarchic cryptocurrency, Bitcoin, to the public in January 2009, more than 550 cryptocurrencies have been developed, the majority with only a modicum of success [1]. Research on the industry is still scarce. The majority of it is singularly focused on Bitcoin rather than a more diverse spread of cryptocurrencies and is steadily being outpaced by fluid industry developments, including new coins, technological progression, and increasing government regulation of the markets. Though the fluidity of the industry does, admittedly, present a challenge to research, a thorough evaluation of the cryptocurrency industry writ large is necessary. This paper seeks to provide a concise yet comprehensive analysis of the cryptocurrency industry with particular analysis of Bitcoin, the first decentralized cryptocurrency. Particular attention will be given to examining theoretical economic differences between existing coins. Section 1 of this paper provides an overview of the industry. Section 1.1 provides a brief history of digital currencies, which segues into a discussion of Bitcoin in section 1.2. Section 2 of this paper provides an in-depth analysis of coin economics, partitioning the major currencies by their network security protocol mechanisms, and discussing the long-term theoretical implications that these classes entail. Section 2.1 will discuss network security protocol. The mechanisms will be discussed in the order that follows. Section 2.2 will discuss the proof-of-work (PoW) mechanism used in the Bitcoin protocol and various altcoins. Section 2.3 will discuss the proof-of-stake (PoS) protocol scheme first introduced by Peercoin in 2011, which relies on a less energy intensive security mechanism than PoW. Section 2.4 will discuss a hybrid PoW/PoS mechanism. Section 2.5 will discuss the Byzantine Consensus mechanism. Section 2.6 presents the results of a systematic review of 21 cryptocurrencies. Section 3 provides an overview of factors affecting industry growth, focusing heavily on the regulatory environment in section 3.1. Section 3.2 discusses public perception and acceptance of cryptocurrency as a payment system in the current retail environment. Section 4 concludes the analysis. A note on sources: Because the cryptocurrency industry is still young and factors that impact it are changing on a daily basis, few comprehensive or fully updated academic sources exist on the topic. While academic work was of course consulted for this project, the majority of the information that informs this paper was derived from …digital_currency/2017-09-11T23:06:58.6634121092017-09-11T23:06:58.663412109„Bitcoin“ an andere Teilnehmer verpflichten. Neue Transaktionen werden von dem transferierenden Teilnehmer mit einem Zeitstempel versehen, digital unterschrieben und publiziert. Durch unabhängige Teilnehmer der Bitcoin Community (den Minern) wird jeder neue Block geprüft und im Erfolgsfall über einen kryptographischen Hashwert fest mit dem bis dato letzten Eintrag der Liste verknüpft. Die Transaktionsliste ist per Peer-to-Peer-Netzwerk redundant über das Internet verteilt und jedem Teilnehmer zugänglich – eine zentrale Verwaltungsinstanz (wie z. B. eine Bank) ist überflüssig. Die Teilnehmer melden sich unter einem (oder mehreren) Pseudonym(en) an; ihre geheimen kryptografischen Schlüssel, mit denen sie die Gültigkeit einer Transaktion zu ihren Gunsten nachweisen und über ihr Guthaben weiter verfügen können, sind in einem lokalen oder von einem Dienstleister verwalteten Wallet gespeichert (das man nicht verlieren oder löschen sollte). Double Spending (das mehrfache Ausgeben einer digitalen Münze), ein zentrales Problem bei elektronischen Währungen, gibt es bei Bitcoin im eigentlichen Sinne nicht. Denn in diesem „Überweisungs-Logbuch“ sind keine Konto-Überziehungen erlaubt: Transferieren darf man nur
u<02>Q#5GGA History of the Virtual Synchrony Replication Model<07>In this chapter, we discuss a widely used fault-tolerant data replication model called virtual synchrony. The model responds to two kinds of needs. First, there is the practical question of how best to embed replication into distributed systems. Virtual synchrony defines dynamic process groups that have self-managed membership. Applications can join or leave groups at will: a process group is almost like a replicated variable that lives in the network. The second need relates to performance. Although state machine replication is relatively easy to understand, protocols that implement state machine replication in the standard manner are too slow to be useful in demanding settings, and are hard to deploy in very large data centers of the sort seen in today's cloud-computing environments. Virtual synchrony implementations, in contrast, are able to deliver updates at the same data rates (and with the same low latencies) as IP multicast: the fast (but unreliable) Internet multi-cast protocol, often supported directly by hardware. The trick that makes it possible to achieve these very high levels of performance is to hide overheads by piggyback-ing extra information on regular messages that carry updates. The virtual synchrony replication model has been very widely adopted, and was used in everything from air traffic control and stock market systems to data center management platforms marketed by companies like IBM and Microsoft. Moreover, in recent years, state machine protocols such as those used in support of Paxos have begun to include elements of the virtual synchrony model, such as self-managed and very dynamic membership. Our exploration of the model takes the form of a history. We start by exploring the background, and then follow evolution of the model over time. A " Cloud Computing " revolution is underway, supported by massive data centers that often contain thousands (if not hundreds of thousands) of servers. In such systems , scalability is the mantra and this, in turn, compels application developers to replicate various forms of information. By replicating the data needed to handle client requests, many services can be spread over a cluster to exploit parallelism.Replicationdistributed_systems/2017-09-11T23:06:58.7708830572017-09-11T23:06:58.770883057
<00>
<01><0F><0F><0F><0F><0F>hSF= <0E><0E><0E><0E><0E><0E>hQC4
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
y
h
W
F
6
$
<0C><0C><0C><0C><0C><0C><0C><0C><0C><0C>oeC<0B><0B><0B><0B><0B><0B>pXH:*
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>

l
_
F
8
-


	<09>	<09>	<09>	<09>	<09>	<09>	{	`	P	A	)	<08><08><08><08><08><08><08><08><08>j[NA8-<07><07><07><07><07><07><07><07><07><07>}t\QH2<06><06><06><06><06><06><06>vlND2!<05><05><05><05><05><05><05>|pfXJA<04><04><04><04><04><04><04><04><04>tXNC(<03><03><03><03><03><03>ne\RI5<02><02><02><02><02><02>xeP?/&

<01>
<01>
<01>
<01>
<01>
<01>
<01><06>zvul<07>yaslr<06>xwar<13>w-analysis threads	<09>vvictim
<EFBFBD>uevasion<0B>tblessing<0B>svanadium<0B>rtutorial<06>qiot
<0A>p!delegation<0E>o#choi matrix<12>n+quantum channel<10>m'test instance<15>l1inductive learning<15>k1de finetti theorem<18>j7logic and computation<17>i5computational effect<06>heff
<EFBFBD>ghandler<0C>fconductor	<09>emagnet
<0A>d!relativity<14>c/multiple matching<11>b)square pattern<06>atom<07>`trie<06>_dak<06>^dsl<1A>];interactive application<15>\1time-varying value<17>[5reactive programming<16>Z3multidirectionality
<0A>Y!modularity<12>X+lazy evaluation<11>W)order function<16>V3functional language<18>U7higher-order function<08>Teeect<07>Sglue<19>R9network virtualization<12>Q+virtual network<06>Pisp<0F>O%ossification<06>Njse
<0A>M!own action<07>Ldyad<0B>Kco-actor<0F>J%joint action<0E>I#side-effect<0B>Hreactive<13>G-observer pattern"<22>FKsoftware engineering principles<06>Epar<0B>Ddowntime<0B>Cpre-copy<07>Bqemu	<09>Avmware<14>@/cleanup operation<10>?'pop operation
<0A>>!starvation<08>=stack<17><5potential antecedent<16>;3employee engagement<08>:facet<12>9+dominant thread
<EFBFBD>8locking<0E>7#shared data<0F>6%non-dominant<07>5safe<1B>4=dimensionality reduction<07>3nnza<11>2)linear algebra<0B>1sparsity	<09>0sparse<15>/1personal computing
<EFBFBD>.sixties<12>-+object-oriented<0B>,thinking<15>+1computing hardware<14>*/single individual<14>)/general principle<13>(-design principle<06>'snr<08>&stant<15>%1source and channel<06>$bms	<09>#reduct<06>"tmi	<09>!quorum<12> +sequence number<06>ues
<EFBFBD>popular<07>ebay	<09>agenda
<0A>!widespread<07>sink<14>/byzantine failure	<09>tarzan<0E>#low-latency<08>onion<06>tor
<EFBFBD>censors
<EFBFBD>secrecy<0C>initiator<1A>;anonymous communication<07>undp<0B>un women<0B>violence
<EFBFBD>
conduct<08>unfpa<0F>%node failure<08>
cover<14>	/locality property<14>/different cluster<16>3considerable amount<15>1global information<0C>disruptor
<0A>!ciphertext<18>7malicious participant<19>9senders and recipients<12>
+cloud computing<11>)legacy systems
<0A>!provenance<18>~7mobile ad-hoc network<0B>}forensic<06>|cop
<0A>{!data model<08>zmovie
<0A>y!graph data<08>xessay<0B>weducator<16>v3area of mathematics
<EFBFBD>upoincar<10>t'mathematician<12>s+paxos algorithm<0C>rinvariant<06>qmpi<14>p/cluster computing<0B>omultiple<16>n3resource allocation<06>mpig<1E>lCimplementation of mapreduce<08>kssion<08>jmapre
<0A>i!repository<0B>hindexing
<0A>g!percolator<15>f1consensus protocol<16>e3consensus algorithm<14>d/understandability<12>c+general pattern<1A>b;large-scale application<19>a9global serializability	<09>`border	<09>_kelips	<09>^pastry	<09>]lookup"<22>\Ksynchronous distributed systems<1F>[Econsensus in an asynchronous<07>Zrati<12>Y+correct process<11>X)crash-recovery<06>Wtla	<09>Vclique<06>Ucut<12>T+message logging<07>Sfifo<11>R)chandy-lamport<06>Qgpe<07>Pprob<16>O3fundamental concept<0C>Npredicate<0F>M%global state
<0A>L!checkpoint<0E>K#local state<0E>J#hypersphere<0E>I#binary code
<0A>H!hyperplane<11>G)hashing method<13>F-traffic analysis	<09>Edc-net<0C>Dherbivore
<EFBFBD>Cdissent<12>B+storage service<15>A1strong consistency<14>@/chain replication<12>?+high throughput<0C>>data loss<0B>=ramcloud<14></partial synchrony<14>;/synchronous model<16>:3synchronous systems<0B>9sumption<0E>8#certificate	<09>7atomic<0F>6%registration<10>5'crash failure<1B>4=asynchronous environment<17>35replication protocol<1A>2;transactions per second<06>1dns
<EFBFBD>0beehive<12>/+traffic changes<14>./intermediate node<11>-)optimal scheme<06>,vlb<1A>+;combinatorial algorithm<10>*'impossibility<14>)/different results<1A>(;communication subsystem

ii<00><13>7<00><02>u5GGA Universal Modular ACTOR Formalism for Artificial Intelligence<07>This paper proposes a modular ACTOR architecture and definitional method for artificial intelligence that is conceptually based on a single kind of object: actors [or, if you will, virtual processors, activation frames, or streams]. The formalism makes no presuppositions about the representation of primitive data structures and control structures. Such structures can be programmed, micro-coded, or hard wired 1n a uniform modular fashion. In fact it is impossible to determine whether a given object is "really" represented as a list, a vector, a hash table, a function, or a process. The architecture will efficiently run the coming generation of PLANNER-like artificial intelligence languages including those requiring a high degree of parallelism. The efficiency is gained without loss of programming generality because it only makes certain actors more efficient; it does not change their behavioral characteristics. The architecture is general with respect to control structure and does not have or need goto, interrupt, or semaphore primitives. The formalism achieves the goals that the disallowed constructs are intended to achieve by other more structured methods. PLANNER Progress "Programs should not only work, but they should appear to work as well." PDP-1X Dogma The PLANNER project is continuing research in natural and effective means for embedding knowledge in procedures. In the course of this work we have succeeded in unifying the formalism around one fundamental concept: the ACTOR. Intuitively, an ACTOR is an active agent which plays a role on cue according to a script" we" use the ACTOR metaphor to emphasize the inseparability of control and data flow in our model. data bases can all be shown to be special cases of actors. All of the above are objects with certain useful modes of behavior. Our formalism shows how all of the modes of behavior can be defined in terms of one kind of behavior: sending messages to actors. An actor is always invoked uniformly in exactly the same way regardless of whether 1t behaves as a recursive function, data structure, or process. "It is vain to multiply Entities beyond need." William of Occam "Monotheism is the Answer." The unification and simplification of the formalisms for the procedural embedding of knowledge has a great many benefits for us: FOUNDATIONS: The concept puts procedural semantics [the theory of how things operate] on a firmer basis. It will now be possib
}<02>_5GGA Hundred Impossibility Proofs for Distributed Computing<07>1 Introduction This talk is about impossibility results in the area of distributed computing. In this category, I include not just results that, say that a particular task cannot be accomplished, but also lower bound results, which say that a task cannot be accomplished within a certain bound on cost. I started out with a simple plan for preparing this talk: I would spend a couple of weeks reading all the impossibility proofs in our field, and would categs rize them according to the ideas used. Then I would make wise and general observations, and try to predict where the future of this area is headed. That turned out to be a bit too ambitious; there are many more such results than I thought. Although it is often hard to say what constitutes a " different result " , I managed to count over 100 such impossibility proofs! And my search wasn't even very systematic or exhaustive. It's not quite as hopeless to understand this area as it might seem from the number of papers. Although there are 100 different results, there aren't 100 different ideas. I thought I could contribute something by identifying some of the commonality among the different results. So what I will do in this talk will be an incomplete version of what I originally intended. I will give you Permission to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage, the ACM copyright notice and the title of the publication and its date appear, and notice is given that copying is by permission of the Association for Computing Machinery. To copy otherwise, or to republish, requires a fee and/or specific permission. a tour of the impossibility results that I was able to collect. I apologize for not being comprehensive, and in particular for placing perhaps undue emphasis on results I have been involved in (but those are the ones I know best!). I will describe the techniques used, as well as giving some historical perspective. I'll intersperse this with my opinions and observations, and I'll try to collect what I consider to be the most important of these at the end. Then I'll make some suggestions for future work. 2 The Results I classified the impossibility results I found into the following categories: shared memory resource allocation , distributed consensus, …PODCdistributed_systems/2017-09-11T23:06:58.9393249512017-09-11T23:06:58.939324951

%%<00>W<EFBFBD>9<00>C<02>!<21>E5AAA Versatile Scheme for Routing Highly Variable Traffic in Service Overlays and IP Backbones<07>— The emergence of new applications on the Internet like voice-over-IP, peer-to-peer, and video-on-demand has created highly dynamic and changing traffic patterns. In order to route such traffic with Quality-of-Service (QoS) guarantees without requiring detection of traffic changes in real-time or reconfiguring the network in response to it, a routing and bandwidth allocation scheme has been recently proposed [9], [20] that a
]<5D>5CCfc11031895c302dc52404d34de58af1a72f3b817zab-high-performance-broadcast-for-primary-backup-systems.pdfdistributed_systems/zab high performance broadcast for primary backup systems2017-09-11T23:06:09.23040212017-09-11T23:06:09.2304021<EFBFBD>wf]<5D>	5<>
EE66401c00817c71713e86438385d91956246aeaabviewing-control-structures-as-patterns-of-passing-messages.pdfdistributed_systems/viewing control structures as patterns of passing messages2017-09-11T23:06:09.042117922017-09-11T23:06:09.04211792	<09>R]<5D>+5<>#GG07f82eecbe3d530e3f967342245a4d5c8e41c05bunderstanding-the-limitation<6F>e]<5D>+5<>#GG
g07f82eecbe3d530e3f967342245a4d5c8e41c05bunderstanding-the-limitations-of-causally-and-totally-ordered-communication.pdfdistributed_systems/understanding the limitations of causally and totally ordered communication2017-09-11T23:06:09.0381879882017-09-11T23:06:09.038187988<EFBFBD>Wd	]g5_GG
d530b50510808903545d298de7e19d6e5463a72cdtowards-a-cloud-computing-research-agenda.pdfdistributed_systems/towards a cloud computing research agenda2017-09-11T23:06:09.0309431152017-09-11T23:06:09.030943115<EFBFBD>t\
]<5D>5{GG
cca9ccbcf4a8440590a81f94295a22386a422d198solution-of-a-problem-in-concurrent-programming-control.pdfdistributed_systems/solution of a problem in concurrent programming control2017-09-11T23:06:08.8842041022017-09-11T23:06:08.884204102<EFBFBD>Qc	]a5YGG
bf3485e24d796c33f11048f74e447853ef4a6dc53tor-the-second-generation-onion-router.pdfdistributed_systems/tor the second generation onion router2017-09-11T23:06:09.0235148932017-09-11T23:06:09.023514893<EFBFBD>%b]<5D>35<33>+GG
`87a6e1ec4dd1df928541467296e4cf2a0f2df0c3tiered-replication-a-cost-effective-alternative-to-full-cluster-geo-replication.pdfdistributed_systems/tiered replication a cost effective alternative to full cluster geo replication2017-09-11T23:06:09.0145668952017-09-11T23:06:09.014566895<EFBFBD>']	]75/GG
_d14dee375bc275d08b09e5b7d420c28a5ef6b47asparse-partitions.pdfdistributed_systems/sparse partitions2017-09-11T23:06:08.8992910162017-09-11T23:06:08.899291016<EFBFBD>Ga	]W5OGG
^bac41b59697da3ca5c80ca08f2bbbc97a3576248the-dining-cryptographers-problem.pdfdistributed_systems/the dining cryptographers problem2017-09-11T23:06:09.0049179692017-09-11T23:06:09.004917969<EFBFBD>)_	]951GG
]e1ac8e8d810a148dc3f5291795b0ac0b114db824the-akamai-network.pdfdistributed_systems/the akamai network2017-09-11T23:06:08.9177910162017-09-11T23:06:08.917791016@]75/GGd14dee375bc275d08b09e5b7d420c28a5ef6b47asparse-partitions.pdfdistributed_systems/sparse partitions2017-09-11T23:06:08.8992910162017-09-11T23:06:08.899291016<EFBFBD>r\
]<5D>5{GGca9ccbcf4a8440590a81f94295a22386a422d198solution-of-a-problem-in-concurrent-programming-control.pdfdistributed_systems/solution of a problem in concurrent programming control2017-09-11T23:06:08.8842041022017-09-11T23:06:08.884204102<02>]w5oGG5eb4500b8053ac8dd1a21bfca10c818e1e0a2405simple-testing-can-prevent-most-critical-failures.pdfdistributed_systems/simple testing can prevent most critic<69>yf]<5D>	5<>
EE
i66401c00817c71713e86438385d91956246aeaabviewing-control-structures-as-patterns-of-passing-messages.pdfdistributed_systems/viewing control structures as patterns of passing messages2017-09-11T23:06:09.042117922017-09-11T23:06:09.04211792<EFBFBD>tg
]<5D>5CC
ffc11031895c302dc52404d34de58af1a72f3b817zab-high-performance-broadcast-for-primary-backup-systems.pdfdistributed_systems/zab high performance broadcast for primary backup systems2017-09-11T23:06:09.23040212017-09-11T23:06:09.2304021<EFBFBD>`
]<5D>5<>GGx993f5b0bb126caae848937b2323efabdf8bc21e9the-chubby-lock-service-for-loosely-coupled-distributed-systems.pdfdistributed_systems/the chubby lock service for loosely coupled distributed systems2017-09-11T23:06:08.9290371092017-09-11T23:06:08.929037109<EFBFBD>x^
]<5D>5GG
\64832c7b1602f0922e4e818ad045d1bb5ae95dd6stronger-semantics-for-low-latency-geo-replicated-storage.pdfdistributed_systems/stronger semantics for low latency geo replicated storage2017-09-11T23:06:08.9104189452017-09-11T23:06:08.910418945
Zj
tkZ<00>
<0A>=y<02>M<EFBFBD>E5GGA Byzantine Fault Tolerant Distributed Commit Protocol<07>In this paper, we present a Byzantine fault tolerant distributed commit protocol for transactions running over un- trusted networks. The traditional two-phase commit protocol is enhanced by replicating the coordinator and by running a Byzantine agreement algorithm among the coordinator replicas. Our protocol can tolerate Byzantine faults at the coordinator replicas and a subset of malicious faults at the participants. A decision certificate, which includes a set of registration records and a set of votes from participants, is used to facilitate the coordinator replicas to reach a Byzantine agreement on the outcome of each transaction. The certificate also limits the ways a faulty replica can use towards non-atomic termination of transactions, or semantically incorrect transaction outcomes.Third IEEE International Symposium on Dependable, Autonomic and Secure Computing (DASC 2007)distributed_systems/2017-09-11T23:06:59.3901909182017-09-11T23:06:59.390190918<EFBFBD><05><
C<02>!5GGByzantine Chain Replication<07>We present a new class of Byzantine-tolerant State Machine Replication protocols for asynchronous environments that we term Byzan-tine Chain Replication. We demonstrate two implementations that present different trade-offs between performance and security, and compare these with related work. Leveraging an external reconfiguration service, these protocols are not based on Byzantine consensus, do not require majority-based quorums during normal operation, and the set of replicas is easy to reconfigure. One of the implementations is instantiated with t + 1 replicas to tolerate t failures and is useful in situations where perimeter security makes malicious attacks unlikely. Applied to in-memory BerkeleyDB replication, it supports 20,000 transactions per second while a fully Byzantine implementation supports 12,000 transactions per second—about 70% of the throughput of a non-replicated database.OPODISdistributed_systems/2017-09-11T23:06:59.2368291022017-09-11T23:06:59.236829102<EFBFBD>r<EFBFBD>;
5<02>
5GGBouvier's Conjecture<07>This paper deals with Bouvier's conjecture which sustains that finite-dimensional non-Noetherian Krull domains need not be Jaf-fard.distributed_systems/2017-09-11T23:06:59.1806889652017-09-11T23:06:59.180688965<EFBFBD><12>:<00>C<02>=5GGBeehive: O(1) Lookup Performance for Power-Law Query Distributions in Peer-to-Peer Overlays<07>Structured peer-to-peer hash tables provide decentralization , self-organization, failure-resilience, and good worst-case lookup performance for applications, but suffer from high latencies (O(logN)) in the average case. Such high latencies prohibit them from being used in many relevant, demanding applications such as DNS. In this paper, we present a proactive replication framework that can provide constant lookup performance for common Zipf-like query distributions. This framework is based around a closed-form optimal solution that achieves O(1) lookup performance with low storage requirements , bandwidth overhead and network load. Simulations show that this replication framework can realistically achieve good latencies, outperform passive caching, and adapt efficiently to sudden changes in object popularity, also known as flash crowds. This framework provides a feasible substrate for high-performance, low-latency applications, such as peer-to-peer domain name service.NSDIdistributed_systems/2017-09-11T23:06:59.1172128912017-09-11T23:06:59.117212891
I
|I<00>/<2F>?
i<02>O5GGConsensus in the presence of partial synchrony<07>The concept of partial synchrony in a distributed system is introduced. Partial synchrony lies between the cases of a synchronous system and an asynchronous system. In a synchronous system, there is a known fixed upper bound &#916; on the time required for a message to be sent from one processor to another and a known fixed upper bound &PHgr; on the relative speeds of different processors. In an asynchronous system no fixed upper bounds &#916; and &PHgr; exist. In one version of partial synchrony, fixed bounds &#916; and &PHgr; exist, but they are not known a priori. The problem is to design protocols that work correctly in the partially synchronous system regardless of the actual values of the bounds &#916; and &PHgr;. In another version of partial synchrony, the bounds are known, but are only guaranteed to hold starting at some unknown time <italic>T</italic>, and protocols must be designed to work correctly regardless of when time <italic>T</italic> occurs. Fault-tolerant consensus protocols are given for various cases of partial synchrony and various fault models. Lower bounds that show in most cases that our protocols are optimal with respect to the number of faults tolerated are also given. Our consensus protocols for partially synchronous processors use new protocols for fault-tolerant &#8220;distributed clocks&#8221; that allow partially synchronous processors to reach some approximately common notion of time.J. ACMdistributed_systems/2017-09-11T23:06:59.8035629882017-09-11T23:06:59.803562988<EFBFBD><00>>
{<02>k
5GGCommodifying Replicated State Machines with OpenReplica<07>This paper describes OpenReplica, an open service that provides replication and synchronization support for large-scale distributed systems. OpenReplica is designed to commodify Paxos replicated state machines by providing infrastructure for their construction, deployment and maintenance. OpenReplica is based on a novel Paxos replicated state machine implementation that employs an object-oriented approach in which the system actively creates and maintains live replicas for user-provided objects. Clients access these replicated objects transparently as if they are local objects. OpenReplica supports complex distributed synchronization constructs through a multi-return mechanism that enables the replicated objects to control the execution flow of their clients, in essence providing blocking and non-blocking method in-vocations that can be used to implement richer synchronization constructs. Further, it supports elasticity requirements of cloud deployments by enabling any number of servers to be replaced dynamically. A rack-aware placement manager places replicas on nodes that are unlikely to fail together. Experiments with the system show that the latencies associated with replication are comparable to ZooKeeper, and that the system scales well.distributed_systems/2017-09-11T23:06:59.5356870122017-09-11T23:06:59.535687012
<00>
<EFBFBD><03><00><00>J<EFBFBD>B<00><02>a5GGChain Replication for Supporting High Throughput and Availability<07>Chain replication is a new approach to coordinating clusters of fail-stop storage servers. The approach is intended for supporting large-scale storage services that exhibit high throughput and availability without sacrificing strong consistency guarantees. Besides outlining the chain replication protocols themselves , simulation experiments explore the performance characteristics of a prototype implementation. Throughput, availability, and several object-placement strategies (including schemes based on distributed hash table routing) are discussed.OSDIdistributed_systems/2017-09-11T23:07:00.1262971192017-09-11T23:07:00.126297119<EFBFBD>r<EFBFBD>A<00>
<02>;
5GGDapper, a Large-Scale Distributed Systems Tracing Infrastructure<07>Modern Internet services are often implemented as complex , large-scale distributed systems. These applications are constructed from collections of software modules that may be developed by different teams, perhaps in different programming languages, and could span many thousands of machines across multiple physical facilities. Tools that aid in understanding system behavior and reasoning about performance issues are invaluable in such an environment. Here we introduce the design of Dapper, Google's production distributed systems tracing infrastructure, and describe how our design goals of low overhead, application-level transparency, and ubiquitous deployment on a very large scale system were met. Dapper shares conceptual similarities with other tracing systems, particularly Magpie [3] and X-Trace [12], but certain design choices were made that have been key to its success in our environment, such as the use of sampling and restricting the instrumentation to a rather small number of common libraries. The main goal of this paper is to report on our experience building, deploying and using the system for over two years, since Dapper's foremost measure of success has been its usefulness to developer and operations teams. Dapper began as a self-contained tracing tool but evolved into a monitoring platform which has enabled the creation of many different tools, some of which were not anticipated by its designers. We describe a few of the analysis tools that have been built using Dapper, share statistics about its usage within Google, present some example use cases, and discuss lessons learned so far.distributed_systems/2017-09-11T23:06:59.9710139162017-09-11T23:06:59.971013916<EFBFBD>z<EFBFBD>@<00>	<02>Q5GGCopysets: Reducing the Frequency of Data Loss in Cloud Storage<07>Random replication is widely used in data center storage systems to prevent data loss. However, random replica-tion is almost guaranteed to lose data in the common scenario of simultaneous node failures due to cluster-wide power outages. Due to the high fixed cost of each incident of data loss, many data center operators prefer to minimize the frequency of such events at the expense of losing more data in each event. We present Copyset Replication, a novel general-purpose replication technique that significantly reduces the frequency of data loss events. We implemented and evaluated Copyset Replication on two open source data center storage systems, HDFS and RAMCloud, and show it incurs a low overhead on all operations. Such systems require that each node's data be scattered across several nodes for parallel data recovery and access. Copyset Replication presents a near optimal trade-off between the number of nodes on which the data is scattered and the probability of data loss. For example, in a 5000-node RAMCloud cluster under a power outage, Copyset Replication reduces the probability of data loss from 99.99% to 0.15%. For Facebook's HDFS cluster, it reduces the probability from 22.8% to 0.78%.USENIX Annual Technical Conferencedistributed_systems/2017-09-11T23:06:59.8829719242017-09-11T23:06:59.882971924

