Logic-Based Program Synthesis and Transformation: 22nd International Symposium, LOPSTR 2012, Leuven, Belgium, September 18-20, 2012, Revised Selected Papers

252 Pages·2013·3.312 MB·English

by  Jürgen Giesl, Thomas Ströder (auth.), Elvira Albert (eds.)

Elvira Albert (Ed.)
Logic-Based
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22nd International Symposium, LOPSTR 2012
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Revised Selected Papers
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Elvira Albert (Ed.)
Logic-Based
Program Synthesis
and Transformation
22nd International Symposium, LOPSTR 2012
Leuven, Belgium, September 18-20, 2012
Revised Selected Papers
1 3
VolumeEditor
ElviraAlbert
ComplutenseUniversityofMadrid
DepartmentofComputerScience(DSIC)
SénecaAvenue2
28040Madrid,Spain
E-mail:[email protected]
ISSN0302-9743 e-ISSN1611-3349
ISBN978-3-642-38196-6 e-ISBN978-3-642-38197-3
DOI10.1007/978-3-642-38197-3
SpringerHeidelbergDordrechtLondonNewYork
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CR Subject Classification (1998): D.1.6, D.2.4-5, F.4.1, G.2.2, F.3, I.2.2-4, D.3.1,
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Preface
This volume contains a selection of the papers presented at the 22nd
International Symposium on Logic-Based Program Synthesis and Transforma-
tion (LOPSTR 2012) held during September 18-20, 2012, in Leuven. LOPSTR
2012 was co-located with PPDP 2012, the 14th International ACM SIGPLAN
Symposium on Principles and Practice of Declarative Programming.
PreviousLOPSTR symposia were held in Odense (2011),Hagenberg (2010),
Coimbra (2009), Valencia (2008), Lyngby (2007), Venice (2006 and 1999),
London(2005and2000),Verona(2004),Uppsala(2003),Madrid(2002),Paphos
(2001), Manchester (1998, 1992, and 1991), Leuven (1997), Stockholm (1996),
Arnhem (1995), Pisa (1994), and Louvain-la-Neuve (1993). Information about
the conference can be found at: http://costa.ls.fi.upm.es/lopstr12/.
The aim ofthe LOPSTR seriesis to stimulate and promote internationalre-
searchandcollaborationinlogic-basedprogramdevelopment.LOPSTRtradition-
allysolicitscontributions,inanylanguageparadigm,intheareasofspecification,
synthesis,verification,analysis,optimization,specialization,security,certification,
applicationsandtools,program/modelmanipulation,andtransformationaltech-
niques.LOPSTRhasareputationforbeingalively,friendlyforumforpresenting
anddiscussingworkinprogress.Formalproceedingsareproducedonlyafterthe
symposiumsothatauthorscanincorporatethisfeedbackinthepublishedpapers.
In response to the call for papers, 27 contributions were submitted from 19
different countries. The Program Committee accepted four full papers for im-
mediate inclusion in the formal proceedings, and nine more papers were ac-
cepted after a revision and another round of reviewing. In addition to the
13 contributed papers, this volume includes the abstracts of the invited talks
by two outstanding researchers: one LOPSTR invited talk by Tom Schrijvers
(University of Ghent, Belgium) and a joint PPDP-LOPSTR invited talk by
Ju¨rgen Giesl (RWTH Aachen, Germany).
I wantto thank the ProgramCommittee members, who workeddiligently to
producehigh-qualityreviewsforthesubmittedpapers,aswellasalltheexternal
reviewers involved in the paper selection. I am very grateful the LOPSTR 2012
Conference Co-chairs, Daniel De Schreye and Gerda Janssens, and the local
organizers for the great job they did in preparing the conference. I also thank
Andrei Voronkov for his excellent EasyChair system that automates many of
the tasksinvolvedinchairingaconference.Finally,I gratefullyacknowledgethe
sponsors of LOPSTR: The Association for Logic Programming and Fonds voor
Wetenschappelijk Onderzoek Vlaanderen.
