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Query-guided maximum satisfiability

Authors:

Aditya V. Nori,

Mayur NaikAuthors Info & Claims

POPL '16: Proceedings of the 43rd Annual ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages

Pages 109 - 122

https://doi.org/10.1145/2837614.2837658

Published: 11 January 2016 Publication History

Abstract

We propose a new optimization problem "Q-MaxSAT", an extension of the well-known Maximum Satisfiability or MaxSAT problem. In contrast to MaxSAT, which aims to find an assignment to all variables in the formula, Q-MaxSAT computes an assignment to a desired subset of variables (or queries) in the formula. Indeed, many problems in diverse domains such as program reasoning, information retrieval, and mathematical optimization can be naturally encoded as Q-MaxSAT instances. We describe an iterative algorithm for solving Q-MaxSAT. In each iteration, the algorithm solves a subproblem that is relevant to the queries, and applies a novel technique to check whether the partial assignment found is a solution to the Q-MaxSAT problem. If the check fails, the algorithm grows the subproblem with a new set of clauses identified as relevant to the queries. Our empirical evaluation shows that our Q-MaxSAT solver Pilot achieves significant improvements in runtime and memory consumption over conventional MaxSAT solvers on several Q-MaxSAT instances generated from real-world problems in program analysis and information retrieval.

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Cited By

Zhang XSi XNaik MShpeisman TGottschlich J(2017)Combining the logical and the probabilistic in program analysisProceedings of the 1st ACM SIGPLAN International Workshop on Machine Learning and Programming Languages10.1145/3088525.3088563(27-34)Online publication date: 18-Jun-2017
https://dl.acm.org/doi/10.1145/3088525.3088563
Si XZhang XGrigore RNaik M(2017)Maximum Satisfiability in Software Analysis: Applications and TechniquesComputer Aided Verification10.1007/978-3-319-63387-9_4(68-94)Online publication date: 13-Jul-2017
https://doi.org/10.1007/978-3-319-63387-9_4
Si XZhang XManquinho VJanota MIgnatiev ANaik M(2016)On Incremental Core-Guided MaxSAT SolvingPrinciples and Practice of Constraint Programming10.1007/978-3-319-44953-1_30(473-482)Online publication date: 23-Aug-2016
https://doi.org/10.1007/978-3-319-44953-1_30

Index Terms

Query-guided maximum satisfiability
1. Mathematics of computing
  1. Mathematical analysis
    1. Mathematical optimization
2. Theory of computation
  1. Design and analysis of algorithms
    1. Mathematical optimization

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cover image ACM Conferences

POPL '16: Proceedings of the 43rd Annual ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages

January 2016

815 pages

ISBN:9781450335492

DOI:10.1145/2837614

General Chair:
Rastislav Bodik
UC Berkeley, USA
,
Program Chair:
Rupak Majumdar
MPI-SWS, Germany

ACM SIGPLAN Notices Volume 51, Issue 1
POPL '16
January 2016
815 pages
ISSN:0362-1340
EISSN:1558-1160
DOI:10.1145/2914770
Editor:
Andy Gill
University of Kansas, Lawrence, KS
Issue’s Table of Contents

Copyright © 2016 ACM.

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Published: 11 January 2016

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January 20 - 22, 2016

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Cited By

Zhang XSi XNaik MShpeisman TGottschlich J(2017)Combining the logical and the probabilistic in program analysisProceedings of the 1st ACM SIGPLAN International Workshop on Machine Learning and Programming Languages10.1145/3088525.3088563(27-34)Online publication date: 18-Jun-2017
https://dl.acm.org/doi/10.1145/3088525.3088563
Si XZhang XGrigore RNaik M(2017)Maximum Satisfiability in Software Analysis: Applications and TechniquesComputer Aided Verification10.1007/978-3-319-63387-9_4(68-94)Online publication date: 13-Jul-2017
https://doi.org/10.1007/978-3-319-63387-9_4
Si XZhang XManquinho VJanota MIgnatiev ANaik M(2016)On Incremental Core-Guided MaxSAT SolvingPrinciples and Practice of Constraint Programming10.1007/978-3-319-44953-1_30(473-482)Online publication date: 23-Aug-2016
https://doi.org/10.1007/978-3-319-44953-1_30

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