:<02>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
u
j
_
T
I
>
3
(


	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	x	m	b	W	L	A	6	+	 		
<08><08><08><08><08><08><08><08><08><08><08><08>{peZOD9.#
<07><07><07><07><07><07><07><07><07><07><07>~sh]RG<1&<06><06><06><06><06><06><06><06><06><06><06><06>vk`UJ?4)<05><05><05><05><05><05><05><05><05><05><05><05>yncXMB7,!<04><04><04><04><04><04><04><04><04><04><04>|qf[PE:/$<03><03><03><03><03><03><03><03><03><03><03>ti^SH=2'<02><02><02><02><02><02><02><02><02><02><02><02><08> <04>
p<08><04>
p<08><04>
p<08><04>
p<08><04>
p<08><04>
p<08><04>
p<08>
p<08>~
p<08>}
p<08>|
p<08>{
p<08>z
p<08>y
p<08>x
p<08>w
p<08>v
p<08>u
p<08>t
p<08>
s
p<08>r
p<08>q
p<08>
p
p<08>	o
p<08>n
p<08>m
p<08>l
p<08>k
p<08>j
p<08>i
p<08>h
p<08>
g
p<08>f
p<08>e
p<08>~d
p<08>}c
p<08>|b
p<08>{a
p<08>z`
p<08>y_
p<08>x^
p<08>w]
p<08>v\
p<08>u[
p<08>tZ
p<08>sY
p<08>rX
p<08>qW
p<08>pV
p<08>oU
p<08>nT
p<08>mS
p<08>lR
p<08>kQ
p<08>jP
p<08>iO
p<08>hN
p<08>gM
p<08>fL
p<08>eK
p<08>dJ
p<08>cI
p<08>bH
p<08>aG
p<08>`F
p<08>_E
p<08>^D
p<08>]C
p<08>\B
p<08>[A
p<08>Z@
p<08>Y?
p<08>X>
p<08>W=
p<08>V<
p<08>U;
p<08>T:
p<08>S9
p<08>R8
p<08>Q7
p<08>P6
p<08>O5
p<08>N4
p<08>M3
p<08>L2
p<08>K1
p<08>J0
p<08>I/
p<08>H.
p<08>G-
p<08>F,
p<08>E+
p<08>D*
p<08>C)
p<08>B(
p<08>A'
p<08>@&
p<08>?%
p<08>>$
p<08>=#
p<08><"
p<08>;!
p<08>: 
p<08>9
p<08>8
p<08>7
p<08>6
p<08>5
p<08>4
p<08>3
p<08>2
p<08>1
p<08>0
p<08>/
p<08>.
p<08>-
p<08>,
p<08>+
p<08>*
p<08>)
p<08>(
p<08>'

p<08>&
p<08>%
p<08>$

p<08>#	
p<08>"
p<08>!
p<08> 
p<08>
p<08>
p<08>
p<08>
p<08>

p<08>
p<08><03>
p<08><03>
p<08><03>
p<08><03>
p<08><03>
p<08><03>
p<08><03>
p<08><03>
p<08><03>
p<08><03>
p<08><03>
p<08><03>
p<08>
<03>
p<08><03>
p<08><03>
p<08>
<03>
p<08>	<03>
p<08><03>
p<08><03>
p<08><03>
p<08><03>
p<08><03>
p<08><03>
p<08><03>
p<08>
<03>
p<08><03>
p<08><03>
p<08>~<03>
p<08>}<03>
p<08>|<03>
p<08>{<03>
p<08>z<03>
p<08>y<03>
p<08>x<03>
p<08>w<03>
p<08>v<03>
p<08>u<03>
p<08>t<03>
p<08>s<03>
p<08>r<03>
p<08>q<03>
p<08>p<03>
p<08>o<03>
p<08>n<03>
p<08>m<03>
p<08>l<03>
p<08>k<03>
p<08>j<03>
p<08>i<03>
p<08>h<03>
p<08>g<03>
p<08>f<03>
p<08>e<03>
p<08>d<03>
o<08>c<03>
n<08>b<03>
n<08>a<00>
m<08>`<03>
k<08>_<03>
j<08>^<03>
j<08>]<03>
j<08>\<03>
j<08>[<03>
j<08>Z<03>
j<08>Yd
i<08>X<03>
h<08>W<03>
h<08>V<03>
f<08>U<03>
f<08>T<03>
f<08>S
/
e<08>R<03>
e<08>Q<03>
e<08>P<03>
e<08>O
<01>
d<08>N<03>
d<08>M
<01>
d<08>L<03>
c<08>K<03>
b<08>J<03>
b<08>I<03>
b<08>H<03>
a<08>G<03>
a<08>F<03>
a<08>E<03>
a<08>D<03>
a<08>C<03>
a<08>B
	
`<08>Ax
`<08>@v
`<08>?

`<08>>s
`<08>=<03>
_<08><<03>
_<08>;<03>
^<08>:<03>
^<08>9<03>
]<08>8<03>
]<08>7<03>
]<08>6<03>
]<08>5<03>
]<08>4<03>
]<08>3<00>
\<08>2<00>
\<08>1<00>
\<08>0<00>
\<08>/<03>
[<08>.<03>
[<08>-<03>
[<08>,<03>
Z<08>+<03>
Y<08>*<03>
X<08>)<03>
X<08>(<00>
W<08>'<03>
V<08>&<03>
V<08>%<03>
U<08>$
<01>
U<08>#
9
T<08>"
<01>
T<08>!
4
T<08> 
3
T<08><03>
T<08>
:
T<08>
<
T<08><03>
T<08>-
S<08>,
S<08>
&
R<08>j
R<08>i
R<08>h
R<08><03>
Q<08><03>
Q<08>w
P<08><03>
P<08><00>
O<08><03>
N<08>
<01>
M<08>
<01>
M<08>
<03>
M<08>
<01>
M<08>
<01>
M<08>
<03>
L<08>	g
L<08><03>
L<08><03>
K<08><03>
K<08><03>
K<08><00>
I<08><03>
I<08><03>
H<08>
<00>
H<08>
	
G<08><03>
G<08>~<03>
G<08>}<03>
G<08>|<00>
F<08>{<03>
F<08>z<03>
E<08>y<03>
E<08>x<03>
D<08>w<03>
D<08>v<03>
D<08>u<03>
D<08>t<03>
D<08>s<03>
C<08>r<03>
C<08>q<03>
C<08>p
	
C<08>o
V
B<08>n
<01>
B<08>m<03>
A<08>l
A<08>k~
A<08>j}
A<08>i|
A<08>h{
A<08>gz
A

;B<00><07><05><0E><02>f<0E>Y.<
<0A><00>
<0A>
"<03>@<04>
S
+g:<02>
<0C>|2
<07><0B>
<01><0B>j
<01>
R<05><04>
<EFBFBD>
<EFBFBD><02>
sg<06>
>
	<09>	<09>	Rl	DP<08><03>
<01><04>@j<08><06>B<08>eS1eSymbolic Representation and Natural Language
O<04>The Quest for Artificial Intelligence a History of Ideas and Achievements
"	Reverend Bayes on -]Toward a cloud computing research agenda
d,[Tor: The Second-Generation Onion Router
bK<04>Why Do Some Men Use Violence Against Women and How Can We Prevent It?
aV<04>-Tiered Replication: A Cost-effective Alternative to Full Cluster Geo-replication
`C<04>Warp: Lightweight Multi-Key Transactions for Key-Value Stores
05mTransactional storage for geo-replicated systems
/?The LCA Problem Revisited
 8sThe phase transition in inhomogeneous random graphs
 Systematic Review in SoftwarB<04>ZooKeeper: Wait-free Coordination for Internet-scale Systems
eA<04>The Space Complexity of Approximating the Frequency Moments
<{Weighted Finite-state Transducers in Speech Recognition<00><07>
The BUDS Language for Dis!EThe Solovay-Kitaev algorithm
<01>"GWarnings for pattern matching
<01>0cThe extensible neuroimaging archive toolkit
<01>'QWhy Functional Programming Matters
<01>1eTowards Equal Rights for Higher-kinded Types
<01>!EThe UNIX Time-Sharing System
~+Ykvm: the Linux Virtual Machine Monitor
{%MThe Story of the Therac in LOTOS
z'QThe Meaning of Employee Engagement
xS<04>'Toward a unified theory of sparse dimensionality reduction in Euclidean space
v#IThe Early History of Smalltalk
s'QUEG Week 2016 Poster Presentations
p=}The Pagerank Citation Ranking: Bringing Order to the Web
l@<04>
Viewing Control Structures as Patterns of Passing Messages
iQ<04>#Understanding the Limitations of Causally and Totally Ordered Communication
g@<04>
Zab: High-performance broadcast for primary-backup systems
f&OWhy Silent Updates Boost Security<00>._Uncovering network tarpits with degreaser<00>7qThe Dynamic Window Approach to Collision Avoidance<00>#ITheory in Programming Practice<00>9The Derivative of a Regu*WUnderstanding RFID Counting Protocols
<01>/aThe operating system: should there be one?<00>*WWormholes: introducing effects to FRP<00>+[
f4: Facebook's Warm BLOB Storage SystemM&OXen and the art of virtualization<00>4m
Web page classification: Features and algorithms'4kViewstamped Replication: A General Primary Copy<00>5mVL2: a scalable and flexible data center network<00>1g
VEWS: A Wikipedia Vandal Early Warning SystemK<04>Untraceable Electronic Mail, Return Addresses, and Digital Pseudonyms<00>7s
Unikernels: library operating systems for the cloud~4m
Unicorn: A System for Searching the Social Graph}=Two Tasty Servings of Pi<00>P<04>#
Transactional Client-Server Cache Consistency: Alternatives and Performance.a
Traits: A mechanism for fine-grained reusecX<04>3
Towards a next generation data center architecture: scalability and commoditizationa%MTop 10 algorithms in data mining<00>E<04>

Time, Clocks, and the Ordering of Events in a Distributed System>6q
There is more consensus in Egalitarian parliaments|$KThe Φ Accrual Failure Detector<00>I<04>The treadmill: real-time garbage collection without motion sickness<00>7s
The semantics of x86-CC multiprocessor machine code9[<04>7The scalable commutativity rule: designing scalable software for multicore processors<00>9
The rendering equation('S
The chemical basis of morphogenesis+[
The algorithmization of counterfactuals
C<04>The Slab Allocator: An Object-Caching Kernel Memory Allocator<00>)
The Redox Code*e<04>KThe Peer Sampling Service: Experimental Evaluation of Unstructured Gossip-Based Implementations<00>=
The Part-Time Parliament{=}The PageRank Citation Ranking: Bringing Order to the Web<00>-_
The Moral Character of Cryptographic WorkDE<04>

The Join Calculus: A Language for Distributed Mobile Programmingz-]The Fast Johnson-lindenstrauss Transform<00><00>The Dangers of Replication and a SolutiondD<04>
The Chubby Lock Service for Loosely-Coupled Distributed Systemsx0e
The Case for Determinism in Database SystemsO#The Byzantine Generals Problemy
o<0C>o
y<02>%E5GGEluding carnivores: file sharing with strong anonymity<07>Anonymity is increasingly important for networked applications amidst concerns over censorship and privacy. This paper outlines the design of HerbivoreFS, a scalable and efficient file sharing system that provides strong anonymity. HerbivoreFS provides computational guarantees that even adversaries able to monitor all network traffic cannot deduce the identity of a sender or receiver beyond an anonymizing clique of <i>k</i> peers. HerbivoreFS achieves scalability by partitioning the global network into smaller anonymizing cliques. Measurements on PlanetLab indicate that the system achieves high anonymous bandwidth when deployed on the Internet.ACM SIGOPS European Workshopdistributed_systems/2017-09-11T23:07:00.3397819822017-09-11T23:07:00.339781982

<01>	~<05>
<01><00>U<EFBFBD>G<00><02>u
5EEHerbivore: A Scalable and Efficient Protocol for Anonymous Communication<07>Anonymity is increasingly important for networked applications amidst concerns over censorship and privacy. In this paper, we describe Herbivore, a peer-to-peer, scalable, tamper-resilient communication system that provides provable anonymity and privacy. Building on dining cryptographer networks, Herbivore scales by partitioning the network into anonymizing cliques. Adversaries able to monitor all network traffic cannot deduce the identity of a sender or receiver beyond an anonymiz-ing clique. In addition to strong anonymity, Herbivore simultaneously provides high efficiency and scalability, distinguishing it from other anonymous communication protocols. Performance measurements from a prototype implementation show that the system can achieve high bandwidths and low latencies when deployed over the Internet.distributed_systems/2017-09-11T23:07:00.946742922017-09-11T23:07:00.94674292<EFBFBD>_<EFBFBD>F<00><02>_=5CCDistributed Snapshots: Determining Global States of Distributed Systems<07>This paper presents an algorithm by which a process in a distributed system determines a global state of the system during a computation. Many problems in distributed systems can be cast in terms of the problem of detecting global states. For instance, the global state detection algorithm helps to solve an important class of problems: stable property detection. A stable property is one that persists: once a stable property becomes true it remains true thereafter. Examples of stable properties are &#8220;computation has terminated,&#8221; &#8220; the system is deadlocked&#8221; and &#8220;all tokens in a token ring have disappeared.&#8221; The stable property detection problem is that of devising algorithms to detect a given stable property. Global state detection can also be used for checkpointing.ACM Trans. Comput. Syst.distributed_systems/2017-09-11T23:07:00.85134792017-09-11T23:07:00.8513479<EFBFBD>~<7E>E<00>5<02>+
5GGConsistent Global States of Distributed Systems: Fundamental Concepts and Mechanisms<07>Reports are available via anonymous FTP from the area ftp.cs.unibo.it:/pub/TR/UBLCS in compressed PostScript format. Abstracts are available from the same host in the directory /pub/TR/ABSTRACTS in plain text format. All local authors can be reached via e-mail at the address last-name@cs.unibo.it. Abstract Many important problems in distributed computing admit solutions that contain a phase where some global property needs to be detected. This subproblem can be seen as an instance of the Global Predicate Evaluation (GPE) problem where the objective is to establish the truth of a Boolean expression whose variables may refer to the global system state. Given the uncertainties in asynchronous distributed systems that arise from commun
m<02>95GGHigh-Level Specifications: Lessons from Industry<07>We explain the rationale behind the design of the TLA + specification language , and we describe our experience using it and the TLC model checker in industrial applications—including the verification of multiprocessor memory designs at Intel. Based on this experience, we challenge some conventional wisdom about high-level specifications.FMCOdistributed_systems/2017-09-11T23:07:01.2196760252017-09-11T23:07:01.219676025<EFBFBD>H<EFBFBD>H
e<02>;c5GGHarvest, Yield and Scalable Tolerant Systems<07>The cost of reconciling consistency and state management with high availability is highly magnified by the unprecedented scale and robustness requirements of today's Internet applications. We propose two strategies for improving overall availability using simple mechanisms that scale over large applications whose output behavior tolerates graceful degradation. We characterize this degradation in terms of harvest and yield, and map it directly onto engineering mechanisms that enhance availability by improving fault isolation, and in some cases also simplify programming. By collecting examples of related techniques in the literature and illustrating the surprising range of applications that can benefit from these approaches, we hope to motivate a broader research program in this area. Increasingly, infrastructure services comprise not only routing, but also application-level resources such as search engines [15], adaptation proxies [8], and Web caches [20]. These applications must confront the same ¢ ¡ ¤ £ ¦ ¥ operational expectations and exponentially-growing user loads as the routing infrastructure, and consequently are absorbing comparable amounts of hardware and software. The current trend of harnessing commodity-PC clusters for scalability and availability [9] is reflected in the largest web server installations. These sites use tens to hundreds of PC's to deliver 100M or more read-mostly page views per day, primarily using simple replication or relatively small data sets to increase throughput. The scale of these applications is bringing the well-known tradeoff between consistency and availability [4] into very sharp relief. In this paper we propose two general directions for future work in building large-scale robust systems. Our approaches tolerate partial failures by emphasizing simple composition mechanisms that promote fault containment, and by translating possible partial failure modes into engineering mechanisms that provide smoothly-degrading functionality rather than lack of availability of the service as a whole. The approaches were developed in the context of cluster computing, where it is well accepted [22] that one of the major challenges is the nontrivial software engineering required to automate partial-failure handling in order to keep system management tractable. In this discussion, strong consistency means single-copy ACID [13] consistency; by assumption a strongly-consistent system provides the ability to perform updates, otherwise discussing consistency is irrelevant. High availability is assumed to be provided through redundancy, e.g. data replication; data is considered highly available if a given consumer of the data can always reach some replica. Partition-resilience means that the system as whole can survive a partition between data replicas. The CAP …Workshop on Hot Topics in Operating Systemsdistributed_systems/2017-09-11T23:07:01.1612561042017-09-11T23:07:01.161256104