March 2013 Elvira Albert
Organization
Program Committee
Elvira Albert Complutense University of Madrid, Spain
Sergio Antoy Portland State University, USA
Demis Ballis University of Udine, Italy
Henning Christiansen Roskilde University, Denmark
Michael Codish Ben-Gurion University of the Negev, Israel
Danny De Schreye K.U. Leuven, Belgium
Esra Erdem Sabanci University, Istanbul
Maribel Fernandez King’s College London, UK
Carsten Fuhs University College London, UK
John Gallagher Roskilde University, Denmark
Robert Glu¨ck University of Copenhagen, Denmark
Miguel Gomez-Zamalloa Complutense University of Madrid, Spain
R´emy Haemmerl´e Technical University of Madrid, Spain
Geoff Hamilton Dublin City University, Ireland
Reiner H¨ahnle Technical University of Darmstadt, Germany
Gerda Janssens K.U. Leuven, Belgium
Isabella Mastroeni University of Verona, Italy
Kazutaka Matsuda University of Tokyo, Japan
Paulo Moura Universidade da Beira Interior, Portugal
Johan Nordlander Lule˚a University of Technology, Sweden
Andrey Rybalchenko Technische Universita¨t Mu¨nchen, Germany
Kostis Sagonas Uppsala University, Sweden
Francesca Scozzari Universit`a “G. D’Annunzio” di Chieti, Italy
Valerio Senni Universta` di Roma “Tor Vergata”,Italy
German Vidal Technical University of Valencia, Spain
Additional Reviewers
Amtoft, Torben Hentschel, Martin
De Angelis, Emanuele Nigam, Vivek
Fioravanti, Fabio Nogueira, Vitor
Grossniklaus, Michael Riesco, Adrian
Table of Contents
Symbolic Evaluation Graphs and Term Rewriting — A General
Methodology for Analyzing Logic Programs (Abstract) ............... 1
Ju¨rgen Giesl, Thomas Stro¨der, Peter Schneider-Kamp,
Fabian Emmes, and Carsten Fuhs
An Introduction to Search Combinators............................. 2
Tom Schrijvers, Guido Tack, Pieter Wuille, Horst Samulowitz, and
Peter J. Stuckey
A Declarative Pipeline Language for Complex Data Analysis .......... 17
Henning Christiansen, Christian Theil Have, Ole Torp Lassen, and
Matthieu Petit
Semantic Code Clones in Logic Programs ........................... 35
C´eline Dandois and Wim Vanhoof
Specialization with Constrained Generalization for Software Model
Checking ....................................................... 51
Emanuele De Angelis, Fabio Fioravanti, Alberto Pettorossi, and
Maurizio Proietti
Enhancing Declarative Debugging with Loop Expansion and Tree
Compression .................................................... 71
David Insa, Josep Silva, and C´esar Toma´s
XACML 3.0 in Answer Set Programming ........................... 89
Carroline Dewi Puspa Kencana Ramli, Hanne Riis Nielson, and
Flemming Nielson
Types vs. PDGs in Information Flow Analysis ....................... 106
Heiko Mantel and Henning Sudbrock
Galliwasp: A Goal-Directed Answer Set Solver....................... 122
Kyle Marple and Gopal Gupta
Computing More Specific Versions of Conditional Rewriting Systems ... 137
Naoki Nishida and Germa´n Vidal
Improving Determinization of Grammar Programs for Program
Inversion........................................................ 155
Minami Niwa, Naoki Nishida, and Masahiko Sakai
X Table of Contents
A Framework for Guided Test Case Generation in Constraint Logic
Programming.................................................... 176
Jos´e Miguel Rojas and Miguel Go´mez-Zamalloa
Simplifying the Verification of Quantified Array Assertions via Code
Transformation .................................................. 194
Mohamed Nassim Seghir and Martin Brain
Proving Properties of Co-logic Programs with Negation by Program
Transformations ................................................. 213
Hirohisa Seki
ProgramAnalysis and Manipulation to Reproduce Learners’Erroneous
Reasoning....................................................... 228
Claus Zinn
Author Index.................................................. 245
Symbolic Evaluation Graphs
and Term Rewriting — A General Methodology
(cid:2)
for Analyzing Logic Programs
(Abstract)
Ju¨rgen Giesl1, Thomas Stro¨der1, Peter Schneider-Kamp2,
Fabian Emmes1, and Carsten Fuhs3
1 LuFGInformatik 2, RWTH Aachen University,Germany
2 Dept.of Mathematics and Computer Science, Universityof Southern Denmark
3 Dept.of Computer Science, University College London, UK
There existmanypowerful techniques to analyzetermination andcomplexity of
term rewrite systems (TRSs). Our goal is to use these techniques for the anal-
ysis of other programming languages as well. For instance, approaches to prove
termination of definite logic programs by a transformation to TRSs have been
studiedfordecades.However,achallengeistohandlelanguageswithmorecom-
plexevaluationstrategies(suchasProlog,wherepredicateslikethecut influence
the control flow).