<01>
<0A>
<07>
<01><00>:<3A>M<00>O<02>5GGKelips: Building an Efficient and Stable P2P DHT through Increased Memory and Background Overhead<07>A peer-to-peer (p2p) distributed hash table (DHT) system allows hosts to join and fail silently (or leave), as well as to insert and retrieve files (objects). This paper explores a new point in design space in which increased memory usage and constant background communication overheads are tolerated to reduce file lookup times and increase stability to failures and churn. Our system, called Kelips, uses peer-to-peer gossip to partially repli-cate file index information. In Kelips, (a) under normal conditions, file lookups are resolved with O(1) time and complexity (i.e., independent of system size), and (b) membership changes (e.g., even when a large number of nodes fail) are detected and disseminated to the system quickly. Per-node memory requirements are small in medium-sized systems. When there are failures, lookup success is ensured through query rerouting. Kelips achieves load balancing comparable to existing systems. Locality is supported by using topologically aware gossip mechanisms. Initial results of an ongoing experimental study are also discussed. * System name derived from kelip-kelip, Malay name for the self-synchronizing fireflies that accumulate after dusk on branches of mangrove trees in Selangor, Malaysia [11]. Our system organizes similarly into affinity groups, and nodes in a group " synchronize " loosely to store information for a common set of file indices.IPTPSdistributed_systems/2017-09-11T23:07:01.9106088872017-09-11T23:07:01.910608887<EFBFBD>C<EFBFBD>L<00>	<02>U5GGImpossibility of Distributed Consensus with One Faulty Process<07>The consensus problem involves an asynchronous system of processes, some of which may be unreliable. The problem is for the reliable processes to agree on a binary value. In this paper, it is shown that every protocol for this problem has the possibility of nontermination, even with only one faulty process. By way of contrast, solutions are known for the synchronous case, the &#8220;Byzantine Generals&#8221; problem.J. ACMdistributed_systems/2017-09-11T23:07:01.7364750982017-09-11T23:07:01.736475098<EFBFBD>#<23>K<00>#<02>]75GGImplementing the Omega failure detector in the crash-recovery failure model<07>a r t i c l e i n f o a b s t r a c t Unreliable failure detectors are mechanisms providing information about process failures, that allow to solve several problems in asynchronous systems, e.g., Consensus. A particular failure detector, Omega, provides an eventual leader election functionality. This paper addresses the implementation of Omega in the crash-recovery failure model. We first propose an algorithm assuming that processes are reachable from the correct process that crashes and recovers a minimum number of times. Then, we propose two algorithms which assume only that processes are reachable from some correct process. Besides this, one of the algorithms requires the membership to be known a priori, while the other two do not.J. Comput. Syst. Sci.distributed_systems/2017-09-11T23:07:01.5703930662017-09-11T23:07:01.570393066<EFBFBD>?<3F>J<00>	<02>]
5EEHow the Hidden Hand Shapes the Market for Software Reliability<07>— Since the 18th century, economists have recognized that absent government intervention, market forces determine the pricing and ultimate fate of technologies. Our contention is that the " hidden hand " explains a series of market failures impacting products in the field of software reliability. If reliability solutions are to reach mainstream developers, greater attention must be paid to market economics and drivers.distributed_systems/2017-09-11T23:07:01.362257082017-09-11T23:07:01.36225708
'<0B>
E<02>i'5GGOn the Calculus of Relations<07>Terms and Conditions of Use provides, in part, that unless you have obtained prior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content in the JSTOR archive only for your personal, non-commercial use. Please contact the publisher regarding any further use of this work. Publisher contact information may be obtained at. Each copy of any part of a JSTOR transmission must contain the same copyright notice that appears on the screen or printed page of such transmission. JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org. Association for Symbolic Logic is collaborating with JSTOR to digitize, preserve and extend access to The Journal of Symbolic Logic.J. Symb. Log.distributed_systems/2017-09-11T23:07:02.0030371092017-09-11T23:07:02.003037109
JQJ<00><03>Q<00>3<02>/5GGLarge-scale Incremental Processing Using Distributed Transactions and Notifications<07>Updating an index of the web as documents are crawled requires continuously transforming a large repository of existing documents as new documents arrive. This task is one example of a class of data processing tasks that transform a large repository of data via small, independent mutations. These tasks lie in a gap between the capabilities of existing infrastructure. Databases do not meet the storage or throughput requirements of these tasks: Google's indexing system stores tens of petabytes of data and processes billions of updates per day on thousands of machines. MapReduce and other batch-processing systems cannot process small updates individually as they rely on creating large batches for efficiency. We have built Percolator, a system for incrementally processing updates to a large data set, and deployed it to create the Google web search index. By replacing a batch-based indexing system with an indexing system based on incremental processing using Percolator, we process th
q<02>Q5GGIn Search of an Understandable Consensus Algorithm<07>Raft is a consensus algorithm for managing a replicated log. It produces a result equivalent to (multi-)Paxos, and it is as efficient as Paxos, but its structure is different from Paxos; this makes Raft more understandable than Paxos and also provides a better foundation for building practical systems. In order to enhance understandabil-ity, Raft separates the key elements of consensus, such as leader election, log replication, and safety, and it enforces a stronger degree of coherency to reduce the number of states that must be considered. Results from a user study demonstrate that Raft is easier for students to learn than Paxos. Raft also includes a new mechanism for changing the cluster membership, which uses overlapping majorities to guarantee safety.USENIX Annual Technical Conferencedistributed_systems/2017-09-11T23:07:02.1590539552017-09-11T23:07:02.159053955
3<05>3<00>A<EFBFBD>S
{<02>e5GGMapReduce: Simplified Data Processing on Large Clusters<07>MapReduce is a programming model and an associated implementation for processing and generating large datasets that is amenable to a broad variety of real-world tasks. Users specify the computation in terms of a <i>map</i> and a <i>reduce</i> function, and the underlying runtime system automatically parallelizes the computation across large-scale clusters of machines, handles machine failures, and schedules inter-machine communication to make efficient use of the network and disks. Programmers find the system easy to use: more than ten thousand distinct MapReduce programs have been implemented internally at Google over the past four years, and an average of one hundred thousand MapReduce jobs are executed on Google's clusters every day, processing a total of more than twenty petabytes of data per day.OSDIdistributed_systems/2017-09-11T23:07:02.4215710452017-09-11T23:07:02.421571045<EFBFBD><04>R<00>/<02>wS5GGOblivious Routing of Highly Variable Traffic in Service Overlays and IP Backbones<07>The emergence of new applications on the Internet like voice-over-IP, peer-to-peer, and video-on-demand has created highly dynamic and changing traffic patterns. In order to route such traffic with quality-of-service (QoS) guarantees without requiring detection of traffic changes in real-time or reconfiguring the network in response to it, a routing and bandwidth allocation scheme has been recently proposed that allows preconfiguration of the network such that all traffic patterns permissible within the network's natural ingress-egress capacity constraints can be handled in a capacity efficient manner. The scheme routes traffic in two phases. In the first phase, incoming traffic is sent from the source to a set of intermediate nodes and then, in the second phase, from the intermediate nodes to the final destination. The traffic in the first phase is distributed to the intermediate nodes in predetermined proportions that depend on the intermediate nodes. In this paper, we develop linear programming formulations and a fast combinatorial algorithm for routing under the scheme so as to maximize throughput (or, minimize maximum link utilization). We compare the throughput performance of the scheme with that of the optimal scheme among the class of all schemes that are allowed to even make the routing dependent on the traffic matrix. For our evaluations, we use actual Internet Service Provider topologies collected for the Rocketfuel project. We also bring out the versatility of the scheme in not only handling widely fluctuating traffic but also accommodating applicability to several widely differing networking scenarios, including i) economical Virtual Private Networks (VPNs); ii) supporting indirection in specialized service overlay models like Internet Indirection Infrastructure (i3); iii) adding QoS guarantees to services that require routing through a network-based middlebox; and iv) reducing IP layer transit traffic and handling extreme traffic variability in IP-over-optical networks without dynamic reconfiguration of the optical layer. The two desirable properties of supporting indirection in specialized service overlay models and static optical layer provisioning in IP-over-optical networks are not present in other approaches for routing variable traffic, such as direct source-destination routing along fixed paths.IEEE/ACM Transactions on Networkingdistributed_systems/2017-09-11T23:07:02.3336330572017-09-11T23:07:02.333633057
(
i*<02>(<00>0<EFBFBD>W
/<02>
5GGPaxos Made Simple<07>The Paxos algorithm, when presented in plain English, is very simple.distributed_systems/2017-09-11T23:07:02.8964270022017-09-11T23:07:02.896427002<EFBFBD>J<EFBFBD>V<00>I<02>/
5GGPastry: Scalable, distributed object location and routing for large-scale peer-to-peer systems<07>This paper presents the design and evaluation of Pastry, a scalable, distributed object location and routing scheme for wide-area peer-to-peer applications. Pastry performs application-level routing and object location in a potentially very large overlay network of nodes connected via the Internet. It can be used to support a wide range of peer-to-peer applications like global data storage, global data sharing, and naming. An insert operation in Pastry stores an object at a user-defined number of diverse nodes within the Pastry network. A lookup operation reliably retrieves a copy of the requested object if one exists. Moreover, a lookup is usually routed to the node nearest the client issuing the lookup (by some measure of proximity), among the nodes storing the requested object. Pastry is completely decentralized, scalable, and self-configuring; it automatically adapts to the arrival, departure and failure of nodes. Experimental results obtained with a prototype implementation on a simulated network of up to 100,000 nodes confirm Pastry's scalability, its ability to self-configure and adapt to node failures, and its good network locality properties.distributed_systems/2017-09-11T23:07:02.8448569342017-09-11T23:07:02.844856934<EFBFBD>;<3B>U
G<02>s/5GGPaxos Made Moderately Complex<07>This article explains the full reconfigurable multidecree Paxos (or multi-Paxos) protocol. Paxos is by no means a simple protocol, even though it is based on relatively simple invariants. We provide pseudocode and explain it guided by invariants. We initially avoid optimizations that complicate comprehension. Next we discuss liveness, list various optimizations that make the protocol practical, and present variants of the protocol.ACM Comput. Surv.distributed_systems/2017-09-11T23:07:02.7412739262017-09-11T23:07:02.741273926<EFBFBD><13>T<00><02>i5GGMesos: A Platform for Fine-Grained Resource Sharing in the Data Center<07>Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission. Abstract We present Mesos, a platform for sharing commodity clusters between multiple diverse cluster computing frameworks, such as Hadoop and MPI 1. Sharing improves cluster utilization and avoids per-framework data replication. Mesos shares resources in a fine-grained manner, allowing frameworks to achieve data locality by taking turns reading data stored on each machine. To support the sophisticated schedulers of today's frameworks , Mesos introduces a distributed two-level scheduling mechanism called resource offers. Mesos decides how many resources to offer each framework, while frameworks decide which resources to accept and which computations to run on them. Our experimental results show that Mesos can achieve near-optimal locality when sharing the cluster among diverse frameworks, can scale up to 50,000 nodes, and is resilient to node failures.NSDIdistributed_systems/2017-09-11T23:07:02.4852839362017-09-11T23:07:02.485283936

<08><08>
K<02>w5GGRecent SRI work in verification<07>end has already been implemented as part of an experimental Ada/Ada-M compiler [7] ; work on a syntax-directed editor is i n progress .) However, the methodology of verification-oriented programming is still a research topic. This section provides an update to our last year ' s VERkshop summary [21], summarizing recent work in verification at SRI. I t considers progress as well as current and future plans. As noted in last year's report, the Fortran verification system [1] handles a subset of both ANS I Fortran 66 and 77. The subset excludes the I/O statements, as well as EQUIVALENCE, DATA, and BLOCK DATA statements. Whil e some restrictions are placed on the remaining statements, the subset permits certain uses of COMMON, adjustable array dimensions , functions, and subroutines with side-effects. Unusual features of the system include a syntax checker that enforces all of th e syntactic restrictions, the thorough analysis of aliasing, and the generation of VCs to ensure against run time errors (e .g ., arithmeti c overflow). If a program is proved correct by the system, then any invocation of the program on an ANSI Fortran processor in a stat e satisfying the input assertion terminates without run time errors and produces a state satisfying the output assertion. The main thrust of this year's work with the Fortran system has been to apply it to several small but difficult programs. Some of tha t work is described below. A VCG reduces th e question of whether a program is consistent with its specifications to that of whether certain logical formulas are theorems in a n underlying theory. VCGs must embody the semantics of the programming language ; for the most part, they have been seen asSOENdistributed_systems/2017-09-11T23:07:02.9346269532017-09-11T23:07:02.934626953
<03>?<03><00>?<3F>Z
}<02>Q#5GGSelf-stabilizing Systems in Spite of Distributed Control<07>The synchronization task between loosely coupled cyclic sequential processes (as can be distinguished in, for instance, operating systems) can be viewed as keeping the relation &#8220;the system is in a legitimate state&#8221; invariant. As a result, each individual process step that could possibly cause violation of that relation has to be preceded by a test deciding whether the process in question is allowed to proceed or has to be delayed. The resulting design is readily&#8212;and quite systematically&#8212;implemented if the different processes can be granted mutually exclusive access to a common store in which &#8220;the current system state&#8221; is recorded.Commun. ACMdistributed_systems/2017-09-11T23:07:03.2752739262017-09-11T23:07:03.275273926<EFBFBD>=<3D>Y
U<02>
5GGOn Proof and Progress in Mathematics<07>This essay on the nature of proof and progress in mathematics was stimulated by the article of Jaffe and Quinn, "Theoretical Mathematics: Toward a cultural synthesis of mathematics and theoretical physics". Their article raises interesting issues that mathematicians should pay more attention to, but it also perpetuates some widely held beliefs and attitudes that need to be questioned and examined. The article had one paragraph portraying some of my work in a way that diverges from my experience, and it also diverges from the observations of people in the field whom I've discussed it with as a reality check. After some reflection, it seemed to me that what Jaffe and Quinn wrote was an example of the phenomenon that people see what they are tuned to see. Their portrayal of my work resulted from projecting the sociology of mathematics onto a one-dimensional scale (speculation versus rigor) that ignores many basic phenomena. Responses to the Jaffe-Quinn article have been invited from a number of mathematicians, and I expect it to receive plenty of specific analysis and criticism from others. Therefore, I will concentrate in this essay on the positive rather than on the contranegative. I will describe my view of the process of mathematics, referring only occasionally to Jaffe and Quinn by way of comparison. In attempting to peel back layers of assumptions, it is important to try to begin with the right questions: 1. What is it that mathematicians accomplish? There are many issues buried in this question, which I have tried to phrase in a way that does not presuppose the nature of the answer. It would not be good to start, for example, with the question How do mathematicians prove theorems? This question introduces an interesting topic, but to start with it would be to project two hidden assumptions: (1) that there is uniform, objective and firmly established theory and practice of mathematical proof, and (2) that progress made by mathematicians consists of proving theorems. It is worthwhile to examine these hypotheses, rather than to accept them as obvious and proceed from there.distributed_systems/2017-09-11T23:07:03.0527390142017-09-11T23:07:03.052739014
<00><07><0F><0F><0F><0F><0F><0F><0F><0F>|iP>4)<0E><0E><0E><0E><0E><0E><0E><0E>qbVB6)

<0A>
<0A><08>
<0A>
<0A>
<0A><07>
<0A>
<0A>
<0A>
<0A>
t
h
]
H
3
<08>
<0C><0C><07><0C><0C><07><0C><0C><0C>xpVLB7*<0B><07><0B><0B><0B><0B><0B><08><08><0B><0B>qiRG0<07>	<08>R
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD><08>
<EFBFBD>
<EFBFBD>
o
[
?
3
*
!0

	<09>	<09>	<09>B	<09>	<09>	<09>	<09>h	<09>	s	[	O	7	 		<08><08>%near-optimal)number of tags}/multiple matchingc3multidirectionalityZ!modularityY)order functionW9network virtualizationR%ossificationO!own actionM-observer patternGparE%non-dominant6	nnza3+object-oriented-
onion%node failure7mobile ad-hoc network<03>
movie<03>'path planning<02>pastry<03>	pass%partial view
<01>/partial synchrony<03>1partial evaluation6parity<03>1paravirtualizationm;parametric polymorphism<02>1parallel operationa
panorama<00>
pagerank	pace
#
owsoverlay
<01>#overfitting1!out-of-bag7)others' action<02>otg<02>osd
orykoracle<02>9optimistic replication
4)optimal scheme<03>%optical flow<02>operating<00>
opera<02>
ologn
[odt<00>
octreeseoch
<01>/occurrence typing
occam<02>
ocaml
<01>1obstacle avoidance<02>%object store<03>+number of steps
<01>/number of records<00>
nosql
/non-negative data/non-game contexts
<01>+non-determinism/%non-blocking<00>nfr
A!networking[9network characteristicY5network architecture
9ner<02>
nde/natural extension<02>
naturalnapster<03>
nadph<00>	nadp<00>	nadh<00>7
n.a. n.a. pc analysis
mvstmutatorN?multithreaded applicationd
multiset
<01>3multiple partitions
-multiple devices
~
multiple<03>multicast
Ympi<03>+mozilla firefox<02>/motion trajectory<02>+motion planning<02>+motion dynamics<02>
motifmosaic<00>%morris-prattmop<02>monsoon
8monitor<00>
monad<02>mod
0%mobile robot<02>=mobile phone application
<01>mmuOmixnet
<01>
mixin
G
mixes
<01>#mix network
<01>mission<02>mirage
<01>+
minwise hashingV
minhashWmillwheel
c#millisecond
<01>#microreboot<00>
mhealth'

mexica[
metadata
/messaging systems
Vmessaging
W+
message passing+message logging<03>1message complexity	meso
]
merge
3	ment
<01>%memory model<00>3memory architecture<00>'memory access
s#memoization.	memo<02>!membership
<01>megastore
-7medication compliance
<01>

mediation
mechanic
<01>mdlN	mdcc
/
<00>
R<05><00><00>K<EFBFBD>]
?<02>55GGSecure network provenance<07>This paper introduces <i>secure network provenance (SNP)</i>, a novel technique that enables networked systems to explain to their operators <i>why</i> they are in a certain state -- e.g., why a suspicious routing table entry is present on a certain router, or where a given cache entry originated. SNP provides network forensics capabilities by permitting operators to track down faulty or misbehaving nodes, and to assess the damage such nodes may have caused to the rest of the system. SNP is designed for adversarial settings and is robust to manipulation; its tamper-evident properties ensure that operators can detect when compromised nodes lie or falsely implicate correct nodes.
 We also present the design of SNooPy, a general-purpose SNP system. To demonstrate that SNooPy is practical, we apply it to three example applications: the Quagga BGP daemon, a declarative implementation of Chord, and Hadoop MapReduce. Our results indicate that SNooPy can efficiently explain state in an adversarial setting, that it can be applied with minimal effort, and that its costs are low enough to be practical.SOSPdistributed_systems/2017-09-11T23:07:03.8560590822017-09-11T23:07:03.856059082<EFBFBD>2<EFBFBD>\
<02>C5GGStronger Semantics for Low-Latency Geo-Replicated Storage<07>We present the first scalable, geo-replicated storage system that guarantees low latency, offers a rich data model, and provides " stronger " semantics. Namely, all client requests are satisfied in the local datacenter in which they arise; the system efficiently supports useful data model abstractions such as column families and counter columns; and clients can access data in a causally-consistent fashion with read-only and write-only transac-tional support, even for keys spread across many servers. The primary contributions of this work are enabling scalable causal consistency for the complex column-family data model, as well as novel, non-blocking algorithms for both read-only and write-only transactions. Our evaluation shows that our system, Eiger, achieves low latency (single-ms), has throughput competitive with eventually-consistent and non-transactional Cassandra (less than 7% overhead for one of Facebook's real-world workloads), and scales out to large clusters almost linearly (averaging 96% increases up to 128 server clusters).NSDIdistributed_systems/2017-09-11T23:07:03.6402839362017-09-11T23:07:03.640283936<EFBFBD>*<2A>[
{<02>uW5GGSignal/Collect: Graph Algorithms for the (Semantic) Web<07>The Semantic Web graph is growing at an incredible pace, enabling opportunities to discover new knowledge by interlinking and analyzing previously unconnected data sets. This confronts researchers with a conundrum: Whilst the data is available the programming models that facilitate scalability and the infrastructure to run various algorithms on the graph are missing. Some use MapReduce – a good solution for many problems. However, even some simple iterative graph algorithms do not map nicely to that programming model requiring programmers to shoehorn their problem to the MapReduce model. This paper presents the Signal/Collect programming model for synchronous and asynchronous graph algorithms. We demonstrate that this abstraction can capture the essence of many algorithms on graphs in a concise and elegant way by giving Signal/Collect adaptations of various relevant algorithms. Furthermore, we built and evaluated a prototype Signal/Collect framework that executes algorithms in our programming model. We empirically show that this prototype transparently scales and that guiding computations by scoring as well as asyn-chronicity can greatly improve the convergence of some example algorithms. We released the framework under the Apache License 2.0 (atInternational Semantic Web Conferencedistributed_systems/2017-09-11T23:07:03.4233620612017-09-11T23:07:03.423362061

<0A><0B><00><16>`<00>-<02>Q5GGTiered Replication: A Cost-effective Alternative to Full Cluster Geo-replication<07>Cloud storage systems typically use three-way random replication to guard against data loss within the cluster, and utilize cluster geo-replication to protect against correlated failures. This paper presents a much lower cost alternative to full cluster geo-replication. We demonstrate that in practical settings, using two replicas is sufficient for protecting against independent node failures, while using three random replicas is inadequate for protecting against correlated node failures. We present Tiered Replication, a replication scheme that splits the cluster into a primary and backup tier. The first two replicas are stored on the primary tier and are used to recover data in the case of independent node failures , while the third replica is stored on the backup tier and is used to protect against correlated failures. The key insight of our paper is that, since the third replicas are rarely read, we can place the backup tier on separate physical infrastructure or a remote location without affecting performance. This separation significantly increases the resilience of the storage system to correlated failures and presents a low cost alternative to geo-replication of an entire cluster. In addition, the Tiered Replication algorithm optimally minimizes the probability of data loss under correlated failures. Tiered Repli-cation can be executed incrementally for each cluster change, which allows it to supports dynamic environments in which nodes join and leave the cluster, and it facilitates additional data placement constraints required by the storage designer, such as network and rack awareness. We have implemented Tiered Replication on HyperDex, an open-source cloud storage system, and demonstrate that it incurs a small performance overhead. Tiered
/<02>'
5GGSparse Partitions<07>This abstract presents a collection of clustering and decomposition techniques enabling the construction of sparse and locality preserving representations for arbitrary networks. These new clustering techniques have already found several powerful applications in the area of distributed network algorithms. Two of these applications are described in this abstract, namely, routing with polynomial communication-space tradeoo and online tracking of mobile users.distributed_systems/2017-09-11T23:07:04.0328769532017-09-11T23:07:04.032876953<EFBFBD>$<24>^
S<02>[
5GGDining Cryptographers are Practical<07>The dining cryptographers protocol provides information-theoretically secure sender and recipient untraceability. However, the protocol is considered to be impractical because a malicious participant may disrupt the communication. We propose an implementation which provides information-theoretical security for senders and recipients, and in which a disruptor with limited computational capabilites can easily be detected.distributed_systems/2017-09-11T23:07:03.9797360842017-09-11T23:07:03.979736084

SS<00>)<29>a<00><02>
5GGWhy Do Some Men Use Violence Against Women and How Can We Prevent It?<07>The views expressed in this publication are those of the authors and do not necessarily represent those of the United Nations, including UNDP, UNFPA, UN Women, UNV or UN Member States. UNDP partners with people at all levels of society to help build nations that can withstand crisis and drive and sustain the kind of growth that improves the quality of life for everyone. On the ground in 177 countries and territories, we offer a global perspective and local insight to help empower lives and build resilient nations. The United Nations Population Fund (UNFPA) is an international development agency that works with countries to protect and promote the sexual and reproductive health of women, men and young people. The United Nations Entity for Gender Equality and the Empowerment of Women (UN Women) is a global champion for women and girls; UN Women was established to accelerate progress on meeting their rights worldwide. The United Nations Volunteers (UNV) programme, is the UN organization that contributes to peace and development through volunteerism worldwide. Partners for Prevention is a UNDP, UNFPA, UN Women and UNV regional joint programme for gender-based violence prevention in Asia and the Pacific. foreword Violence against women constrains the enjoyment of women's human rights everywhere. We know that it is a manifestation of power and control and a tool to maintain gender inequalities, disrupting the health, survival, safety and freedom of women and their families around the world. We know that to end violence against women and girls, we must ensure their full empowerment, promote and protect their rights, including access to justice and support services, and end the discrimination they face in all aspects of their lives. Changing cultures towards zero tolerance for violence against women, therefore, must be a priority for States, communities and families. Over the past few decades, much has been done in legal and policy reform and the extension of services to support and protect women and their families from domestic and sexual violence, while prevention effo
]<02>;#5GGToward a cloud computing research agenda<07>The 2008 LADIS workshop on Large Scale Distributed Systems brought together leaders from the commercial cloud computing community with researchers working on a variety of topics in distributed computing. The dialog yielded some surprises: some hot research topics seem to be of limited near-term importance to the cloud builders, while some of their practical challenges seem to pose new questions to us as systems researchers. This brief note summarizes our impressions.SIGACT Newsdistributed_systems/2017-09-11T23:07:04.5150849612017-09-11T23:07:04.515084961<EFBFBD><1B>c	{
#5GGComments on a problem in concurrent programming control<07>Commun. ACMdistributed_systems/2017-09-11T23:07:04.4776630862017-09-11T23:07:04.477663086<EFBFBD>d<EFBFBD>b
[<02>!?5GGTor: The Second-Generation Onion Router<07>We present Tor, a circuit-based low-latency anonymous communication service. This second-generation Onion Routing system addresses limitations in the original design. Tor adds perfect forward secrecy, congestion control, directory servers, integrity checking, configurable exit policies, and a practical design for rendezvous points. Tor works on the real-world Internet, requires no special privileges or kernel modifications, requires little synchronization or coordination between nodes, and provides a reasonable trade-off between anonymity, usability, and efficiency. We briefly describe our experiences with an international network of more than a dozen hosts. We close with a list of open problems in anonymous communication. Onion Routing is a distributed overlay network designed to anonymize TCP-based applications like web browsing, secure shell, and instant messaging. Clients choose a path through the network and build a circuit, in which each node (or " onion router " or " OR ") in the path knows its predecessor and successor, but no other nodes in the circuit. Traffic flows down the circuit in fixed-size cells, which are unwrapped by a symmetric key at each node (like the layers of an onion) and relayed downstream. The Onion Routing project published several design and analysis papers [27, 41, 48, 49]. While a wide area Onion Routing network was deployed briefly, the only long-running public implementation was a fragile proof-of-concept that ran on a single machine. Even this simple deployment processed connections from over sixty thousand distinct IP addresses from all over the world at a rate of about fifty thousand per day. But many critical design and deployment issues were never resolved, and the design has not been updated in several years. Here we describe Tor, a protocol for asynchronous, loosely federated onion routers that provides the following improvements over the old Onion Routing design: Perfect forward secrecy: Onion Routing was originally vulnerable to a single hostile node recording traffic and later compromising successive nodes in the circuit and forcing them to decrypt it. Rather than using a single multiply en-crypted data structure (an onion) to lay each circuit, Tor now uses an incremental or telescoping path-building design , where the initiator negotiates session keys with each successive hop in the circuit. Once these keys are deleted, subsequently compromised nodes cannot decrypt old traffic. As a side benefit, onion replay detection is no longer necessary, and the process of building circuits is more reliable , since the initiator knows when a hop fails …USENIX Security Symposiumdistributed_systems/2017-09-11T23:07:04.3398068852017-09-11T23:07:04.339806885
<00>	<09><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F>|qf[PE:/$<0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E>ti^SH=2'
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
w
m
b
W
L
A
6
+
 

<0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C>{peZOD9.#<0B><0B><0B><0B><0B><0B><0B><0B><0B><0B><0B>ti^SH=2'
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
w
l
a
V
K
@
5
*


		<09>	<09><08>1<04>
<01><08>0<04>
<01><08>/<04>
<01><08>.<04>
<01><08>-<04>
<01><08>,<04>
<01><08>+
<01><08>*~
<01><08>)}
<01><08>(|
<01><08>'{
<01><08>&z
<01><08>%y
<01><08>$x
<01><08>#<00>
<01><08>"w
<01><08>!v
<01><08> u
<01><08><00>
<01><08>t
<01><08>s
<01><08>r
<01><08>q
<01><08>p
<01><08>o
<01><08>n
<01><08>m
<01><08>l
<01><08>k
<01><08>j
<01><08>i
<01><08>h
<01><08><00>
<01><08><02>
<01><08>g
<01><08>f
<01><08>

<01>
<01><08>.
<01><08>e
<01><08>
d
<01><08>	c
<01><08>b
<01><08>a
<01><08><00>
<01><08>`
<01><08>_
<01><08>^
<01><08>H
<01><08>
<00>
<01><08><02>
<01><07>
I
<01><08>~]
<01><08>}\
<01><08>|[
<01><08>{Z
<01><08>zY
<01><08>yX
<01><08>xW
<01><08>wV
<01><08>vU
<01><08>uT
<01><08>t<02>
<01><08>sS
<01><08>rR
<01><08>qQ
<01><08>p[
<01><08>oP
<01><08>nO
<01><08>mN
<01><08>lM
<01><08>kL
<01><08>jK
<01><08>iJ
<01><08>hI
<01><08>gH
<01><08>fG
<01><08>eF
<01><08>dE
<01><08>cp
|<08>b
x
|<08>aD
|<07>`

|<08>_C
|<08>^4
{<08>]B
{<08>\A
{<08>[
<01>
{<08>Z@
y<08>Y?
y<08>X]
y<08>W>
y<08>V=
y<08>U<
x<08>T;
x<08>S:
x<08>R9
w<08>Q8
w<08>P7
w<08>O6
w<08>N5
w<08>M1
v<08>L&
v<08>K4
v<08>J3
v<08>I2
v<08>H1
u<08>G0
u<08>F%
u<08>E
u<08>D"
u<08>C/
s<08>B.
s<08>A-
s<08>@,
s<08>?V
s<08>>+
r<08>=*
r<08><)
r<08>;(
r<08>:'
o<08>9&
o<08>8%
o<08>7$
o<08>6#
o<08>5"
n<08>4<00>
k<08>3
<01>
h<08>2!
f<08>1
<01>
f<08>0

f<08>/
<01>
f<08>. 
f<08>-
<01>
e<08>,

e<08>+
m
e<08>*
e<08>)
e<08>(
d<08>'<00>
d<08>&

d<08>%
d
<00>
E<06>s
o<00><00>"<22>i
<00>

)5GGViewing Control Structures as Patterns of Passing Messages<07>Artif. Intell.distributed_systems/2017-09-11T23:07:05.1111469732017-09-11T23:07:05.111146973<EFBFBD><00>h
m<02>}'GGGamification in educational software development<07>Software development education often suffers from the image of tedious programming, leading to low levels of activity. In general, gamification can help making tasks more attractive. This paper reports on a gamification case study, indicating that the use of gamification may be an effective instrument to increase the activity of students in Educational Software Development.CSERCgamification/2017-09-11T23:07:04.8761240232017-09-11T23:07:04.876124023<EFBFBD>u<EFBFBD>g<00>#<02>+
5GGUnderstanding the Limitations of Causally and Totally Ordered Communication<07>Causally and totally ordered communication support (CATOCS) has been proposed as important to provide as part of the basic building blocks for constructing reliable distributed systems. In this paper, we identify four major limitations to CATOCS, investigate the applicability of CATOCS to several classes of distributed applications in light of these limitations, and the potential impact of these facilities on communication scalability and robustness. From this investigation, we find limited merit and several potential problems in using CATOCS. The fundamental difficulty with the CATOCS is that it attempts to solve state problems at the communication level in violation of the well-known " end-to-end " argument.distributed_systems/2017-09-11T23:07:04.8143110352017-09-11T23:07:04.814311035<EFBFBD>U<EFBFBD>f<00>
<02>e<EFBFBD>35GGZab: High-performance broadcast for primary-backup systems<07>Zab is a crash-recovery atomic broadcast algorithm we designed for the ZooKeeper coordination service. ZooKeeper implements a primary-backup scheme in which a primary process executes clients operations and uses Zab to propagate the corresponding incremental state changes to backup processes<sup>1</sup>. Due the dependence of an incremental state change on the sequence of changes previously generated, Zab must guarantee that if it delivers a given state change, then all other changes it depends upon must be delivered first. Since primaries may crash, Zab must satisfy this requirement despite crashes of primaries.2011 IEEE/IFIP 41st International Conference on Dependable Systems & Networks (DSN)distributed_systems/2017-09-11T23:07:04.7201411132017-09-11T23:07:04.720141113<EFBFBD>7<EFBFBD>e<00><02>	Q5GGZooKeeper: Wait-free Coordination for Internet-scale Systems<07>In this paper, we describe ZooKeeper, a service for coordinating processes of distributed applications. Since ZooKeeper is part of critical infrastructure, ZooKeeper aims to provide a simple and high performance kernel for building more complex coordination primitives at the client. It incorporates elements from group messaging, shared registers, and distributed lock services in a repli-cated, centralized service. The interface exposed by Zoo-Keeper has the wait-free aspects of shared registers with an event-driven mechanism similar to cache invalidations of distributed file systems to provide a simple, yet powerful coordination service. The ZooKeeper interface enables a high-performance service implementation. In addition to the wait-free property, ZooKeeper provides a per client guarantee of FIFO execution of requests and linearizability for all requests that change the ZooKeeper state. These design decisions enable the implementation of a high performance processing pipeline with read requests being satisfied by local servers. We show for the target workloads, 2:1 to 100:1 read to write ratio, that ZooKeeper can handle tens to hundreds of thousands of transactions per second. This performance allows ZooKeeper to be used extensively by client applications.USENIX Annual Technical Conferencedistributed_systems/2017-09-11T23:07:04.6597390142017-09-11T23:07:04.659739014

<01>	<09>3
<01>
}<02>
9GGThe Pagerank Citation Ranking: Bringing Order to the Web<07>The importance of a Web page is an inherently subjective matter, which depends on the readers interests, knowledge and attitudes. But there is still much that can be said objectively about the relative importance of Web pages. This paper describes PageRank, a method for rating Web pages objectively and mechanically, eeectively measuring the human interest and attention devoted to them. We compare PageRank to an idealized random Web surfer. We show how to eeciently compute PageRank for large numbers of pages. And, we show how to apply PageRank to search and to user navigation.information_retrieval/2017-09-11T23:07:05.7541721192017-09-11T23:07:05.754172119<EFBFBD>]<5D>k
[<02>C3EEReducing Garbage Collector Cache Misses<07>Cache misses are currently a major factor in the cost of garbage collection, and we expect them to dominate in the future. Traditional garbage collection algorithms exhibit relatively little temporal locality; each live object in the heap is likely to be touched exactly once during each garbage collection. We measure two techniques for dealing with this issue: prefetch-on-grey, and lazy sweeping. The first of these is new in this context. Lazy sweeping has been in common use for a decade. It was introduced as a mechanism for reducing paging and pause times; we argue that it is also crucial for eliminating cache misses during the sweep phase.
Our measurements are obtained in the context of a non-moving garbage collector. Fully copying garbage collection inherently requires more traffic through the cache, and thus probably also stands to benefit substantially from something like the prefetch-on-grey technique. Generational garbage collection may reduce the benefit of these techniques for some applications, but experiments with a non-moving generational collector suggest that they remain quite useful.ISMMgarbage_collection/2017-09-11T23:07:05.459992922017-09-11T23:07:05.45999292<EFBFBD>
<EFBFBD>j<00>A<02>?'GGA Data-driven Method for the Detection of Close Submitters in Online Learning Environments<07>Online learning has become very popular over the last decade. However , there are still many details that remain unknown about the strategies that students follow while studying online. In this study, we focus on the direction of detecting 'invisible' collaboration ties between students in online learning environments. Specifically, the paper presents a method developed to detect student ties based on temporal proximity of their assignment submissions. The paper reports on findings of a study that made use of the proposed method to investigate the presence of close submitters in two different massive open online courses. The results show that most of the students (i.e., student user accounts) were grouped as couples, though some bigger communities were also detected. The study also compared the population detected by the algorithm with the rest of user accounts and found that close submitters needed a statistically significant lower amount of activity with the platform to achieve a certificate of completion in a MOOC. These results confirm that the detected close submitters were performing some collaboration or even engaged in unethical behaviors, which facilitates their way into a certificate. However, more work is required in the future to specify various strategies adopted by close submitters and possible associations between the user accounts.WWWgamification/2017-09-11T23:07:05.3836918952017-09-11T23:07:05.383691895
<00>
<0F><0F>P$<0E><0E><0E><0E>qY?!
<0A>
<0A>
<0A>
<0A>
<0A>
o
W
;
<0C><0C><0C><0C><0C>uU;!<0B><0B><0B><0B><0B>dC#
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
q
R
3
	<09>	<09>	<09>	<09>	w	[	4	<08><08><08><08><08><08>pR8<07><07><07><07><07>dF&<06><06><06><06>~\><05><05><05><05><05>~dF!<04><04><04><04>_<<03><03><03><03><03>S(<02><02><02><02>weSA
<01>
<01>
<01>
<01>
<01>
o
U
=
<1F>C'
!M. CelikbilekM.Celikbilek<15>B
B. ZhongB.Zhong<17>A
W. YanqinW.Yanqin<0F>@
M. LiM.Li<0F>?
J. YeJ.Ye<1C>>%P. A. MirceaP.A.Mircea<15>=
M. IancuM.Iancu<1C><%S. D. ValeanS.D.Valean<17>;
M. GordanM.Gordan<18>:!G. A. NagyG.A.Nagy <20>9)M. A. MunteanuM.A.Munteanu<0F>8
Y. LiY.Li<0F>7
C. YuC.Yu<0F>6
C. XuC.Xu<13>5
Y. ChenY.Chen"<22>4+J. P. H. DrenthJ.P. H.Drenth<1F>3'
T.j.g. GeversT.j.g.Gevers<17>2
W. KievitW.Kievit<1A>1#J. A. SloanJ.A.Sloan<1A>0#M. C. HoganM.C.Hogan(<28>/1S. M. H. VerheesenS.M. H.Verheesen*<2A>.3!M. K. K. NeijenhuisM.K. K.Neijenhuis<1D>-%
P. AzimzadehP.Azimzadeh<19>,!
S. IravaniS.Iravani<1F>+'
!A. EshraghianA.Eshraghian<1E>*'A. P. KiyasovA.P.Kiyasov<1B>)#
A. RizvanovA.Rizvanov<1C>(%M. A. TitovaM.A.Titova <20>')A. A. GumerovaA.A.Gumerova"<22>&+G. R. BurganovaG.R.Burganova<17>%
G. PevnevG.Pevnev"<22>$+M. O. MavlikeevM.O.Mavlikeev<1B>##
E. GaraninaE.Garanina#<23>"+
%A. ShafigullinaA.Shafigullina<17>!
A. TitovaA.Titova"<22> +E. I. SharipovaE.I.Sharipova<1B>#
D. HartmannD.Hartmann<17>
N. HüserN.Hüser<17>
H. FriessH.Friess<1B>#
B. HolzmannB.Holzmann<0F>
M. LuM.Lu<19>!
S. SchulzeS.Schulze<13>
C. MadlC.Madl<1D>%
T. ReibergerT.Reiberger!<21>)
#J. FeichtingerJ.Feichtinger<1B>#
C. IlliaschC.Illiasch<1F>'
!F. PleiningerF.Pleininger<1D>%
N. PfistererN.Pfisterer<15>
E. FuchsE.Fuchs<1B>#
M. YalınayM.Yalınay<1B>#
C. ErdoğduC.Erdoğdu<19>!
T. KarakanT.Karakan<15>
C. SofiaC.Sofia<1D>%
C. GregórioC.Gregório<1B>
#
A. OliveiraA.Oliveira<1F>'
!D. BranquinhoD.Branquinho<1D>%
I. SydorchukI.Sydorchuk<1D>
%
L. SydorchukL.Sydorchuk<15>	
P. FominP.Fomin<1D>%
R. SydorchukR.Sydorchuk<1D>%
A. SydorchukA.Sydorchuk<17>
V. BocharV.Bochar<17>
O. BocharO.Bochar<1B>#
E. SklyarovE.Sklyarov<11>
Y. LiuY.Liu<11>
M. MinM.Min<0F>

Y. BiY.Bi<1B>#
B. GrahovacB.Grahovac<17>
D. StimacD.Stimac<17>~
D. KovačD.Kovač<1D>}%
M. ČarapinaM.Čarapina<15>|
S. MilicS.Milic$<24>{-B. Mohar VitezicB.MoharVitezic<19>z!
J. PrakashJ.Prakash<15>y
G. StormG.Storm<1B>x#
B. ÖztürkB.Öztürk<17>w
R. BansalR.Bansal<1C>v%R. E. CastroR.E.Castro%<25>u-
C.m.p. RodriguesC.m.p.Rodrigues"<22>t+P. M. RodriguesP.M.Rodrigues<1C>s%M. B. AfonsoM.B.Afonso<1C>r%A. L. SimãoA.L.Simão<15>q
N. RossoN.Rosso<1D>p%
C. TiribelliC.Tiribelli<1D>o%
F. ZanconatiF.Zanconati<19>n!
D. BonazzaD.Bonazza<1D>m%
N. DemanziniN.Demanzini<1B>l#
M. GiuricinM.Giuricin<1D>k%
S. PalmisanoS.Palmisano<1E>j'S. E. GambaroS.E.Gambaro<1E>i'P. J. GiraudiP.J.Giraudi,<2C>h5)C. M. ChackeleviciusC.M.Chackelevicius<11>g
Y. NieY.Nie<0F>f
H. HeH.He<11>e
X. LiuX.Liu<15>d
F. BendeF.Bende<18>c!R. G. MareR.G.Mare<17>b
A. StepanA.Stepan<17>a
M. DanilaM.Danila<1D>`%
R.l.d. SirliR.l.d.Sirli<19>_!
A. PopescuA.Popescu<17>^
I. SporeaI.Sporea<1B>]#
R. LupusoruR.Lupusoru<17>\
M. ParolaM.Parola<17>[
E. AlbanoE.Albano<1D>Z%
E. BugianesiE.Bugianesi<1B>Y#
P. PontissoP.Pontisso<19>X!
G. VillanoG.Villano<15>W
C. BoccaC.Bocca<13>V
E. NovoE.Novo<19>U!
S. BruzzìS.Bruzzì<17>T
B. FogliaB.Foglia<19>S!
S. CannitoS.Cannito<15>R
S. SuttiS.Sutti<19>Q!
E. MorelloE.Morello<13>P
T. OhtaT.Ohta<1B>O#
Y. YamamotoY.Yamamoto<17>N
S. TakadaS.Takada<15>M
S. KanouS.Kanou<1D>L%
T. MiyashitaT.Miyashita<17>K
M. NakuraM.Nakura&<26>J/Claude E. ShannonClaudeE.Shannon'<27>I/
!Úlfar ErlingssonÚlfarErlingsson#<23>H+
Arnar BirgissonArnarBirgisson)<29>G1%
Hans-Juergen BoehmHans-JuergenBoehm,<2C>F5Carlos Delgado KloosCarlosDelgadoKloos0<73>E9Pedro J. Muñoz MerinoPedroJ. MuñozMerino!<21>D)
Dragan GasevicDraganGasevic'<27>C/
Vitomir KovanovicVitomirKovanovic
o<0C><0B>fo<00>s<EFBFBD>q
s<02>U
9GGDavis's Poetic Dialogue with Leiris's Autobiography<07>In his article "Davis's Poetic Dialogue with Leiris's Autobiography" Jonathan Evans analyzes Lydia Davis's translation of the first two parts of Michel Leiris's autobiography, which shows an encounter between two writers. Davis has also written stories which reference Leiris and thus position him as a precursor. Evans proposes that Leiris is not only a source of influence for Davis, but that their texts can be read as a dialogue. Using a methodology that draws on Lacanian psychoanalysis, Evans shows how Leiris focuses on sound and graphological patterns in order to understand his own conscious and unconscious relationship with words. Davis, in her stories, forces the reader to question their own relationship to language and the symbolic order. Thus, Davis's translation of Leiris's autobiography becomes a graft on her work as it offers her a chance to explore writing in a way which would be uncharacteristic in her own work. Jonathan Evans, "Davis's Poetic Dialogue with Leiris's Autobiography" page 2 of 10 CLCWeb: Comparative Literature and Culture 14.1 (2012): <http://docs.lib.purdue.edu/clcweb/vol14/iss1/8>logic_and_programming/2017-09-11T23:07:12.6113049322017-09-11T23:07:12.611304932y<EFBFBD>p	Q

1GGUEG Week 2016 Poster Presentations<07>languages/haskell/2017-09-11T23:07:06.4984450682017-09-11T23:07:06.498445068<EFBFBD>&<26>o	Y
a3EEA mathematical theory of communication<07>Mobile Computing and Communications Reviewinformation_theory/2017-09-11T23:07:06.318742922017-09-11T23:07:06.31874292<EFBFBD>p<EFBFBD>n<00>/<02>1GGAn implementation and semantics for transactional memory introspection in Haskell<07>Transactional Memory Introspection (TMI) is a novel reference monitor architecture that provides complete mediation, freedom from <i>time of check to time of use</i> bugs and improved failure handling for authorization. TMI builds on and integrates with implementations of the Software Transactional Memory (STM) architecture [Harris and Fraser 2003]. In this paper we present a formal definition of TMI and a concrete implementation over the Haskell STM. We find that this specification and reference implementation establishes clear semantics for the TMI architecture. In particular, they help identify and resolve ambiguities that apply to implementations such in our prior work [Birgisson et al. 2008].PLASlanguages/haskell/2017-09-11T23:07:06.1644838872017-09-11T23:07:06.164483887
F<00>
<01><0C><0C>H{gR<)<07><0B><0B><0B><0B>0<0B><0B>|olWD2
<EFBFBD>
<EFBFBD>
p<03><03>
<EFBFBD><03><07>H:H<04><04>
<04><04>
<01>
<01>a<05><04><0F>8<02><04><08><0F>5<05>Q(<07><05>
<01><07>'sr<04>_k<05><07><0F><05>
<01>'
<01><04>]<05><05>9
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
n
]<03>
F
3

	^	<09><07>	<09>	<09><02>	<09>	<09>	<09><07>		h<08>X<08>	[	I	2		
s<08><02><08><02><08><08>
<01>
<01><02><02>q<03>z'S<03><0F>@1	<06><06><06><06><06><06>t`I6G<0F><0F>t_O<+
[<0E><0E><0E><0E><0E>kXD1
<0A>
<0A>
<0A><08>
<0A>
<0A>
<0A>
<0A>
<0A>o J. Muño!S. Bruzzì<03>!S. Cannito<03>
S. Sutti<03>S. Takada<03>
S. Kanou<03>'Shu-Chun Weng<00>7Shriram Krishnamurthi3)Shojiro Nishio
<01>-Shiva Shivakumar<00>-Roger Dingledine<03>XRachel S. Itoe
S. Vitor<04>S. Mizuno{%Simon Marlow
<01>3
Siegfried RasthoferX!S. Hayashii'Shih-Fu Chang<03>#Sharad Goel<03>#Saul Jaspan'Simon Haegler<00>%Sachin Kattiv'Ryan Stutsmanum'Simon Parsons
<01>
S Kabbajm!S Bouchibal5Ric%S. Matsubara|-Simon J. Puglisi<02>#Ryan Farellb)Slava Chernyak
O/Simon J. Thompson#Samuel BenzY-Russell C. SearsU'Russell PowerH<05>
S. Jo<04>
S. Milic<03>7Simon L. Peyton Jones
<01><04>S. Y. Seo<05>-Robert E. Gruber2+Sanjay Ghemawat-Shan He%VS. H. Kim<05>S. B. Kim<05>%S. Abou Saif<04>
S. Hefny<04>!S. Barakat<04>#S. Tawefeek<04>)S. Abd-Elsalam<04>/S. Manolakopoulos<04>1S. R. R. Fernandes<04>
S. Lopesz'S. Ioanitescut
S. AbbaspR. LiU%S. D. Valean<1S. M. H. Verheesen/!S. Iravani,!S. SchulzeS. W. Kim<05>S. K. Cho<04>!S. W. Shin<04>%S. Palmisano<03>'S. E. Gambaro<03>!S. W. Paik<04>nRS. O. Lee<05>S. T. Lee<05>'Stephen Chong}/Stephanie Miedema<03>)Stephan Ellner
)Steffen Grarup
<01>#Stefan Frei<02>1Stefan Dziembowski_-Stefan Burkhardt<02>'Sriram Sankar
<01>3Srinath T. V. Setty
<01>-Srikanth Kandula
<01>%
Srijan Kumar:/Srecko Joksimovic<03>!
Somesh Jha'Sofia Syntila
7Sivakumar Viswanathan<00><07>!S. M. Park<05>'Scott Wallace%Rémi Coulom<02><07>RobS. Kim<05>S. Park<05>+Sanjoy Dasgupta<02><0C>
PhilipS. Jang+Robert S. Boyer<02><08>S. AraiC#S. Strasser!!S. IvashukS. Han<08>#Stephen Fox
/Sebastian Thrunyz<02>#Ronald Parr<02>+Sebastian Thrun<02>T. GagoSeep Goel<05>'S. Hohenester''Shiva Shankar<00>/Shinichi Kawamoto<00>!
Shi-Min Hui#
Shangyu Luo3'
Shahram Izadin'Sergey Melnik<00>/Sergey Doroshenko
<01>%Sergey Bykov
]
Sen Wang8/Sebastian Fischer3Sebastian Deterding
<01>'Scott Shenker
<01>#Scott Owens<00>+Scott A. Brandt<00>#Satadru Pan<00>)Sanni Siltanen<00>'Sanjeev Kumar<00>-Sandhya Kunnatur
<01>+
Sander Dieleman$'Samuel Madden
/Samuel C. Kendall
i#Sam Whittle
U3Sam Tobin-Hochstadt#Sam Mcveety
R#
Salim Virji[%Sage A. Weil<00>)Sabyasachi Roy<00>)Ryan Culpepper8-
Rusmin Soetjipto