We present a general methodology for the analysis of such programs. Here,
the logic program is first transformed into a symbolic evaluation graph which
represents all possible evaluations in a finite way. Afterwards, different analyses
can be performed on these graphs. In particular, one can generate TRSs from
such graphs and apply existing tools for termination or complexity analysis of
TRSs to infer informationonthe termination orcomplexity ofthe originallogic
program.
More information can be found in the full paper [1].
Reference
1. Giesl,J.,Str¨oder,T.,Schneider-Kamp,P.,Emmes,F.,Fuhs,C.:Symbolicevaluation
graphs and term rewriting — a general methodology for analyzing logic programs.
In:Proc. PPDP 2012, pp.1–12. ACM Press (2012)
(cid:2) SupportedbytheDFGundergrant GI274/5-3, theDFGResearch TrainingGroup
1298(AlgoSyn),andtheDanishCouncilforIndependentResearch,NaturalSciences.
E.Albert(Ed.):LOPSTR2012,LNCS7844,p.1,2013.
(cid:2)c Springer-VerlagBerlinHeidelberg2013
An Introduction to Search Combinators
TomSchrijvers1,GuidoTack2,PieterWuille1,3,
HorstSamulowitz4,andPeterJ.Stuckey5
1 UniversiteitGent,Belgium
{tom.schrijvers,pieter.wuille}@ugent.be
2 NationalICTAustralia(NICTA)andMonashUniversity,Victoria,Australia
[email protected]
3 KatholiekeUniversiteitLeuven,Belgium
[email protected]
4 IBMResearch,NewYork,USA
[email protected]
5 NationalICTAustralia(NICTA)andUniversityofMelbourne,Victoria,Australia
[email protected]
Abstract. The ability to model search in a constraint solver can be an essen-
tial asset for solving combinatorial problems. However, existing infrastructure
for defining search heuristics is often inadequate. Either modeling capabilities
are extremely limited or users are faced with a general-purpose programming
languagewhosefeaturesarenottailoredtowardswritingsearchheuristics.Asa
result,majorimprovementsinperformancemayremainunexplored.
This article introduces search combinators, a lightweight and solver-
independentmethodthatbridgesthegapbetweenaconceptuallysimplemodel-
inglanguageforsearch(high-level,functionalandnaturallycompositional)and
anefficientimplementation(low-level,imperativeandhighlynon-modular).By
allowingtheusertodefineapplication-tailoredsearchstrategiesfromasmallset
ofprimitives,searchcombinatorseffectivelyprovidearichdomain-specificlan-
guage(DSL)formodelingsearchtotheuser.Remarkably,thisDSLcomesata
lowimplementationcosttothedeveloperofaconstraintsolver.
1 Introduction
Search heuristics often make all the difference between effectively solving a combi-
natorial problem and utter failure. Heuristics make a search algorithm efficient for a
varietyofreasons,e.g.,incorporationofdomainknowledge,orrandomizationtoavoid
heavy-tailedruntimes.Hence,theabilitytoswiftlydesignsearchheuristicsthataretai-
lored towards a problem domain is essential for performance. This article introduces
search combinators, a versatile, modular, and efficiently implementable language for
expressingsearchheuristics.
1.1 StatusQuo
In CP, much attention has been devoted to facilitating the modeling of combinatorial
problems. A range of high-level modeling languages, such as OPL [1], Comet [2],
E.Albert(Ed.):LOPSTR2012,LNCS7844,pp.2–16,2013.
©Springer-VerlagBerlinHeidelberg2013