Runhui LiD+Ruey-Lung Hsiao
3
Roy Thomas Fielding%Rowan Davies'Ross Patersone+Roshan P. James
<01>#
Rose F. Liu
-Ronald L. Rivest<00>5Romi Fadillah Rahmat<02>+Rolf Neugebauer^!Roel Wuyts
+3Rodrigo De Oliveira
<01>%Robin Milner<02>-Robert W. Sumner<00>/Robert N M WatsonY'Robert Morris
A-Robert Griesemer
b+Robert Fenichel
<01>)Robert Escriva
/Robert E. Shostak
}/Robert D. Blumofe
Y/Robert Cartwright<02><0F><00>Robert Bruce Findler5<0F><02>Robbert Van Renesse
<01><0F><02>Rob Arthan<00>%Rilla Khaled
<01><0F><02>Richard Mortier
<01>/Richard L. Hudson
<01>-Richard Carlsson<00>3
+Stijn Mostinckx<05>3Russell C. Eberhart<05>T. Lee
T. KuwaiW#T. KobatakeB!T. Karakan#T. Ichikawa<04>!T. Bucsics_-Søren B. Lassen
<01>-
Sylvain Lefebvre^ CSwaminathan Sivasubramanian9'Svante Janson<02>+
Suvrat Bhooshan1'Susmit Sarkar<00>)Sunny Consolvo
<01>%Sunil Shukla;1Sunil Kumar Shinde'Sung-Eui Yoon<03>-Sudipta Sengupta
&/Stéphane Ducasse
(3Stéphane Clinchant
<01>%Steven Smith
<01>/Steven M. Lavalle<02>#Steven Hand
<01>'Steven Awodey<02>#
Steven Arzt+Steve Marschner<00>%
Steve Hodgesu/Stephen M. Rumblet%Stephen Kell<02>/Smruti R. Sarangi<05>S. H. Lee]S. IioT!S. Ryozawa?R. Quispel1
<00>
<0F><0F><0F><0F>[A'<0E><0E><0E><0E>eE'
<0A>
<0A>
<0A>
<0A>
x
\
>
&<0C><0C><0C><0C><0C>b6<0B><0B><0B><0B><0B>hL
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
m
S
=
	<09>	<09>	<09>	<09>	<09>	k	S	1	<08><08><08><08><08>{[?#<07><07><07><07><07>u_C-<06><06><06><06>vZ<"<05><05><05><05>|bH.<04><04><04><04>mL2<03><03><03><03><03>|\@$
<02><02><02>{]C
<01>
<01>
<01>
<01>
{
W
1
<15>C
Y. AhmadY.Ahmad#<23>B+
%M. Sharaf-EldinM.Sharaf-Eldin!<21>A)
#S. Abd-ElsalamS.Abd-Elsalam<19>@!
G. DalekosG.Dalekos#<23>?+
%K. ZisimopoulosK.Zisimopoulos<1B>>#
C. ΤsoulasC.Τsoulas<1B>=#
A. KourikouA.Kourikou<1D><%
A. KoukofikiA.Koukofiki'<27>;/
)M. PapatheodoridiM.Papatheodoridi<17>:
K. ZachouK.Zachou<1B>9#
C. TriantosC.Triantos'<27>8/
)S. ManolakopoulosS.Manolakopoulos<17>7
J. GoulisJ.Goulis.<2E>67+G. V. PapatheodoridisG.V.Papatheodoridis<17>5
M. BilzerM.Bilzer<17>4
B. DreherB.Dreher<19>3!
E. ZehnterE.Zehnter<19>2!
U. NaumannU.Naumann<1D>1%
T. WitthöftT.Witthöft<15>0
B. WeberB.Weber<15>/
P. GeyerP.Geyer<15>.
M. KrausM.Kraus<1B>-#
H. SteffensH.Steffens<17>,
G. TeuberG.Teuber<15>+
H. LöhrH.Löhr<1B>*#
P. BuggischP.Buggisch<17>)
J. VelosaJ.Velosa<1E>('R. T. MarinhoR.T.Marinho!<21>')
#P. AlexandrinoP.Alexandrino(<28>&1S. R. R. FernandesS.R. R.Fernandes<15>%
S. VitorS.Vitor<19>$!
P. PereiraP.Pereira<1F>#'
!R. GonçalvesR.Gonçalves<19>"!
H. RibeiroH.Ribeiro<17>!
R. CoelhoR.Coelho<17> 
G. MacedoG.Macedo<17>
R. GasparR.Gaspar<19>!
A. PeixotoA.Peixoto<19>!
H. CardosoH.Cardoso!<21>)
#A. AlbuquerqueA.Albuquerque<15>
M. SilvaM.Silva<13>
J. ReisJ.Reis<19>!
A. MartinsA.Martins<17>
L. SantosL.Santos<1B>#
R. CarvalhoR.Carvalho<19>!
M. CardosoM.Cardoso<17>
E. BrancoE.Branco<1B>#
J. CarvalhoJ.Carvalho<17>
V. AnapazV.Anapaz <20>)M. A. El ZahryM.A. ElZahry<1A>#Z. M. HefnyZ.M.Hefny"<22>+A. T. AbdelmoezA.T.Abdelmoez<13>
E. AdelE.Adel<19>!
M. AttallaM.Attalla<13>

I. AokiI.Aoki<17>
H. SasakiH.Sasaki<19>!
N. MachidaN.Machida<1B>
#
T. IchikawaT.Ichikawa<15>	
A. SilvaA.Silva<1B>#
P. MinistroP.Ministro!<21>)
#A. CastanheiraA.Castanheira<19>!
E. CancelaE.Cancela<19>!
R. AraújoR.Araújo<1D>%
J. FernandesJ.Fernandes<15>
J. PinhoJ.Pinho<19>!
D. MartinsD.Martins<15>

P. SousaP.Sousa<19>!
J. RoseiraJ.Roseira<13>
T. GagoT.Gago<15>~
L. ToméL.Tomé<1D>}%
C. AgostinhoC.Agostinho<1F>|'
!P. FigueiredoP.Figueiredo<15>{
D. GomesD.Gomes<15>z
S. LopesS.Lopes<19>y!
C. LériasC.Lérias'<27>x/
)M. Gravito-SoaresM.Gravito-Soares<17>w
E. SoaresE.Soares<19>v!
I. LupescuI.Lupescu<19>u!
G. ChiriacG.Chiriac<1F>t'
!S. IoanitescuS.Ioanitescu<13>s
L. MicuL.Micu<17>r
I. CopaciI.Copaci<1C>q%M. A. EljakyM.A.Eljaky<15>p
S. AbbasS.Abbas<1C>o%E. S. TharwaE.S.Tharwa <20>n)E. M. AbdelaalE.M.Abdelaal<17>m
F. KarnelF.Karnel<17>l
J. KarnerJ.Karner/<2F>k7
1M. Peck-RadosavljevicM.Peck-Radosavljevic<19>j!
M. TraunerM.Trauner<1B>i#
W. SieghartW.Sieghart<1D>h%
A. FerlitschA.Ferlitsch<15>g
M. CejnaM.Cejna<1D>f%
B. AngermayrB.Angermayr<1D>e%
M. MandorferM.Mandorfer<19>d!
P. SchwablP.Schwabl<19>c!
N. GöschlN.Göschl)<29>b1
+M. Feldner-BusztinM.Feldner-Busztin<1B>a#
M. DiermayrM.Diermayr<19>`!
M. SchoderM.Schoder<19>_!
T. BucsicsT.Bucsics<1D>^%
H. GuerreiroH.Guerreiro <20>])A. P. OliveiraA.P.Oliveira(<28>\1B. M. Santos PeixeB.M. SantosPeixe<15>[
A. AlvesA.Alves<1B>Z#
P. QueirósP.Queirós<19>Y!
C. MartinsC.Martins<11>X
A. VazA.Vaz<1B>W#
C. TeixeiraC.Teixeira$<24>V-A. G. G. AntunesA.G. G.Antunes<0F>U
R. LiR.Li"<22>T+J. I. EmparanzaJ.I.Emparanza<1C>S%M. L. RinconM.L.Rincon<1B>R#
U. MendarteU.Mendarte<1D>Q%
L. ZubiaurreL.Zubiaurre#<23>P+
%B. ArrizabalagaB.Arrizabalaga<1D>O%
G. LetamendiG.Letamendi<1E>N'M. D. De JuanM.D. DeJuan<17>M
P. OtazuaP.Otazua<1B>L#
E. SalvadorE.Salvador <20>K)J. M. AlustizaJ.M.Alustiza<17>J
I. UrretaI.Urreta<17>I
E. ZapataE.Zapata.<2E>H7A. Castiella EguzkizaA.CastiellaEguzkiza<1A>G#H. I. SerinH.I.Serin<1B>F#
T. YildirimT.Yildirim<15>E
A. AktasA.Aktas<1E>D'Z. T. OzdemirZ.T.Ozdemir

:<02><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F>|qf[PE:/$<0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E>ti^SH=2'
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
w
l
a
V
K
@
5
*


	<0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C>zodYNC8-"
<0B><0B><0B><0B><0B><0B><0B><0B><0B><0B><0B>}rg\QF;0%
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
u
j
_
T
I
>
3
(


	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	x	m	b	W	L	A	6	+	 		
<08><08><08><08><08><08><08><08><08><08><08><08>{peZOD9.#
<07><07><07><07><07><07><07><07><07><07><07>~sh]RG<1&<06><06><06><06><06><06><06><06><06><06><06><06>vk`UJ?4)<05><05><05><05><05><05><05><05><05><05><05><05>yncXMB7,!<04><04><04><04><04><04><04><04><04><04><04>|qf[PE:/$<03><03><03><03><03><03><03><03><03><03><03>ti^SH=2'<02><02><02><02><02><02><02><02><02><02><02><02><08>Z<05>
|<08>Y<05>
{<08>X<05>
{<08>W<05>
{<08>V<05>
{<08>U<05>
{<08>T<05>
z<08>S<05>
y<08>R<05>
y<08>Q<05>
y<08>P<05>
x<08>O<05>
x<08>N<05>
w<08>M<05>
w<08>L<05>
w<08>K<05>
w<08>J<05>
v<08>I<05>
v<08>H<05>
u<08>G<05>
u<08>F<05>
u<08>E<05>
t<08>D<05>
t<08>C<05>
t<08>B<05>
s<08>A<05>
r<08>@<05>
q<08>?<05>
p<08>><05>
p<08>=<05>
p<08><<05>
p<08>;<05>
p<08>:<05>
p<08>9<05>
p<08>8<05>
p<08>7<05>
p<08>6<05>
p<08>5<05>
p<08>4<05>
p<08>3<05>
p<08>2<05>
p<08>1<05>
p<08>0<05>
p<08>/<05>
p<08>.<05>
p<08>-<05>
p<08>,<05>
p<08>+<05>
p<08>*<05>
p<08>)<05>
p<08>(<05>
p<08>'<05>
p<08>&<05>
p<08>%<05>
p<08>$<05>
p<08>#<05>
p<08>"<05>
p<08>!<05>
p<08> <05>
p<08><05>
p<08><05>
p<08><05>
p<08><05>
p<08><05>
p<08><05>
p<08>
p<08>~
p<08>}
p<08>|
p<08>{
p<08>z
p<08>y
p<08>x
p<08>w
p<08>v
p<08>u
p<08>t
p<08>
s
p<08>r
p<08>q
p<08>
p
p<08>	o
p<08>n
p<08>m
p<08>l
p<08>k
p<08>j
p<08>i
p<08>h
p<08>
g
p<08>f
p<08>e
p<08>~d
p<08>}c
p<08>|b
p<08>{a
p<08>z`
p<08>y_
p<08>x^
p<08>w]
p<08>v\
p<08>u[
p<08>tZ
p<08>sY
p<08>rX
p<08>qW
p<08>pV
p<08>oU
p<08>nT
p<08>mS
p<08>lR
p<08>kQ
p<08>jP
p<08>iO
p<08>hN
p<08>gM
p<08>fL
p<08>eK
p<08>dJ
p<08>cI
p<08>bH
p<08>aG
p<08>`F
p<08>_E
p<08>^D
p<08>]C
p<08>\B
p<08>[A
p<08>Z@
p<08>Y?
p<08>X>
p<08>W=
p<08>V<
p<08>U;
p<08>T:
p<08>S9
p<08>R8
p<08>Q7
p<08>P6
p<08>O5
p<08>N4
p<08>M3
p<08>L2
p<08>K1
p<08>J0
p<08>I/
p<08>H.
p<08>G-
p<08>F,
p<08>E+
p<08>D*
p<08>C)
p<08>B(
p<08>A'
p<08>@&
p<08>?%
p<08>>$
p<08>=#
p<08><"
p<08>;!
p<08>: 
p<08>9
p<08>8
p<08>7
p<08>6
p<08>5
p<08>4
p<08>3
p<08>2
p<08>1
p<08>0
p<08>/
p<08>.
p<08>-
p<08>,
p<08>+
p<08>*
p<08>)
p<08>(
p<08>'

p<08>&
p<08>%
p<08>$

p<08>#	
p<08>"
p<08>!
p<08> 
p<08>
p<08>
p<08>
p<08>
p<08>

p<08>
p<08><04>
p<08><04>
p<08><04>
p<08><04>
p<08><04>
p<08><04>
p<08><04>
p<08><04>
p<08><04>
p<08><04>
p<08><04>
p<08><04>
p<08>
<04>
p<08><04>
p<08><04>
p<08>
<04>
p<08>	<04>
p<08><04>
p<08><04>
p<08><04>
p<08><04>
p<08><04>
p<08><04>
p<08><04>
p<08>
<04>
p<08><04>
p<08><04>
p<08>~<04>
p<08>}<04>
p<08>|<04>
p<08>{<04>
p<08>z<04>
p<08>y<04>
p<08>x<04>
p<08>w<04>
p<08>v<04>
p<08>u<04>
p<08>t<04>
p<08>s<04>
p<08>r<04>
p<08>q<04>
p<08>p<04>
p<08>o<04>
p<08>n<04>
p<08>m<04>
p<08>l<04>
p<08>k<04>
p<08>j<04>
p<08>i<04>
p<08>h<04>
p<08>g<04>
p<08>f<04>
p<08>e<04>
p<08>d<04>
p<08>c<04>
p<08>b<04>
p<08>a<04>
p<08>`<04>
p<08>_<04>
p<08>^<04>
p<08>]<04>
p<08>\<04>
p<08>[<04>
p<08>Z<04>
p<08>Y<04>
p<08>X<04>
p<08>W<04>
p<08>V<04>
p<08>U<04>
p<08>T<04>
p<08>S<04>
p<08>R<04>
p<08>Q<04>
p<08>P<04>
p<08>O<04>
p<08>N<04>
p<08>M<04>
p<08>L<04>
p<08>K<04>
p<08>J<04>
p<08>I<04>
p<08>H<04>
p<08>G<04>
p<08>F<04>
p<08>E<04>
p<08>D<04>
p<08>C<04>
p<08>B<04>
p<08>A<04>
p<08>@<04>
p<08>?<04>
p<08>><04>
p<08>=<04>
p<08><<04>
p<08>;<04>
p<08>:<04>
p<08>9<04>
p<08>8<04>
p<08>7<04>
p<08>6<04>
p<08>5<04>
p<08>4<04>
p<08>3<04>
p<08>2<04>
p<08>1<04>
p<08>0<04>
p<08>/<04>
p<08>.<04>
p<08>-<04>
p<08>,<04>
p<08>+<04>
p<08>*<04>
p<08>)<04>
p<08>(<04>
p<08>'<04>
p<08>&<04>
p<08>%<04>
p<08>$<04>
p<08>#<04>
p<08>"<04>
p<08>!<04>
p
<00>
"<0F><0F><0F><0F>nR6<0E><0E><0E>uT8
<0A>
<0A>
<0A>
~
b
I
'
<0C><0C><0C><0C>pL1
<0B><0B><0B><0B><0B>`?%
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
p
U
<
&
	<09>	<09>	<09>	<09>	<09>	j	N	2	<08><08><08><08><08><08>lV>*<07><07><07><07><07><07>nZF4
<06><06><06><06><06>|bD&<05><05><05><05>xV:<04><04><04><04><04>oS7<03><03><03><03>cC<02><02><02><02>kO7
<01>
<01>
<01>
<01>
<01>
u
Z
:
"<15>J
U. KumarU.Kumar<1D>I%
J. BorovickaJ.Borovicka<18>H!M. C. SulzM.C.Sulz!<21>G)
#C. MeyenbergerC.Meyenberger<13>F
R. FreiR.Frei<1B>E#
G. SemadeniG.Semadeni<19>D!
Y. MashimoY.Mashimo<13>C
S. AraiS.Arai<1B>B#
T. KobatakeT.Kobatake<17>A
M. HaradaM.Harada<15>@
H. IwanoH.Iwano<19>?!
S. RyozawaS.Ryozawa<1B>>#
Y. TanisakaY.Tanisaka%<25>=-
'L. Taberna-AranaL.Taberna-Arana <20><)J. Garcia CanoJ.GarciaCano%<25>;-
'K. MönkemüllerK.Mönkemüller<19>:!
H. NeumannH.Neumann(<28>91%M. A. D’assuncaoM.A.D’assuncao<1D>8%
I. JovanovicI.Jovanovic/<2F>77
/Á. Martínez-AlcaláÁ.Martínez-Alcalá<1E>6'P. T. KroenerP.T.Kroener<1A>5#M. J. BrunoM.J.Bruno<15>4
B. VeldtB.Veldt"<22>3+L. M. Van DrielL.M. VanDriel$<24>2-M. Van Der VoortM.Van DerVoort<19>1!
R. QuispelR.Quispel<19>0!
D. ShapiroD.Shapiro<17>/
T. MarmonT.Marmon<1D>.%
L. MacconellL.Macconell<17>-
B. HansenB.Hansen<19>,!
C. VincentC.Vincent<17>+
V. VargasV.Vargas <20>*)K. Van ErpecumK.VanErpecum<1B>)#
M. ShiffmanM.Shiffman<19>(!
V. LuketicV.Luketic<1F>''
!S. HohenesterS.Hohenester<1B>&#
A. FloreaniA.Floreani<17>%
J. RegulaJ.Regula<19>$!
P. PockrosP.Pockros<1F>#'
!P. InvernizziP.Invernizzi<17>"
C. BowlusC.Bowlus<1B>!#
S. StrasserS.Strasser<1B> #
G. MazzellaG.Mazzella<1B>#
P. AndreoneP.Andreone<17>
F. NevensF.Nevens<1B>#
O. PlehutsaO.Plehutsa<19>!
S. IvashukS.Ivashuk<13>
M. KangM.Kang<11>
H. KooH.Koo<13>
K. SongK.Song<11>
T. LeeT.Lee<11>
K. HuhK.Huh<13>
Y. KangY.Kang<0F>
K. YuK.Yu<11>
S. HanS.Han<11>
K. RyuK.Ryu<13>
Y. ChoiY.Choi<13>
S. JangS.Jang<0F>
X. LiX.Li<17>
K. TanakaK.Tanaka<17>
A. SuzukiA.Suzuki<1B>
#
N. SakiyamaN.Sakiyama<13>
H. WangH.Wang<13>
X. WangX.Wang<11>

X. ZhuX.Zhu<15>	
L. ZhangL.Zhang<13>
W. MengW.Meng<11>
J. YanJ.Yan<13>
L. MiaoL.Miao<13>
W. ZhouW.Zhou<11>
K. ZhuK.Zhu<15>
D. FestiD.Festi<19>!
A. PessionA.Pession<15>

A. PreteA.Prete#<23>+
%K. KleinschmidtK.Kleinschmidt<19>!
R. MasettiR.Masetti<19>~!
G. MarascoG.Marasco<1D>}%
A. ColecchiaA.Colecchia<1B>|#
F. RavaioliF.Ravaioli<18>{!M. S. ChoiM.S.Choi<18>z!S. W. PaikS.W.Paik<16>yK. C. KohK.C.Koh<16>xJ. H. LeeJ.H.Lee<13>w
G. GwakG.Gwak<13>v
W. KangW.Kang<16>uS. K. ChoS.K.Cho<18>t!S. W. ShinS.W.Shin<18>s!D. H. SinnD.H.Sinn<0F>r
S. JoS.Jo<1C>q%N. Al HajjarN.AlHajjar<15>p
C. IancuC.Iancu<15>o
I. GrozaI.Groza<13>n
P. RaduP.Radu <20>m)Z. A. SparchezZ.A.Sparchez<17>l
K. HoneinK.Honein<1E>k'J. Bou JaoudeJ.BouJaoude <20>j)A. Abou RachedA.AbouRached<1E>i'R. Slim KaramR.SlimKaram<17>h
R. SayeghR.Sayegh<15>g
J. HajalJ.Hajal<15>f
C. YaghiC.Yaghi<1C>e%A. S. HanafyA.S.Hanafy!<21>d)
#N. MuscatielloN.Muscatiello<18>c!M. Di MasoM.DiMaso!<21>b)
#A. FacciorussoA.Facciorusso<17>a
M. YousefM.Yousef<1C>`%M. El GharibM.ElGharib<1C>_%S. Abou SaifS.AbouSaif<13>^
O. NegmO.Negm<1F>]'
!L. SandulescuL.Sandulescu$<24>\-!L. M. SconfienzaL.M.Sconfienza<1F>['
!F. SardanelliF.Sardanelli<16>ZG. Di LeoG.DiLeo<19>Y!
D. OrlandiD.Orlandi<19>X!
C. MessinaC.Messina<17>W
R. CasaleR.Casale<1E>V'G. E. TontiniG.E.Tontini(<28>U1L. Carlo PescatoriL.CarloPescatori<1B>T#
V. IvashkinV.Ivashkin<17>S
C. PavlovC.Pavlov<19>R!
E. LiusinaE.Liusina<1E>Q'T. Voicu MogaT.VoicuMoga+<2B>P3
-C. Ivascu-SiegfriedC.Ivascu-Siegfried<19>O!
A. MansourA.Mansour"<22>N+M. Abd El-KaderM.AbdEl-Kader<19>M!
E. ShehataE.Shehata<15>L
S. HefnyS.Hefny<1B>K#
W. El-GendyW.El-Gendy<19>J!
S. BarakatS.Barakat<19>I!
I. PedrotoI.Pedroto <20>H)J. M. FerreiraJ.M.Ferreira<19>G!
T. MoreiraT.Moreira<1A>F#J. C. SousaJ.C.Sousa<15>E
M. RochaM.Rocha<1B>D#
S. TawefeekS.Tawefeek

<0A><00>
<01>
<0A>
<0A>
<0A>
~
l
]
L
8
%

<0C><0C><0C><0C><0C><0C><0C>pc9R<*<0B><0B><0B><0B><0B><0B><0B>iU>)
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD><0F>
{
l<0F>
Y
D
.

	<09>	<09>	<09>	<09>	<09>	<09>	<09>	vi<0F>	e	V	G	6	&	<08><08><08><08><08><08>{hP/X<07><07><07><07><07><07><07><07>~iYH8&
<06><06><06>
<01><06><06><06>l<0F>VE:.!
<05><05><05><05><05><05>F<05>qfYL=0$
<04><04><04><04><04><04><04><04><04><0F>r_Q<,<03><03><03><03><03><03><03>}<0F>jXF2$<02><02><02><02><02><02><02><02>p_(P5#
<01>
<01>
<01>
<01><>-Łukasz Juszczyk/Úlfar Er-William H. Macey<05>-Łukasz Juszczyk/Úlfar Erlingsson<03>+Öznur Özkasap
<01>-Özalp Babaoğlu<03>)Éric Gaussier%Ákos Seress<02>7Á. Martínez-Alcalá7!
Ziv ScullyO%
Zhi-Li ZhangC%Zhi-Hua Zhou$Zhen Xiao
<01>Zhen Ji$
Zhe Zhug%Zhaoguo WangG%Zhanyong Wanw%
Zezhou Chengk!Zexuan Zhu"%
Zekai J. Gao2'Z. T. OzdemirD#Z. M. Hefny<04>
Z. Huang<05>)Z. A. Sparchez<04>'
Yves Le Traon%Yutaka Suzue@'Yuichi Fujiki<00>!
Yuening Hu=Yu Luo
<01>'Youngwoon Lee<03>%Yossi Matias<02>)Yongpeng Zhang#%Yongle Zhang
<01>!Yoel Gluck<02>%Yoann Baveye+Yingyi Bu

1Yifeng Frank Huang
x!Yifan Gong<02>+Yehia El-KhatibG
Yawei LiR'Yasushi Saito
%Yaron Minsky
<01>#Yair Sovran^#Y. Yamamoto<03>Y. Xie<05>#Y. Tanisaka>Y. SumidaRY. Nie<03>
Y. Nakai~#Y. MiyasakoP!Y. MashimoDY. Liu
Y. Li8Y. Kim_Y. KangY. J. KimNY. ChoiY. Chen5
Y. Bi

Y. Ahmad<04>Xu Zhao
<01>!Xindong Wu!Xin Zhuang
<01>'
Xiaowei Huang6%
Xiaoguang Qiy%Xiaofeng Ren<02>Xiao Yang&#Xian Warner<03>)Xavier Défago
<01>X. Zhu
X. WangX. Liu<03>
X. Li#Wyatt Lloyd<00>-Wolfram Burgardy<02>+Wilson C. Hsieh.-William W. Cohen<03>-William Ribarsky<00>3William P. Thurston<03>-William F. Smyth<02>-Whitfield Diffie<00>Wes Irish
<01>'Werner Vogels;%Wenchao Zhou<03>%Wenbing Zhaop!Weiwen Liu<00>#Weimin Chen<02>!Walid Tahax+Waleed F. FarisW. ZhouW. YanqinAW. Yang<05>#W. SieghartiW. MengW. Kievit2W. Kang<04>#W. El-Gendy<04>+Vladimir Vapnik0/Vitomir Kovanovic<03>#Vipin Kumar CVenugopalan Ramasubramaniank1Venkata Rami Reddy'Vedran Dunjko<02>;
Vedavyas Panneershelvam"5Vasileios Trigonakis<00>'Valient Gough
<01>-Valerio Pascucci<00>+Vadim YushprakhTV. Vargas+#V. T. Rajan
<01>1
V. S. Subrahmanian<!V. Luketic(#V. Ivashkin<04>V. BocharV. Anapaz<04>#Urs Hölzles%Ulf T. Wiger<00>!U. Naumann<04>#U. MendarteR
U. KumarJ%Tyler Akidau
L7Tushar Deepak Chandra
a)Tushar Chandra0)
Turner Whitted`#Tudor David<00>%Tudor Bosman
<01>-Traian Stancescu
+Torsten Kröger<02>'Torben ThraneTom Ridge<00>#Tom Jackson
<01>5
Timothy P. Lillicrap)/Timothy L. Harris
<01>#Tim Roselli<03>!Tim Kraska
#Tiark Rompf<00>'
Thore Graepel,1Thomas Würthinger<02>%
Thomas Verma.+Thomas R. GrossQ/Thomas Gazagnaire
<01>)Thomas E. HartD3Thomas Duebendorfer<02>+Thomas Braibant<00>-Thomas B. Schön*#Thomas Arts<00>-Thirumalesh Bhat<02>-Theodore W. HongD-
Theodore JohnsonL+Theo Vassilakis<00>-Thaddeus Diamond<00>%Thabo Beeler<00>-Terry A. Landers
#Ted Kaehler
Tao Chenf#Tanja Lange<00>)Tamás Sarlós<05>+Takuya Katayama
<01>'Takahiro Hara
<01>'T.j.g. Gevers3T. Yumurag#T. YildirimF%T. YamaguchiV%T. Witthöft<04>#T. Watanabex'T. Voicu Moga<04>)T. V. Lakshmani#T. TakasagoQT. Sasaki%T. ReibergerT. Ohta<03>%T. NishimuraS!T. Moreira<04>%T. Miyashita<03>
\T. Marmon/T. Lee
T. KuwaiW#T. KobatakeB!T. Karakan#T. Ichikawa<04>T. Gago!T. Bucsics_-Søren B. Lassen
<01>-
Sylvain Lefebvre^ CSwaminathan Sivasubramanian9'Svante Janson<02>+
Suvrat Bhooshan1'Susmit Sarkar<00>)Sunny Consolvo
<01>%Sunil Shukla;1Sunil Kumar Shinde'Sung-Eui Yoon<03>-Sudipta SYi Xing#Ziling Zhou<05>Tao Wei<05>%Xin-She Yang<05>#Vern Paxson<05>9Ulises Cortés García<05>-Timothy R. Olsen<05>1Wolfgang De Meuter<05>)Tom Van Cutsem<05>Yuhui Shi<05>!Uri Lublin<05>5Yaniv Kamay Qumranet<05>
<00>
<0F><0F><0F><0F>nP2<0E><0E><0E><0E><0E>x_D+
<0A>
<0A>
<0A>
<0A>
<0A>
o
H
2

<0C><0C><0C><0C><0C>p\H%<0B><0B><0B><0B>vZ@"
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
z
`
@
"
	<09>	<09>	<09>	<09>	<09>	w	^	E	,	<08><08><08><08><08><08>jT@,<07><07><07><07><07><07>nV@(
<06><06><06>fI%<05><05><05><05>oM+<04><04><04><04>X><03><03><03><03>`D<02><02><02><02>^:
<01>
<01>
<01>
<01>
a
<
&<26>M/Frank D. FranconeFrankD.Francone"<22>L+Martin A. KeaneMartinA.Keane$<24>K-Peter J. BentleyPeterJ.Bentley#<23>J+
Christian JacobChristianJacob<17>I
Yuhui ShiYuhuiShi*<2A>H3Russell C. EberhartRussellC.Eberhart<1F>G'
James KennedyJamesKennedy <20>F)David B. FogelDavidB.Fogel!<21>E)
Dennis RitchieDennisRitchie(<28>D1Amit Rahul BaishyaAmitRahulBaishya'<27>C/
Christian LimpachChristianLimpach<15>B
Eric JulEricJul&<26>A/Jacob Gorm HansenJacobGormHansen'<27>@/#
Christopher ClarkChristopherClark#<23>?+
Anthony LiguoriAnthonyLiguori<19>>!
Uri LublinUriLublin&<26>=/Dor Laor QumranetDorLaorQumranet,<2C><5Yaniv Kamay QumranetYanivKamayQumranet<19>;!
Avi KivityAviKivity<1A>:#Mu Y ThomasMuYThomas&<26>9/Smruti R. SarangiSmrutiR.Sarangi!<21>8)
Pooja AggarwalPoojaAggarwal<17>7
Seep GoelSeepGoel)<29>61
Benjamin SchneiderBenjaminSchneider$<24>5-William H. MaceyWilliamH.Macey<1B>4#
David GreggDavidGregg<1D>3%
Mark PurcellMarkPurcell<1F>2'
Owen CallananOwenCallanan<1D>1%
Jimmy ClearyJimmyCleary<1F>0'
Jelani NelsonJelaniNelson<1F>/'
Jean BourgainJeanBourgain!<21>.)
Tamás SarlósTamásSarlós<19>-!
Ravi KumarRaviKumar%<25>,-
Anirban DasguptaAnirbanDasgupta <20>+)Paula B. CohenPaulaB.Cohen(<28>*1Marvin D. TretkoffMarvinD.Tretkoff!<21>))
Paula TretkoffPaulaTretkoff<1A>(#Alan C. KayAlanC.Kay,<2C>'5Daniel H. H. IngallsDanielH. H.Ingalls!<21>&)
Jonathan EvansJonathanEvans<1F>%'
!A. GalyavievaA.Galyavieva#<23>$+
%A. AbdulkhakovaA.Abdulkhakova$<24>#-!K. N. SaifullinaK.N.Saifullina<15>"
Z. HuangZ.Huang<13>!
H. TongH.Tong<15> 
L. HuangL.Huang<13>
C. TangC.Tang<13>
W. YangW.Yang<13>
B. SongB.Song<13>
F. YuanF.Yuan<11>
Y. XieY.Xie<0F>
J. LiJ.Li<13>
J. ParkJ.Park<11>
J. ChoJ.Cho<13>
H. JangH.Jang<11>
H. NamH.Nam<11>
S. KimS.Kim<13>
S. ParkS.Park<13>
C. ChoiC.Choi<11>
H. KimH.Kim<13>
D. KangD.Kang<17>
R. DaegonR.Daegon<18>!S. M. ParkS.M.Park<18>!H. B. ChaeH.B.Chae<16>
J. H. HanJ.H.Han<16>S. O. LeeS.O.Lee<16>D. G. KimD.G.Kim<16>
S. T. LeeS.T.Lee<16>	S. W. KimS.W.Kim<16>I. H. KimI.H.Kim<16>S. H. KimS.H.Kim<16>S. B. KimS.B.Kim<16>I. S. MinI.S.Min<16>S. Y. SeoS.Y.Seo<15>
K. KoikeK.Koike<13>
M. TadaM.Tada<1B>
#
N. SasahiraN.Sasahira<1D>%
M. MatsuyamaM.Matsuyama<17>
T. SasakiT.Sasaki<15>~
Y. NakaiY.Nakai<1B>}#
N. YamamotoN.Yamamoto<1D>|%
S. MatsubaraS.Matsubara<17>{
S. MizunoS.Mizuno<1B>z#
N. TakaharaN.Takahara<17>y
R. UchinoR.Uchino<1B>x#
T. WatanabeT.Watanabe<17>w
K. TakagiK.Takagi<19>v!
D. AkiyamaD.Akiyama<19>u!
G. UmefuneG.Umefune<19>t!
H. IsayamaH.Isayama<17>s
A. YamadaA.Yamada<17>r
H. KogureH.Kogure<1B>q#
K. IshigakiK.Ishigaki"<22>p+M. V. KabrawalaM.V.Kabrawala <20>o)P. N. N. DesaiP.N. N.Desai<11>n
E. KimE.Kim<11>m
D. KimD.Kim<11>l
K. MinK.Min<11>k
B. SonB.Son<17>j
N. OhashiN.Ohashi<19>i!
S. HayashiS.Hayashi<19>h!
H. HachiyaH.Hachiya<17>g
T. YumuraT.Yumura<17>f
M. SawadaM.Sawada<11>e
S. ItoS.Ito<13>d
A. MoriA.Mori$<24>c-G. J. M. WebsterG.J. M.Webster<1F>b'
!A. WinstanleyA.Winstanley$<24>a-N. L. H. BekkaliN.L. H.Bekkali<11>`
K. LeeK.Lee<11>_
Y. KimY.Kim<16>^J. K. RyuJ.K.Ryu<16>]S. H. LeeS.H.Lee<16>\J. W. LeeJ.W.Lee<16>[J. H. SonJ.H.Son<18>Z!D. K. JangD.K.Jang<16>YJ. K. LeeJ.K.Lee<15>X
H. KounoH.Kouno<15>W
T. KuwaiT.Kuwai<1D>V%
T. YamaguchiT.Yamaguchi<19>U!
H. ImagawaH.Imagawa<11>T
S. IioS.Iio<1D>S%
T. NishimuraT.Nishimura<17>R
Y. SumidaY.Sumida<1B>Q#
T. TakasagoT.Takasago<1B>P#
Y. MiyasakoY.Miyasako<1D>O%
A. YamaguchiA.Yamaguchi<16>NY. J. KimY.J.Kim<16>MD. H. KohD.H.Koh<18>L!J. H. YoonJ.H.Yoon"<22>K+J. P. GutierrezJ.P.Gutierrez

<00>a<EFBFBD>r
Q<02>W
5GGDesign Principles Behind Smalltalk<07>The purpose of the Smalltalk project is to provide computer support for the creative spirit in everyone. Our work flows from a vision that includes a creative individual and the best computing hardware available. We have chosen to concentrate on two principle areas of research: a language of description (programming language) that serves as an interface between the models in the human mind and those in computing hardware, and a language of interaction (user interface) that matches the human communication system to that of the computer. Our work has followed a two-to four-year cycle that can be seen to parallel the scientific method: Build an application program within the current system (make an observation) Based on that experience, redesign the language (formulate a theory) Build a new system based on the new design (make a prediction that can be tested) The Smalltalk-80 system marks our fifth time through this cycle. In this article, I present some of the general principles we have observed in the course of our work. While the presentation frequently touches on Smalltalk "motherhood", the principles themselves are more general and should prove useful in evaluating other systems and in guiding future work. Just to get warmed up, I'll start with a principle that is more social than technical and that is largely responsible for the particular bias of the Smalltalk project: Personal Mastery: If a system is to serve the creative spirit, it must be entirely comprehensible to a single individual. The point here is that the human potential manifests itself in individuals. To realize this potential, we must provide a medium that can be mastered by a single individual. Any barrier that exists between the user and some part of the system will eventually be a barrier to creative expression. Any part of the system that cannot be changed or that is not sufficiently general is a likely source of impediment. If one part of the system works differently from all the rest, that part will require additional effort to control. Such an added burden may detract from the final result and will inhibit future endeavors in that area. We can thus infer a general principle of design: Good Design: A system should be built with a minimum set of unchangeable parts; those parts should be as general as possible; and all parts of the system should be held in a uniform framework. Language In …languages/smalltalk/2017-09-11T23:07:12.6364619142017-09-11T23:07:12.636461914

<07><07>
I<02>)5GGThe Early History of Smalltalk<07>Most ideas come from previous ideas. The sixties, particularly in the ARPA community, gave rise to a host of notions about &#8220;human-computer symbiosis&#8221; through interactive time-shared computers, graphics screens and pointing devices. Advanced computer languages were invented to simulate complex systems such as oil refineries and semi-intelligent behavior. The soon to follow paradigm shift of modern personal computing, overlapping window interfaces, and object-oriented design came from seeing the work of the sixties as something more than a &#8220;better old thing&#8221;. That is, more than a better way: to do mainframe computing; for end-users to invoke functionality; to make data structures more abstract. Instead the promise of exponential growth in computing/$/volume   demanded that the sixties be regarded as &#8220;<italic>almost</italic> a new thing&#8221; and to find out what the actual &#8220;new things&#8221; might be. For example, one would compute with a handheld &#8220;Dynabook&#8221; in a way that would not be possible on a shared mainframe; millions of potential users meant that the user interface would have to become a learning environment along the lines of Montessori and Bruner; and needs for large scope, reduction in complexity, and end-user literacy would require that data and control structures be done away with in favor of a more biological scheme of protected universal cells interacting only through messages that could mimic any desired behavior.
Early Smalltalk was the first complete realization of these new points of view   as parented by its many predecessors in hardware, language and user interface design. It became the exemplar of the new computing, in part, because we were actually trying for a qualitative shift in belief structures&#8212;a new Kuhnian paradigm in the same spirit as the invention of the printing press&#8212;and thus took highly extreme positions which almost forced these new styles to be invented.HOPL Preprintslanguages/smalltalk/2017-09-11T23:07:12.6938620612017-09-11T23:07:12.693862061
(2(<00><06>u
_<02>_aGGA sparse Johnson: Lindenstrauss transform<07>Dimension reduction is a key algorithmic tool with many applications including nearest-neighbor search, compressed sensing and linear algebra in the streaming model. In this work we obtain a <i>sparse</i> version of the fundamental tool in dimension reduction -- the Johnson-Lindenstrauss transform. Using hashing and local densification, we construct a sparse projection matrix with just ~O(1/&#949;) non-zero entries per column. We also show a matching lower bound on the sparsity for a large class of projection matrices. Our bounds are somewhat surprising, given the known lower bounds of &#937;(1/&#949;<sup>2</sup>) both on the number of rows of any projection matrix and on the sparsity of projection matrices generated by natural constructions. Using this, we achieve an ~O(1/&#949;) update time per non-zero element for a (1 &#949;)-approximate projection, thereby substantially outperforming the ~O(1/&#949;<sup>2</sup>) update time required by prior approaches. A variant of our method offers the same guarantees for sparse vectors, yet its ~O(d) worst case running time matches the best approach of Ailon and Liberty.STOCmachine_learning/dimensionality_reduction/2017-09-11T23:07:12.8329919432017-09-11T23:07:12.832991943<EFBFBD>J<EFBFBD>t
<02>
%GGPart I: Transcendence of Values of Some Special Functions<07>This paper is a transcript of the Inaugural Monroe H. Martin Lecture and Seminar given at Johns Hopkins University on February 23rd and 24th, 2009. In Part I, we present classical and recent results on the transcendence of values of certain special functions of one variable at algebraic points. In Part II, we describe some new results, joint with Marvin D. Tretkoff, on the transcendence of values at algebraic points of hypergeometric functions of several variables. Note that the author's maiden name is Paula B. Cohen. In this part of our paper, we present some results on the transcendence of values of certain special functions of one variable at algebraic points. Recall that the algebraic numbers are the complex numbers satisfying a non-trivial polynomial relation with rational coefficients. We denote the field of rational numbers by Q, and the field of algebraic numbers by Q. A transcendental number, α, is a complex number which is not algebraic. Therefore P (α) = 0 for every polynomial P ∈ Q[x] with at least one non-zero coefficient. The first examples of explicit transcendental numbers are due to Liouville in 1844 [Lio1], but their construction is rather artificial. Liouville showed that an irrational algebraic number cannot be too well approximated by rational numbers with denominators of relatively small size. He then constructed numbers that are so well approximated by rational numbers that they must be transcendental. An example is the number ξ = ∞ n=1 10 −n!. In 1874, Cantor gave another proof of the existence of transcendental numbers. He showed that the set of all algebraic numbers is countable, while the set of real numbers is uncountable. It follows that the set of transcendental numbers is uncountable. Somewhat paradoxically, it is usually very difficult to show that any given number is transcendental.mathematics/2017-09-11T23:07:12.7893640142017-09-11T23:07:12.789364014
N$N<00>R<EFBFBD>w
Y<02>-1GGFast asymmetric thread synchronization<07>For most multi-threaded applications, data structures must be shared between threads. Ensuring thread safety on these data structures incurs overhead in the form of locking and other synchronization mechanisms. Where data is shared among multiple threads these costs are unavoidable. However, a common access pattern is that data is accessed primarily by one dominant thread, and only very rarely by the other, non-dominant threads. Previous research has proposed biased locks, which are optimized for a single dominant thread, at the cost of greater overheads for non-dominant threads. In this article we propose a new family of biased synchronization mechanisms that, using a modified interface, push accesses to shared data from the non-dominant threads to the dominant one, via a novel set of message passing mechanisms. We present mechanisms for protecting critical sections, for queueing work, for caching shared data in registers where it is safe to do so, and for asynchronous critical section accesses. We present results for the conventional Intel&#174; Sandy Bridge processor and for the emerging network-optimized many-core IBM&#174; PowerEN#8482; processor. We find that our algorithms compete well with existing biased locking algorithms, and, in particular, perform better than existing algorithms as accesses from non-dominant threads increase.TACOmemory_management/2017-09-11T23:07:13.0174528812017-09-11T23:07:13.017452881<EFBFBD>X<EFBFBD>v<00>'<02>9aGGToward a unified theory of sparse dimensionality reduction in Euclidean space<07>Let &#934;&#8712;R<sup>m x n</sup> be a sparse Johnson-Lindenstrauss transform [52] with column sparsity s. For a subset T of the unit sphere and &#949;&#8712;(0,1/2), we study settings for m,s to ensure E<sub>&#934;</sub> sup<sub>x&#8712; T</sub> |&#934; x|<sub>2</sub><sup>2</sup> - 1| < &#949;, i.e. so that &#934; preserves the norm of every x &#8712; T simultaneously and multiplicatively up to 1+&#949;. We introduce a new complexity parameter, which depends on the geometry of T, and show that it suffices to choose s and m such that this parameter is small. Our result is a sparse analog of Gordon's theorem, which was concerned with a dense &#934; having i.i.d. Gaussian entries. We qualitatively unify several results related to the Johnson-Lindenstrauss lemma, subspace embeddings, and Fourier-based restricted isometries. Our work also implies new results in using the sparse Johnson-Lindenstrauss transform in randomized linear algebra, compressed sensing, manifold learning, and constrained least squares problems such as the Lasso.STOCmachine_learning/dimensionality_reduction/2017-09-11T23:07:12.9498640142017-09-11T23:07:12.949864014

.<04>
.<00>?<3F>y
/<02>!=GGA Wait-Free Stack<07>In this paper, we describe a novel algorithm to create a concurrent wait-free stack. To the best of our knowledge, this is the first wait-free algorithm for a general purpose stack. In the past, researchers have proposed restricted wait-free implementations of stacks, lock-free implementations, and efficient universal constructions that can support wait-free stacks. The crux of our wait-free implementation is a fast pop operation that does not modify the stack top; instead, it walks down the stack till it finds a node that is unmarked. It marks it but does not delete it. Subsequently, it is lazily deleted by a cleanup operation. This operation keeps the size of the stack in check by not allowing the size of the stack to increase beyond a factor of W as compared to the actual size. All our operations are wait-free and linearizable.ICDCITnon_blocking_algorithms/2017-09-11T23:07:13.2861721192017-09-11T23:07:13.286172119<EFBFBD><0B>x
Q<02>'
9GGThe Meaning of Employee Engagement<07>The meaning of employee engagement is ambiguous among both academic researchers and among practitioners who use it in conversations with clients. We show that the term is used at different times to refer to psychological states, traits, and behaviors as well as their antecedents and outcomes. Drawing on diverse relevant literatures, we offer a series of propositions about (a) psychological state engagement; (b) behavioral engagement; and (c) trait engagement. In addition, we offer propositions regarding the effects of job attributes and leadership as main effects on state and behavioral engagement and as moderators of the relationships among the 3 facets of engagement. We conclude with thoughts about the measurement of the 3 facets of engagement and potential antecedents, especially measurement via employee surveys. The notion of employee engagement is a relatively new one, one that has been heavily marketed by human resource (HR) consulting firms that offer advice on how it can be created and leveraged. Academic researchers are now slowly joining the fray, and both parties are saddled with competing and inconsistent interpretations of the meaning of the construct. Casual observation suggests that much of the appeal to organizational management is driven by claims that employee engagement drives bottom-line results. Indeed, at least one HR consulting firm (Hewitt Associates LLC, 2005, p. 1) indicates that they ''have established a conclusive, compelling relationship between engagement and profitability through higher productivity, sales, customer satisfaction, and employee retention .'' Some practitioners view engagement as having evolved from prior research on work attitudes, directly implying that this newer concept adds interpretive value that extends beyond the boundaries of those traditions. We agree with this thought and hope to show why we agree in what follows. Although compelling on the surface, the meaning of the employee engagement concept is unclear. In large part, this can be attributed to the ''bottom-up'' manner in which the engagement notion has quickly evolved within the practitioner community. This is not an unfamiliar stage in the incre-mental evolution of an applied psychological construct. Thus, similar to the manner in which burnout was at first a construct attributed to pop psychology (Maslach, Schaufeli, & Leiter, 2001) engagement is a concept with a sparse and diverse theoretical and empirically demonstrated nomological net— the relationships among potential antecedents and consequences of engagement as well as the components of engagement have We appreciate the thoughtful comments of our colleagues Karen Barbera and Scott …logic_and_programming/2017-09-11T23:07:13.1694130862017-09-11T23:07:13.169413086

]=
]<00>\<5C>{
Y<02>I
1GGkvm: the Linux Virtual Machine Monitor<07>Virtualization is a hot topic in operating systems these days. It is useful in many scenarios: server consolidation , virtual test environments, and for Linux enthusiasts who still can not decide which distribution is best. Recently , hardware vendors of commodity x86 processors have added virtualization extensions to the instruction set that can be utilized to write relatively simple virtual machine monitors. The Kernel-based Virtual Machine, or kvm, is a new Linux subsystem which leverages these virtualization extensions to add a virtual machine monitor (or hyper-visor) capability to Linux. Using kvm, one can create and run multiple virtual machines. These virtual machines appear as normal Linux processes and integrate seamlessly with the rest of the system. Virtualization has been around almost as long as computers. The idea of using a computer system to emulate another, similar, computer system was early recognized as useful for testing and resource utilization purposes. As with many computer technologies, IBM led the way with their VM system. In the last decade, VMware's software-only virtual machine monitor has been quite successful. More recently, the Xen [xen] open-source hypervisor brought virtualization to the open source world, first with a variant termed paravirtualization and as hardware became available, full virtualization. 2 x86 Hardware Virtualization Extensions x86 hardware is notoriously difficult to virtualize. Some instructions that expose privileged state do not trap when executed in user mode, e.g. popf. Some privileged state is difficult to hide, e.g. the current privilege level, or cpl. Recognizing the importance of virtualization, hardware vendors [Intel][AMD] have added extensions to the x86 architecture that make virtualization much easier. While these extensions are incompatible with each other, they are essentially similar, consisting of: • A new guest operating mode – the processor can switch into a guest mode, which has all the regular privilege levels of the normal operating modes, except that system software can selectively request that certain instructions, or certain register accesses, be trapped. • Hardware state switch – when switching to guest mode and back, the hardware switches the control registers that affect processor operation modes, as well as the segment registers that are difficult to switch, and the instruction pointer so that a control transfer can take effect. • Exit reason reporting – when a switch from guest mode back to host mode occurs, the hardware reports the reason for the switch so that software can take the appropriate action. Under …operating_systems/2017-09-11T23:07:13.3863181152017-09-11T23:07:13.386318115<EFBFBD>?<3F>z
M<02>
1GGThe Story of the Therac in LOTOS<07>We consider the use of formal speciication and veriication techniques for proving the safety, or otherwise, of an abstraction of a safety-critical medical application: the Therac-25 radiation machine. This machine was responsible for several patient deaths in the late 1980s. The speciication is given in LOTOS and we consider trace analysis, property testing, and temporal logic for reasoning about the safe and unsafe behaviour of the speciied machine. The testing tool LOLA is used for rigorous veriicationn with LOLA, two signiicant design errors are uncovered. The work reported herein is part of a case study on the practical use of formal methods in safety-critical softwaree the speciication is based only on an informal description of part of the ma-chine's behaviour, and does not constitute a speciication of the entire machine.operating_systems/2017-09-11T23:07:13.3729770512017-09-11T23:07:13.372977051

<01><0B>
<EFBFBD><07>
<01><00>k<EFBFBD>
U<02>M
OGGGenetic Programming: An Introduction<07>1. viii Line 13, change " iteration s " to " iterations " 2. xv Line 17, change " Figure 99.1 " to " Figure 1 " 3. xv Lines 20-21, delete the sentence " GP-related resources are provided in an appendix. " 4. xvi Figure 99.1, change " 99.1 " to " 1 " 5. xvii After the 2 nd bulleted item beginning " Part III, " insert the following, additional bullet, Y Four appendices summarize valuable resources available for the reader: Appendix A contains printed and recorded resources, Appendix B suggests web-related resources, Appendix C discusses GP software tools, including Discipulus tm , the GP software developed by the authors, and Appendix D mentions events most closely related to the field of genetic programming. URLs can be found online at http://mkp.com/GP-Intro. 6. 52 Line 3, change " and and " to " and " 7. 88 Line 18, change " deGaris " to " de Garis " 8. 128 Line 5, change " derivations " to " deviations " 9. i c N c N c p i − − − = 1 1 to i c N c N c p i − − − = 1 1 11. 142 Exercise 13, line 1, insert " set " after " function " 12. 147 Equation 6.1, change " E[m(H , t]… " to " E[m(H , t + 1)]… " 13. 167 Line 10, change " separarately " to " separately " 14. 168 Equation 6.6, change ∑ k D F (k, jmin (k)) to ∑ j D F (j, jmin (j)) * All line numbers refer to running text and do not include tables, figures, bulleted text, or code samplesparadigms/functional_programming/2017-09-11T23:07:14.0170300292017-09-11T23:07:14.017030029<EFBFBD>h<EFBFBD>~
E<02>_#1GGThe UNIX Time-Sharing System<07>UNIX is a general-purpose, multi-user, interactive operating system for the Digital Equipment Corporation PDP-11/40 and 11/45 computers. It offers a number of features seldom found even in larger operating systems, including: (1) a hierarchical file system incorporating demountable volumes; (2) compatible file, device, and inter-process I/O; (3) the ability to initiate asynchronous processes; (4) system command language selectable on a per-user basis; and (5) over 100 subsystems including a dozen languages. This paper discusses the nature and implementation of the file system and of the user command interface.Commun. ACMoperating_systems/2017-09-11T23:07:13.9887351072017-09-11T23:07:13.988735107<EFBFBD>D<EFBFBD>}
<00>G

OGGRewriting nation-state: borderland literatures of India and the question of state sovereignty<07>paradigms/functional_programming/2017-09-11T23:07:13.9674750982017-09-11T23:07:13.967475098<EFBFBD>q<EFBFBD>|
Q<02>s1GGLive Migration of Virtual Machines<07>Migrating operating system instances across distinct physical hosts is a useful tool for administrators of data centers and clusters: It allows a clean separation between hard-ware and software, and facilitates fault management, load balancing, and low-level system maintenance.
 By carrying out the majority of migration while OSes continue to run, we achieve impressive performance with minimal service downtimes; we demonstrate the migration of entire OS instances on a commodity cluster, recording service downtimes as low as 60<i>ms</i>. We show that that our performance is sufficient to make live migration a practical tool even for servers running interactive loads.
 In this paper we consider the design options for migrating OSes running services with liveness constraints, focusing on data center and cluster environments. We introduce and analyze the concept of writable working set, and present the design, implementation and evaluation of high-performance OS migration built on top of the Xen VMM.NSDIoperating_systems/2017-09-11T23:07:13.6641540532017-09-11T23:07:13.664154053
UY<0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F>|qf[PE:/$<0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E>ti^SH=2'
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
w
l
a
V
K
@
5
*


	<0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C>zodY<08>/
<01><08>.
<01><08>-

<01><08>,
<01><08>+<05>
<01><08>*<05>
<01><08>)<05>
<01><08>(<05>
<01><08>'<05>
<01><08>&<05>
<01><08>%<05>
<01><08>$<05>
<01><08>#<05>
<01><08>"<05>
<01><08>!<05>
<01><08> <05>
<01><08><05>
<01><08><05>
<01><08><05>
<01><08><05>
<01><08><05>
<01><08>
<01><08><05>
<01><08><05>
<01><08><02>
<01><08>
<01><08><05>
<01><08><05>
<01><08><05>
<01><08><05>
<01><08><05>
<01><08><05>
<01><08><05>
<01><08><05>
<01><08>
<05>
<01><08>!
<01><08><05>
<01><08>
<00>
<01><08>	<05>
<01><08><05>
<01><08>
<01><08>
<01><08><05>
<01><08><05>
<01><08><05>
<01><08><05>
<01><08>
<05>
<01><08><05>
<01><08><05>
<01><08>~<00>
<01><08>}<05>
<01><08>|<05>
<01><08>{
<01><08>z<05>
<01><08>y<05>
<01><08>x<05>
<01><08>w<05>
<01><08>vo
<01><08>um
<01><08>t<05>
<01><08>s<00>
<01><08>r<05>
<01><08>q<05>
<08>p<05>
<08>o<05>
<08>n<05>
<08>m<05>
<08>l<05>
<08>k<05>
<08>j<05>
<08>i<05>
<08>h<05>
<08>g<05>
<08>f<05>
<08>e<05>
<08>d
<01>
~<08>c<05>
~<08>b<05>
}<08>a`
|<08>`_
|<08>_<05>
|<08>^<05>
|<08>]<05>
|<08>\
<01>
|<08>[\
|
o|<0F><0F><0F><0F><0F><0F><0F><0F><0F>vfVG6)|<08><0E><0E><0E><0E><0E><0E>x<08>gUA-
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
u
g
X
F
6
&

<0C><0C><0C><0C><0C><0C><0C><0C>|lYE<08>.<0B><0B><0B><0B><0B><0B><0B>{j^H4"
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
~
o
`
U
A
-<08>

	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	n	_	P	D	9	#	<08><08>!Haifeng Yu<05>)Han La Poutré<05> CJ. Octavio Gutierrez-Garcia<05>)Heather Miller<05>!Ingo Maier<05>+Jacob M. Taylor<02>/Jacob Gorm Hansen<05>%Jacob Albers-J.michael Ashley<02>
J. Ye?J. YanJ. W. Lee\J. Velosa<04>/J. Strother Moore<02>+J. Ross Quinlan!J. Roseira<04>J. Reis<04>J. Regula%!J. Prakash<03>
J. Pinho<04>J. Park<05>+J. P. H. Drenth4+J. P. GutierrezK%J. P. Barker<02>)J. M. Ferreira<04>)J. M. AlustizaK
J. Li<05>J. KarnerlJ. K. Ryu^J. K. LeeY%J. J. FurmanN+J. I. EmparanzaT
J. Hajal<04>!J. H. YoonLJ. H. Son[J. H. Lee<04>J. H. Han<05>J. Goulis<04>)J. Garcia Cano<%J. Fernandes<04>)J. Feichtinger-J. Eliot B. Moss
<01>J. Cho<05>#J. Carvalho<04>#J. C. Sousa<04>'J. Bou Jaoude<04>%J. BorovickaI#J. A. Sloan13J. A. M. Vermaseren>'Iulian Moraru
<01>!Ion Stoica
93Ioannis Stavrakakis/Ioannis KoltsidasO1
Ioannis Antonoglou!)Indranil Gupta
<01>)
Ilya Sutskever(#
Ilka Wittig|Ilan Horn
nIan Rae
Ian Pratt_%Ian E. Smith
<01>Ian Dey!Ian ClarkeA#Iain Becker
<01>I. UrretaJ%I. SydorchukI. Sporea<03>I. S. Min<05>!I. Pedroto<04>!I. Lupescuv%I. Jovanovic8I. H. Kim<05>
I. Groza<04>I. CopacirI. Aoki<04>)Hung-Chih Yang
!Huiqing Li
%
Hugues Hoppee/Howard E. Sturgis
<01>)Hiroshi Motoda#Himani Apte
+Hesham A. Rakha/
Hermann Schägger~)Henry G. Baker
<01>)Henrik Nilssony'
Henri Gourauda#Helmut Sies<00>%Harris Hyman<03>-Harold Bekkeringn/Hari Balakrishnan
D-
Hans-Peter Braun}1Hans-Juergen Boehm<03>+Hans-J. Briegel<02>'Hans Svensson<00>!Haizhou Li<02>H. WangH. Tong<05>#H. Steffens<04>H. Sasaki<04>!H. Ribeiro<04>!H. Neumann:H. Nam<05>
H. Löhr<04>
H. KounoXH. KooH. KogurerH. Kim<05>H. Jang<05>
H. Iwano@!H. Isayamat!H. ImagawaU
6<07><0F><0F><0F>h)
<0E><0E><0E>pD"
<0A>
<0A>
<0A>
r
G
#<0C><0C><0C>tO,<0B><0B><0B><0B>[4
<EFBFBD>
<EFBFBD>
<EFBFBD>
w
W
;
	<09>	<09>	<09>	r	R	,	
<08><08><08><08>qF"<07><13>
Yi XingYiXing<1F>'
Barmak ModrekBarmakModrek!<21>
)
Levan AtanelovLevanAtanelov(<28>1#Christopher J. LeeChristopherJ.Lee<19>!
Haifeng YuHaifengYu<1B>~#
Ziling ZhouZilingZhou<1B>}#
Binbin ChenBinbinChen(<28>|1Dawn Xiaodong SongDawnXiaodongSong<13>{
Tao WeiTaoWei<1F>z'
Mathias PayerMathiasPayer#<23>y+
Laszlo SzekeresLaszloSzekeres<1D>x%
Xin-She YangXin-SheYang,<2C>w5Amir Hossein GandomiAmirHosseinGandomi(<28>v1Michael A. NielsenMichaelA.Nielsen.<2E>u7#Christopher M. DawsonChristopherM.Dawson<1B>t#
Vern PaxsonVernPaxson<1D>s%
Asim ShankarAsimShankar<19>r!
Ankur TalyAnkurTaly<1D>q%
Peter WittekPeterWittek<1D>p%
Gael SentísGaelSentís<1D>o%
Alex MonràsAlexMonràs0<73>n9Ulises Cortés GarcíaUlisesCortésGarcía!<21>m)
Matija PretnarMatijaPretnar#<23>l+
Albert EinsteinAlbertEinstein$<24>k-Randy L. BucknerRandyL.Buckner'<27>j/
!Mohana RamaratnamMohanaRamaratnam$<24>i-Timothy R. OlsenTimothyR.Olsen$<24>h-Daniel S. MarcusDanielS.Marcus#<23>g+
Marco ScandurraMarcoScandurra0<61>f9Alejandro A. SchäfferAlejandroA.Schäffer <20>e)Han La PoutréHanLaPoutré"<22>d+Ramana M. IduryRamanaM.Idury<1D>c%
Amihood AmirAmihoodAmir+<2B>b3
!Emmanuel Lopez-NeriEmmanuelLopez-Neri:<3A>aC-J. Octavio Gutierrez-GarciaJ.OctavioGutierrez-Garcia!<21>`)
Heather MillerHeatherMiller!<21>_)
Philipp HallerPhilippHaller(<28>^1Wolfgang De MeuterWolfgangDeMeuter#<23>]+
Stijn MostinckxStijnMostinckx <20>\)Tom Van CutsemTomVanCutsem2<6D>[;Andoni Lombide CarretonAndoniLombideCarreton/<2F>Z7
%Engineer BainomugishaEngineerBainomugisha<1F>Y'
Raouf BoutabaRaoufBoutaba)<29>X1
Mosharaf ChowdhuryMosharafChowdhury0<79>W9Gerth Stølting BrodalGerthStøltingBrodal!<21>V)
Frank PiessensFrankPiessens<1F>U'
Adriaan MoorsAdriaanMoors!<21>T)
Martin OderskyMartinOdersky<19>S!
Ingo MaierIngoMaier<<3C>RE#Proofreader Jennifer McclainProofreaderJenniferMcclain!<21>Q)
!Ken DellapentaKenDellapenta<1F>P'
Emilia ThiuriEmiliaThiuri,<2C>O5Denise E. M. PenroseDeniseE. M.Penrose <20>N)David W. CorneDavidW.Corne
g
,kg
_<02>I1OGGOptimal Purely Functional Priority Queues<07>Brodal recently introduced the rst implementation of imperative priority queues to support ndMin, insert, and meld in O(1) worst-case time, and deleteMin in O(log n) worst-case time. These bounds are asymptotically optimal among all comparison-based priority queues. In this paper, we adapt Brodal's data structure to a purely functional setting. In doing so, we both simplify the data structure and clarify its relationship to the binomial queues of Vuillemin, which support all four operations in O(log n) time. Speciically, we derive our implementation from binomial queues in three steps: rst, we reduce the running time of insert to O(1) by eliminating the possibility of cascading links; second, we reduce the running time of ndMin to O(1) by adding a global root to hold the minimum element; and nally, we reduce the running time of meld to O(1) by allowing priority queues to contain other priority queues. Each of these steps is expressed using ML-style functors. The last transformation, known as data-structural bootstrapping, is an interesting application of higher-order functors and recursive structures.J. Funct. Program.paradigms/functional_programming/2017-09-11T23:07:15.6236459962017-09-11T23:07:15.623645996<EFBFBD>.<2E>
e<02>G
OEETowards Equal Rights for Higher-kinded Types<07>Generics are a very popular feature of contemporary OO languages, such as Java, C# or Scala. Their support for genericity is lacking, however. The problem is that they only support abstracting over proper types, and not over generic types. This limitation makes it impossible to, e.g., define a precise interface for Iterable, a core abstraction in Scala's collection API. We implemented " type constructor polymorphism " in Scala 2.5, which solves this problem at the root, thus greatly reducing the duplication of type signatures and code.paradigms/functional_programming/2017-09-11T23:07:15.551142092017-09-11T23:07:15.55114209<EFBFBD><0B>

o<02>uAGGPrediction in Joint Action: What, When, and Where<07>Drawing on recent findings in the cognitive and neurosciences, this article discusses how people manage to predict each other's actions, which is fundamental for joint action. We explore how a common coding of perceived and performed actions may allow actors to predict the what, when, and where of others' actions. The "what" aspect refers to predictions about the kind of action the other will perform and to the intention that drives the action. The "when" aspect is critical for all joint actions requiring close temporal coordination. The "where" aspect is important for the online coordination of actions because actors need to effectively distribute a common space. We argue that although common coding of perceived and performed actions alone is not sufficient to enable one to engage in joint action, it provides a representational platform for integrating the actions of self and other. The final part of the paper considers links between lower-level processes like action simulation and higher-level processes like verbal communication and mental state attribution that have previously been at the focus of joint action research.topiCSorganizational_simulation/2017-09-11T23:07:14.9426201172017-09-11T23:07:14.942620117<EFBFBD>P<EFBFBD>
M<02>

aGGDeprecating the Observer Pattern<07>Programming interactive systems by means of the observer pattern is hard and error-prone yet is still the implementation standard in many production environments. We present an approach to gradually deprecate observers in favor of re-active programming abstractions. Several library layers help programmers to smoothly migrate existing code from call-backs to a more declarative programming model. Our central high-level API layer embeds an extensible higher-order data-flow DSL into our host language. This embedding is enabled by a continuation passing style transformation.paradigms/functional_reactive_programming/2017-09-11T23:07:14.2838349612017-09-11T23:07:14.283834961
M
jpK<0C>jFp
<EFBFBD>	{<00><02>*]<5D>7<>GG
<01>9b8aec8ef5c67da463f5ec7c174570eb7d1643a8epitaxis-a-system-for-syntactic-and-semantic-software-queries.pdfprogram_verification/epitaxis a system for syntactic and semantic software queries2017-09-11T23:06:14.0409360352017-09-11T23:06:14.040936035<EFBFBD>Y<EFBFBD>&	]yqGG<00>7de4f6fddb11254d1fd5f8adfd67b6e0c9439eaathe-derivative-of-a-regular-type-one-hole-contexts.pdfplt/the derivative of a regular type one hole contexts2017-09-11T23:06:13.8456379392017-09-11T23:06:13.845637939	<09>#	]g_GGdd0854bf535d79d51104ae<61>%<25>,	]71/GG
<01>23c425f022baa054c68683eaf81f5d482915ce13grovers_algorithm.pdfquantum_computing/grovers algorithm2017-09-11T23:06:14.1639909672017-09-11T23:06:14.163990967<EFBFBD>.<2E>.	]IAGG
<01>67ea9f0fe38b6848de19578589eab498473562c3ids-evasion-ptacek-newsham.pdfsecurity/ids evasion ptacek newsham2017-09-11T23:06:14.2006989752017-09-11T23:06:14.200698975
<0A><00>	]31+GG703d0b290a4ece50c17854ed72ecc808ce3e6f43shors_algorithm.pdfquantum_computing/shors algorithm2017-09-11T23:06:14.1694089362017-09-11T23:06:14.169408936
<0A><00>	]71/GG23c425f022baa054c68683eaf81f5d482915ce<63>!<21>-	]31+GG
<01>703d0b290a4ece50c17854ed72ecc808ce3e6f43shors_algorithm.pdfquantum_computing/shors algorithm2017-09-11T23:06:14.1694089362017-09-11T23:06:14.169408936<EFBFBD>I<EFBFBD>+	][1SGG
<01>239ff60210c28900f866c588f40e974d897a9f62advance_in_quantum_machine_learning.pdfquantum_computing/advance in quantum machine learning2017-09-11T23:06:14.0655710452017-09-11T23:06:14.065571045<EFBFBD>K<EFBFBD>(	]e!]GG<00>d0d8b7501d7f75613d5493d706d6d81852a73d6ecommunicating-sequential-processes-paper.pdfprocesses/communicating sequential processes paper2017-09-11T23:06:13.9075610352017-09-11T23:06:13.907561035<EFBFBD>?<3F>)	]Y!QGG<00>614d66c63f8a04cf24cf19ce885f6a34be56a67ccommunicating-sequential-processes.pdfprocesses/communicating sequential processes2017-09-11T23:06:13.9905249022017-09-11T23:06:13.990524902<00>	]e!]GGd0d8b7501d7f75613d5493d706d6d81852a73d6ecommunicating-sequential-processes-paper.pdfprocesses/communicating sequential processes paper2017-09-11T23:06:13.9075610352017-09-11T23:06:13.907561035<EFBFBD>/<2F>'	]Q<>L<EFBFBD>/	]g_GG
<01>dd0854bf535d79d51104ae3d5c19c6ac7e562180macaroons-cookies-with-contextual-caveats.pdfsecurity/macaroons cookies with contextual caveats2017-09-11T23:06:14.4265568852017-09-11T23:06:14.426556885<EFBFBD>1<EFBFBD>'	]QIGG<00>e437aad09eb0508f015c4615e3a9c738bdee9fdftheory-in-programming-practice.pdfplt/theory in programming practice2017-09-11T23:06:13.8512170412017-09-11T23:06:13.851217041

fM
f
Q<02>-!OGGWhy Functional Programming Matters<07>As software becomes more and more complex, it is more and more important to structure it well. Well-structured software is easy to write, easy to debug, and provides a collection of modules that can be re-used to reduce future programming costs. Conventional languages place conceptual limits on the way problems can be modularised. Functional languages push those limits back. In this paper we show that two features of functional languages in particular, higher-order functions and lazy evaluation, can contribute greatly to modularity. As examples, we manipulate lists and trees, program several numerical algorithms, and implement the alpha-beta heuristic an algorithm from Artiicial Intelligence used in game-playing programs. Since modularity is the key to successful programming, functional languages are vitally important to the real world.Comput. J.paradigms/functional_programming/2017-09-11T23:07:15.9188330082017-09-11T23:07:15.918833008<EFBFBD>/<2F>
Q<02>%/aGGA survey of network virtualization<07>Due to the existence of multiple stakeholders with conflicting goals and policies, alterations to the existing Internet architecture are now limited to simple incremental updates; deployment of any new, radically different technology is next to impossible. To fend off this ossification, network virtualization has been propounded as a diversifying attribute of the future inter-networking paradigm. By introducing a plurality of heterogeneous network architectures cohabiting on a shared physical substrate, network virtualization promotes innovations and diversified applications. In this paper, we survey the existing technologies and a wide array of past and state-of-the-art projects on network virtualization followed by a discussion of major challenges in this area. The Internet has been stunningly successful over the course of past three decades in supporting multitude of distributed applications and a wide variety of network technologies. However, its popularity has become the biggest impediment to its further growth. Due to its multi-provider nature, adopting a new architecture or modification of the existing one requires consensus among competing stakeholders. As a result, alterations to the Internet architecture have become restricted to simple incremental updates and deployment of new network technologies have become increasingly difficult [1,2]. To fend off this ossification, network virtualization has been propounded as a diversifying attribute of the future inter-networking paradigm. Even though architectural purists view network virtualization as a means for evaluating new architectures, the pluralist approach considers vir-tualization as a fundamental attribute of the architecture itself [1]. They believe that network virtualization can eradicate the ossifying forces of the Internet and stimulate innovation [1,2]. A networking environment supports network virtual-ization if it allows coexistence of multiple virtual networks on the same physical substrate. Each virtual network (VN) in a network virtualization environment (NVE) is a collection of virtual nodes and virtual links. Essentially, a virtual network is a subset of the underlying physical network resources. Network virtualization proposes decoupling of func-tionalities in a networking environment by separating the role of the traditional Internet Service Providers (ISPs) into two: infrastructure providers (InPs), who manage the physical infrastructure, and service providers (SPs), who create 1389-1286/$-see front matter Ó 2009 Elsevier B.V. All rights reserved.Computer Networksparadigms/functional_reactive_programming/2017-09-11T23:07:15.6554838872017-09-11T23:07:15.655483887

<01>

<01><00>#<23>
G<02>1aGGFunctional Reactive Animation<07><i>Fran</i> (Functional Reactive Animation) is a collection of data types and functions for composing richly interactive, multimedia animations. The key ideas in Fran are its notions of <i>behaviors</i> and <i>events</i>. Behaviors are time-varying, reactive values, while events are sets of arbitrarily complex conditions, carrying possibly rich information. Most traditional values can be treated as behaviors, and when images are thus treated, they become animations. Although these notions are captured as data types rather than a programming language, we provide them with a denotational semantics, including a proper treatment of real time, to guide reasoning and implementation. A method to effectively and efficiently perform <i>event detection</i> using <i>interval analysis</i> is also described, which relies on the partial information structure on the domain of event times. Fran has been implemented in Hugs, yielding surprisingly good performance for an interpreter-based system. Several examples are given, including the ability to describe physical phenomena involving gravity, springs, velocity, acceleration, etc. using ordinary differential equations.ICFPparadigms/functional_reactive_programming/2017-09-11T23:07:16.2409208982017-09-11T23:07:16.240920898<EFBFBD>q<EFBFBD><00><02>
aGGRAY: Integrating Rx and Async for Direct-Style Reactive Streams<07>Languages like F#, C#, and recently also Scala, provide “async” extensions which aim to make asynchronous programming easier by avoiding an inversion of control that is inherent in traditional callback-based programming models (for the purpose of this paper called the “Async” model). This paper outlines a novel approach to integrate the Async model with observable streams of the Reactive Extensions model which is best-known from the .NET platform, and of which popular implementations exist for Java, Ruby, and other widespread languages. We outline the translation of “Reactive Async” programs to efficient state machines, in a way that generalizes the state machine translation of regular Async programs. Finally, we sketch a formalization of the Reactive Async model in terms of a small-step operational semantics.paradigms/functional_reactive_programming/2017-09-11T23:07:16.2144780272017-09-11T23:07:16.214478027<EFBFBD>z<EFBFBD>
M<02>?/aGGA survey on reactive programming<07>Reactive programming has recently gained popularity as a paradigm that is well-suited for developing event-driven and interactive applications. It facilitates the development of such applications by providing abstractions to express time-varying values and automatically managing dependencies between such values. A number of approaches have been recently proposed embedded in various languages such as Haskell, Scheme, JavaScript, Java, .NET, etc. This survey describes and provides a taxonomy of existing reactive programming approaches along six axes: representation of time-varying values, evaluation model, lifting operations, multidirectionality, glitch avoidance, and support for distribution. From this taxonomy, we observe that there are still open challenges in the field of reactive programming. For instance, multidirectionality is supported only by a small number of languages, which do not automatically track dependencies between time-varying values. Similarly, glitch avoidance, which is subtle in reactive programs, cannot be ensured in distributed reactive programs using the current techniques.ACM Comput. Surv.paradigms/functional_reactive_programming/2017-09-11T23:07:16.0977639162017-09-11T23:07:16.097763916
$#<0F><0F>K<0E><0E>O|N#
<0A>
<0A>
<0A>
<0A>
Y
3<0C><0C><0C>V<0B>V"
<EFBFBD>
<EFBFBD>
O
"	<09>	<09>	y	Q	.	<08>y+YInductive Supervised Quantum Learning.
<01>)UImproved Dynamic Dictionary Matching
<01>C<04>Making Programs Forget: Enforcing Lifetime for Sensitive Data<00>H<04>
MEXICA: A computer model of a cognitive account of creative writing'S
MDCC: Multi-Data Center Consistency]"GLooking Inside the (Drop) Box<00>'QLive Migration of Virtual Machines
|D<04>
Linearizability: A Correctness Condition for Concurrent Objectsj*WLinear work suffix array construction<00>8u
Lightweight Locking for Main Memory Database SystemsR,]
Light Propagation Volumes in Cryengine 3+A<04>Life beyond Distributed Transactions: an Apostate's Opinion
O6q
Large-scale cluster management at Google with BorgiY<04>3Large-scale Incremental Processing Using Distributed Transactions and Notifications
Q3iLarge-Scale Newscast Computing on the Internet<00>Z<04>7
KinectFusion: real-time 3D reconstruction and interaction using a moving depth camera&g<04>OKelips: Building an Efficient and Stable P2P DHT through Increased Memory and Background Overhead
M<}
Kafka: a Distributed Messaging System for Log Processingg4kJoint action: bodies and minds moving together.<00>)UJails: Confining the Omnipotent Root<00>=}IronFleet: proving practical distributed systems correct<00>?<04>

Introduction to a System for Distributed Databases (SDD-1)\%MIntroduction to Cryptocurrencies
1*WInternet Security Glossary, Version 2<00>A
Interactive topic modelingC
Interactive Horizon Mapping,5
Instant architecture0+YInformation-based models for ad hoc IR<00>E<04>Incremental Mature Garbage Collection Using the Train Algorithm<00>-]Incremental Collection of Mature Objects<00>7qIn Search of an Understandable Consensus Algorithm
PD<04>	Impossibility of Distributed Consensus with One Faulty Process
LQ<04>#Implementing the Omega failure detector in the crash-recovery failure model
KV<04>/
Implementing Fault-Tolerant Services Using the State Machine Approach: A Tutoriall#K
Immutability Changes EverythingH9w
Imaging vector fields using line integral convolution1
D<0B>D

7<02>c
GGBuridan’s Principle<07>The problem of Buridan's Ass, named after the fourteenth century French philosopher Jean Buridan, states that an ass placed equidistant between two bales of hay must starve to death because it has no reason to choose one bale over the other. With the benefit of modern mathematics, the argument can be expressed as follows. Assume that, at time 0, the ass is placed at position x along the line joining the bales of hay, where one bale is at position 0 and the other at position 1, so 0 < x < 1. The position of the ass at time t > 0 is a function of two arguments: the time t and the starting position x. Let A t (x) denote that position. For simplicity, assume that when the ass reaches a bale of hay it stays there forever, so for all t ≥ 0: A t (0) = 0, A t (1) = 1, and 0 ≤ A t (x) ≤ 1 for any x with 0 < x < 1. The ass is a physical mechanism subject to the laws of physics. Any such mechanism is continuous, so A t (x) is a continuous function of x. Since A t (0) = 0 and A t (1) = 1, by continuity there must be a finite range of values of x for which 0 < A t (x) < 1. These values represent initial positions of the ass for which it does not reach either bale of hay within t seconds. Such a range of values of x exists for any time t, including times large enough to insure that the ass has starved to death by then. Thus, there exists a finite range of starting positions for which the ass starves to death. The key assumption in this argument is continuity: the ass's position at a later time is a continuous function of its initial position. Continuity has been a guiding principle in the development of modern physics. Phenomena that appear discontinuous, such as discrete atomic spectral lines, are explained in terms of continuous physical laws, such as Schroedinger's equation. The assumption of continuity is discussed at length in Section 6. For now, let us accept it and investigate its consequences. The general principle underlying the starvation of Buridan's ass can be stated as follows: Buridan's Principle. A discrete decision based upon an input having a …physics/2017-09-11T23:07:16.4403339842017-09-11T23:07:16.440333984<EFBFBD>&<26>	<00>
<02>i<EFBFBD>==GGCognitive Computing: A Brief Survey and Open Research Challenges<07>Cognitive computing is a multidisciplinary field of research aiming at devising computational models and decision making mechanisms based on the neurobiological processes of the brain, cognitive sciences, and psychology. The objective of cognitive computational models is to endow computer systems with the faculties of knowing, thinking, and feeling. The major contributions of this survey include (i) giving insights into cognitive computing by listing and describing its definitions, related fields, and terms, (ii) classifying current research on cognitive computing according to its objectives, (iii) presenting a concise review of cognitive computing approaches, and (iv) identifying the open research issues in the area of cognitive computing.2015 3rd International Conference on Applied Computing and Information Technology/2nd International Conference on Computational Science and Intelligenceparadigms/new_paradigms/2017-09-11T23:07:16.3658630372017-09-11T23:07:16.365863037
#)#
e<02>
GGQuantum vacuum pressure on a conducting slab<07>The casimir pressure on a non ideal conducting slab is calculated. Using a simple model for the conductivity according to which the slab is perfectly conducting at frequencies below plasma frequency ω p and perfectly transparent above such frequency, it is found that the vacuum pressure on each surface of the slab is ¯ hω 4 p 24π 2 c 3 which is finite without removal of any divergence.physics/2017-09-11T23:07:16.5467939452017-09-11T23:07:16.546793945<EFBFBD>S<EFBFBD>
U<02>%%/GGImproved Dynamic Dictionary Matching<07>1 Introduction In the dynamic dictionary matching problem, a dictionary D contains a set of patterns that can change over time by insertion and deletion of individual patterns. The user also presents text strings and asks for all occurrences of any patterns in the text. The two main contributions of this paper are: 1) A faster algorithm for dynamic string dictionary matching with bounded alphabets, and 2) A dynamic dictionary matching algorithm for two dimensional texts and square patterns. The first contribution is based on an algorithm that solves the general problem of maintaining a sequence of well-balanced parentheses under the operations insert, delete, and find nearest enclosing parenthesis pair. The main ideas behind the second contribution are: a linearization of two dimensional square patterns along the main diagonal, and new data structures to allow efficient manipulation of failure links. The classical pattern matching paradigm is that of searching for a given pattern in a given text. For example, the classical string matching problem is defined This is one of the most studied problems in computer science [16] and has many different linear time solutions (e.g., [lo, 191 d an many others). The two dimensional version of this problem in which strings of symbols are replaced with matrices is also well studied [9, 8, 21. Another paradigm is that of multiple matching. The input is a set of patterns D and a text. The object is to find all occurrences of all patterns from D that appear in the text. A motivation for this paradigm was given by Aho and Corasick [l]. They solved a bibliographic search problem for a set of words. Aho and Corasick gave an O((t + d) loga + tocc) time algorithm (AC for short) for the multiple string matching problem, where the text is of length t, the sum of all pattern lengths is d, the total number of pattern occurrences reported is tom, and u is the number of distinct characters that occur in D. It will always be the case that d 1 u, so terms depending on 0 are sometimes omitted. Recently there has been interest in a stronger paradigm, that of (dynamic) dictionary matching. Like multiple matching, we seek all appearances of any of a set of patterns (the dictionary) in an input text. The difference between dictionary matching and multiple matching is that the dictionary matching paradigm assumes a very …Inf. Comput.pattern_matching/2017-09-11T23:07:16.4534851072017-09-11T23:07:16.453485107

	<09>	<09>
c<02>A-/GGThe extensible neuroimaging archive toolkit<07>The Extensible Neuroimaging Archive Toolkit (XNAT) is a software platform designed to facilitate common management and productivity tasks for neuroimaging and associated data. In particular, XNAT enables qualitycontrol procedures and provides secure access to and storage of data. XNAT follows a threetiered architecture that includes a data archive, user interface, and middleware engine. Data can be entered into the archive as XML or through data entry forms. Newly added data are stored in a virtual quarantine until an authorized user has validated it. XNAT subsequently maintains a history profile to track all changes made to the managed data. User access to the archive is provided by a secure web application. The web application provides a number of quality control and productivity features, including data entry forms, data-type-specific searches, searches that combine across data types, detailed reports, and listings of experimental data, upload/download tools, access to standard laboratory workflows, and administration and security tools. XNAT also includes an online image viewer that supports a number of common neuroimaging formats, including DICOM and Analyze. The viewer can be extended to support additional formats and to generate custom displays. By managing data with XNAT, laboratories are prepared to better maintain the long-term integrity of their data, to explore emergent relations across data types, and to share their data with the broader neuroimaging community.Neuroinformaticspattern_matching/2017-09-11T23:07:16.5706931152017-09-11T23:07:16.570693115
I<03>I<00><EFBFBD>
k<02>]IGGProgramming with algebraic effects and handlers<07>Eff is a programming language based on the algebraic approach to computational effects, in which effects are viewed as algebraic operations and effect handlers as homomorphisms from free algebras. Eff supports first-class effects and handlers through which we may easily define new computational effects, seamlessly combine existing ones, and handle them in novel ways. We give a de-notational semantics of eff and discuss a prototype implementation based on it. Through examples we demonstrate how the standard effects are treated in eff , and how eff supports programming techniques that use various forms of delimited continuations , such as backtracking, breadth-first search, selection functionals, cooperative multi-threading, and others.J. Log. Algebr. Meth. Program.plt/2017-09-11T23:07:16.6977609862017-09-11T23:07:16.697760986<EFBFBD>H<EFBFBD>
G<02>1/GGWarnings for pattern matching<07>We examine the ML pattern-matching anomalies of useless clauses and non-exhaustive matches. We state the definition of these anomalies, building upon pattern matching semantics, and propose a simple algorithm to detect them. We have integrated the algorithm in the Objective Caml compiler, but we show that the same algorithm is also usable in a non-strict language such as Haskell. Or-patterns are considered for both strict and nonstrict languages.J. Funct. Program.pattern_matching/2017-09-11T23:07:16.6593391112017-09-11T23:07:16.659339111<EFBFBD>d<EFBFBD>
[<02>k
GGOn the Electrodynamics of Moving Bodies<07>It is known that Maxwell's electrodynamics—as usually understood at the present time—when applied to moving bodies, leads to asymmetries which do not appear to be inherent in the phenomena. Take, for example, the reciprocal electrodynamic action of a magnet and a conductor. The observable phenomenon here depends only on the relative motion of the conductor and the magnet, whereas the customary view draws a sharp distinction between the two cases in which either the one or the other of these bodies is in motion. For if the magnet is in motion and the conductor at rest, there arises in the neighbourhood of the magnet an electric field with a certain definite energy, producing a current at the places where parts of the conductor are situated. But if the magnet is stationary and the conductor in motion, no electric field arises in the neighbourhood of the magnet. In the conductor, however, we find an electro-motive force, to which in itself there is no corresponding energy, but which gives rise—assuming equality of relative motion in the two cases discussed—to electric currents of the same path and intensity as those produced by the electric forces in the former case. Examples of this sort, together with the unsuccessful attempts to discover any motion of the earth relatively to the " light medium, " suggest that the phenomena of electrodynamics as well as of mechanics possess no properties corresponding to the idea of absolute rest. They suggest rather that, as has already been shown to the first order of small quantities, the same laws of electrodynamics and optics will be valid for all frames of reference for which the equations of mechanics hold good. 1 We will raise this conjecture (the purport of which will hereafter be called the " Principle of Relativity ") to the status of a postulate, and also introduce another postulate, which is only apparently irreconcilable with the former, namely, that light is always propagated in empty space with a definite velocity c which is independent of the state of motion of the emitting body. These two postulates suffice for the attainment of a simple and consistent theory of the electrodynamics of moving bodies based on Maxwell's theory for stationary bodies. The introduction of a " luminiferous ether " will prove to be superfluous inasmuch as the view here to be developed will not require an " absolutely stationary space " …physics/2017-09-11T23:07:16.6133530272017-09-11T23:07:16.613353027
#Hr	<09>#
W<02>-GGDistributed Authorization in Vanadium<07>In this tutorial, we present an authorization model for distributed systems that operate with limited internet connectivity. Reliable internet access remains a luxury for a majority of the world's population. Even for those who can afford it, a dependence on internet connectivity may lead to sub-optimal user experiences. With a focus on decentralized deployment, we present an authorization model that is suitable for scenarios where devices right next to each other (such as a sensor or a friend's phone) should be able to communicate securely in a peer-to-peer manner. The model has been deployed as part of an open-source distributed application framework called Vanadium. As part of this tuto-rial, we survey some of the key ideas and techniques used in distributed authorization, and explain how they are combined in the design of our model.FOSADsecurity/2017-09-11T23:07:16.9136679692017-09-11T23:07:16.913667969<EFBFBD>~<7E>
Y<02>_;1GGInductive Supervised Quantum Learning.<07>In supervised learning, an inductive learning algorithm extracts general rules from observed training instances, then the rules are applied to test instances. We show that this splitting of training and application arises naturally, in the classical setting, from a simple independence requirement with a physical interpretation of being nonsignaling. Thus, two seemingly different definitions of inductive learning happen to coincide. This follows from the properties of classical information that break down in the quantum setup. We prove a quantum de Finetti theorem for quantum channels, which shows that in the quantum case, the equivalence holds in the asymptotic setting, that is, for large numbers of test instances. This reveals a natural analogy between classical learning protocols and their quantum counterparts, justifying a similar treatment, and allowing us to inquire about standard elements in computational learning theory, such as structural risk minimization and sample complexity.Physical review lettersquantum_computing/2017-09-11T23:07:16.8275400392017-09-11T23:07:16.827540039<EFBFBD>R<EFBFBD>
7<02>]#GGPropositions as types<07>Connecting mathematical logic and computation, it ensures that some aspects of programming are absolute.Commun. ACMplt/2017-09-11T23:07:16.8005581052017-09-11T23:07:16.800558105<EFBFBD>4<EFBFBD>
<00>G

7CCDai-depur: an Integrated Supervisory Multi-level Architecture for Wastewater Treatment Plants<07>program_verification/2017-09-11T23:07:16.75822292017-09-11T23:07:16.7582229
<05>	{
<05>~<7E>	7
11GGChaotic bat algorithm<07>J. Comput. Sciencequantum_computing/2017-09-11T23:07:17.1452050782017-09-11T23:07:17.145205078<EFBFBD>m<EFBFBD>
E<02>=O1GGThe Solovay-Kitaev algorithm<07>This pedagogical review presents the proof of the Solovay-Kitaev theorem in the form of an efficient classical algorithm for compiling an arbitrary single-qubit gate into a sequence of gates from a fixed and finite set. The algorithm can be used, for example, to compile Shor's algorithm, which uses rotations of π/2 k , into an efficient fault-tolerant form using only Hadamard, controlled-not, and π/8 gates. The algorithm runs in O(log 2.71 (1/ǫ)) time, and produces as output a sequence of O(log 3.97 (1/ǫ)) quantum gates which is guaranteed to approximate the desired quantum gate to an accuracy within ǫ > 0. We also explain how the algorithm can be generalized to apply to multi-qubit gates and to gates from SU (d).Quantum Information & Computationquantum_computing/2017-09-11T23:07:17.0607380372017-09-11T23:07:17.060738037<EFBFBD>
<01>
W<02>[YGGDefending against network IDS evasion<07>ICSI as a Senior Scientist. Most of his work is in the areas of scalable multimedia conferencing systems, reliable multicast protocols, multicast routing and address allocation, and network simulation and visualisation. He is co-chair of the IETF Multiparty Multimedia Session Control working group and the IRTF Reliable Multicast Research Group. When attempting to build sound network intrusion detection systems, a major problem is hardening the monitor against "evasion": attempts by attackers to mislead the monitor as to the actual state of the end-to-end dialog between the attacker and its victim [Ptacek and Newsham 98, Paxson 98]. Evasion techniques include sending traffic that is ambiguous from the monitor's observational vantage point (such as whether a given packet has sufficient TTL to reach the victim) and attempting to overwhelm the monitor by clogging it with more connection state records than it can sustain ("state holding" attacks). One technique for preventing certain forms of evasion attacks is "bifurcating analysis", in which the monitor deals with ambiguous traffic streams by instantiating separate analysis threads for each possible interpretation of the ambiguous traffic. We discuss the applicability of this approach to different forms of evasion, with the key distinction being tractable analysis for cases where the number of analysis threads can be bounded, versus problematic analysis for cases where the attacker can cause the number of threads to grow arbitrarily large.Recent Advances in Intrusion Detectionsecurity/2017-09-11T23:07:17.0341101072017-09-11T23:07:17.034110107
	$!<00><0C>
W<02>_S7GGUnderstanding RFID Counting Protocols<07>Counting the number of radio frequency identification (RFID) tags, namely <i>RFID counting</i>, is needed by a wide array of important wireless applications. Motivated by its paramount practical importance, researchers have developed an impressive arsenal of techniques to improve the performance of RFID counting (i.e., to reduce the time needed to do the counting). This paper aims to gain deeper and fundamental insights in this subject to facilitate future research on this topic. As our central thesis, we find out that the overlooked key design aspect for RFID counting protocols to achieve near-optimal performance is a conceptual separation of a protocol into two phases. The first phase uses small overhead to obtain a rough estimate, and the second phase uses the rough estimate to further achieve an accuracy target. Our thesis also indicates that other performance-enhancing techniques or ideas proposed in the literature are only of secondary importance. Guided by our central thesis, we manage to design near-optimal protocols that are more efficient than existing ones and simultaneously simpler than most of them.IEEE/ACM Transactions on Networkingsublinear_algorithms/2017-09-11T23:07:17.3100600592017-09-11T23:07:17.310060059<EFBFBD><EFBFBD>
<00>]

/GGFaculty of Associated Medical Sciences 1. Anterior Translation of Humeral Head in Glenohumeral Joint: Comparison between Limb Dominance and Gender Using Ultrasonography<07>sports_analytics/2017-09-11T23:07:17.2479541022017-09-11T23:07:17.247954102<EFBFBD>X<EFBFBD>
A<02>cGGSoK: Eternal War in Memory<07>Memory corruption bugs in software written in low-level languages like C or C++ are one of the oldest problems in computer security. The lack of safety in these languages allows attackers to alter the program's behavior or take full control over it by hijacking its control flow. This problem has existed for more than 30 years and a vast number of potential solutions have been proposed, yet memory corruption attacks continue to pose a serious threat. Real world exploits show that all currently deployed protections can be defeated. This paper sheds light on the primary reasons for this by describing attacks that succeed on today's systems. We systematize the current knowledge about various protection techniques by setting up a general model for memory corruption attacks. Using this model we show what policies can stop which attacks. The model identifies weaknesses of currently deployed techniques, as well as other proposed protections enforcing stricter policies. We analyze the reasons why protection mechanisms implementing stricter polices are not deployed. To achieve wide adoption, protection mechanisms must support a multitude of features and must satisfy a host of requirements. Especially important is performance, as experience shows that only solutions whose overhead is in reasonable bounds get deployed. A comparison of different enforceable policies helps designers of new protection mechanisms in finding the balance between effectiveness (security) and efficiency. We identify some open research problems, and provide suggestions on improving the adoption of newer techniques.2013 IEEE Symposium on Security and Privacysecurity/2017-09-11T23:07:17.1880610352017-09-11T23:07:17.188061035
_<0F><0F><0F><0F><0F><0F><0F><0F>vm_
<EFBFBD>genomic
<EFBFBD>
isoform<0E>#cardinality<0F>%near-optimal<11>~)rough estimate<11>})number of tags<0B>|counting
<EFBFBD>{defense


-
-<00>O<EFBFBD>
o<02>y9%GGASAP: the Alternative Splicing Annotation Project<07>Recently, genomics analyses have demonstrated that alternative splicing is widespread in mammalian genomes (30-60% of genes reported to have multiple isoforms), and may be one of their most important mechanisms of functional regulation. However, by comparison with other genomics data such as genome annotation, SNPs, or gene expression, there exists relatively little database infrastructure for the study of alternative splicing. We have constructed an online database ASAP (the Alternative Splicing Annotation Project) for biologists to access and mine the enormous wealth of alternative splicing information coming from genomics and proteomics. ASAP is based on genome-wide analyses of alternative splicing in human (30 793 alternative splice relationships found) from detailed alignment of expressed sequences onto the genomic sequence. ASAP provides precise gene exon-intron structure, alternative splicing, tissue specificity of alternative splice forms, and protein isoform sequences resulting from alternative splicing. Moreover, it can help biologists design probe sequences for distinguishing specific mRNA isoforms. ASAP is intended to be a community resource for collaborative annotation of alternative splice forms, their regulation, and biological functions. The URL for ASAP is http://www.bioinformatics.ucla.edu/ASAP.Nucleic Acids Researchtime_series/2017-09-11T23:07:17.6160830082017-09-11T23:07:17.616083008
<03>0<0E>
<0A><0C>,<0B>
<EFBFBD>	a<08><07>8<06><05>Fd<03><00>$<24>2	ec!GGhttp://www.people.hbs.edu/jlerner/simple.pdfThe Simple economics of Open Source  (2000)economics/2018-02-26T06:25:07.2366660162018-02-26T06:25:07.236666016<EFBFBD>^<5E>1
<00>[_!GGhttp://www.mit.edu/~dbertsim/papers/Revenue%20Management/Optimal%20Bidding%20in%20Online%20Auctions.pdfOptimal Bidding in Online Auctions (2001)economics/2018-02-26T06:25:07.2366660162018-02-26T06:25:07.236666016<EFBFBD>%<25>0
7<>GGhttps://osf.io/6qzxc/Datacenter Traffic Control: Understanding Techniques and Trade-offsnetworks/2018-02-03T06:25:06.7749499512018-02-03T06:25:06.774949951<EFBFBD><18>/	i35GGhttp://affect.media.mit.edu/pdfs/95.picard.pdfAffective Computingaffective-computing/2018-02-02T06:25:06.9577280272018-02-02T06:25:06.957728027<EFBFBD>)<29>.	W}GGhttps://spectreattack.com/spectre.pdfSpectre Attacks: Exploiting Speculative Execution (2018)security/2018-01-30T06:25:06.6858959962018-01-30T06:25:06.685895996<EFBFBD><02>-	[+GGhttps://meltdownattack.com/meltdown.pdfMeltdown (2018)security/2018-01-30T06:25:06.6858959962018-01-30T06:25:06.685895996<EFBFBD>c<EFBFBD>,
<00>?q5GGhttps://irenelopatovska.files.wordpress.com/2012/10/lopatovska_arapakis_2011_theories.pdfTheories, Methods and Current Research on Emotionsaffective-computing/2018-01-30T06:25:06.6698339842018-01-30T06:25:06.669833984<EFBFBD>8<EFBFBD>+
U<>/GGhttp://dreammachin.es/p1-wallace.pdfMultiple Narrative Disentanglement: Unraveling *Infinite Jest*machine_learning/2018-01-21T06:25:06.4233610842018-01-21T06:25:06.423361084<EFBFBD><03>*<00><13>k%GGhttps://github.com/tpn/pdfs/raw/master/Realizing%20Quality%20Improvement%20Through%20Test%20Driven%20Development%20-%20Results%20and%20Experiences%20of%20Four%20Industrial%20Teams%20(nagappan_tddRealizing quality improvement through test driven development: results and experiences of four industrial teamstesting/tdd/2018-01-12T06:25:06.6559199222018-01-12T06:25:06.655919922<EFBFBD>(<28>)	Qu+GGhttps://github.com/marsyas/marsyas[C++] Marsyas open source audio processing frameworkaudio_comp_sci/2017-10-27T05:25:06.4915878912017-10-27T05:25:06.491587891<EFBFBD><14>(	KS+GGhttps://github.com/MTG/essentia[C++] Essential open source libraryaudio_comp_sci/2017-10-26T05:25:06.0193911132017-10-26T05:25:06.019391113<EFBFBD><1F>'	}11GGhttp://web.cecs.pdx.edu/~mpj/pubs/composing-fractals.pdfComposing Fractalslanguages/haskell/2017-10-25T05:25:06.5538200682017-10-25T05:25:06.553820068<EFBFBD>><3E>&
<00>
o+GGhttps://github.com/adamstark/Chord-Detector-and-Chromagram[C++] Implementation of real time chord detectionaudio_comp_sci/2017-10-25T05:25:06.5452949222017-10-25T05:25:06.545294922<EFBFBD>u<EFBFBD>%<00>C<EFBFBD>%GGhttps://www.tk.informatik.tu-darmstadt.de/fileadmin/user_upload/Group_TK/zhou2010survey.pdfA survey of coordinated attacks and collaborative intrusion detection (2010)security/2017-10-24T05:25:06.0431608892017-10-24T05:25:06.043160889<EFBFBD>"<22>$
<00>
11GGhttp://homepages.inf.ed.ac.uk/slindley/papers/handlers.pdfHandlers In Actionlanguages/haskell/2017-10-21T05:25:06.0342170412017-10-21T05:25:06.034217041<EFBFBD>L<EFBFBD>#
<00>g1GGhttps://people.cs.kuleuven.be/~tom.schrijvers/Research/papers/mpc2015.pdfFusion for Free: Efficient Algebraic Handlerslanguages/haskell/2017-10-21T05:25:06.0342170412017-10-21T05:25:06.034217041