Certified MaxSAT Preprocessing
Paper i proceeding, 2024

Building on the progress in Boolean satisfiability (SAT) solving over the last decades, maximum satisfiability (MaxSAT) has become a viable approach for solving NP-hard optimization problems. However, ensuring correctness of MaxSAT solvers has remained a considerable concern. For SAT, this is largely a solved problem thanks to the use of proof logging, meaning that solvers emit machine-verifiable proofs to certify correctness. However, for MaxSAT, proof logging solvers have started being developed only very recently. Moreover, these nascent efforts have only targeted the core solving process, ignoring the preprocessing phase where input problem instances can be substantially reformulated before being passed on to the solver proper. In this work, we demonstrate how pseudo-Boolean proof logging can be used to certify the correctness of a wide range of modern MaxSAT preprocessing techniques. By combining and extending the VeriPB and CakePB tools, we provide formally verified end-to-end proof checking that the input and preprocessed output MaxSAT problem instances have the same optimal value. An extensive evaluation on applied MaxSAT benchmarks shows that our approach is feasible in practice.

preprocessing

proof logging

formally verified proof checking

maximum satisfiability

Författare

Hannes Ihalainen

Helsingin Yliopisto

Andy Oertel

Köpenhamns universitet

Lunds universitet

Yong Kiam Tan

Agency for Science, Technology and Research (A*STAR)

Jeremias Berg

Helsingin Yliopisto

Matti Järvisalo

Helsingin Yliopisto

Magnus Myreen

Chalmers, Data- och informationsteknik, Formella metoder

Jakob Nordström

Lunds universitet

Köpenhamns universitet

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

03029743 (ISSN) 16113349 (eISSN)

Vol. 14739 LNAI 396-418
9783031634970 (ISBN)

12th International Joint Conference on Automated Reasoning, IJCAR 2024
Nancy, France,

Ämneskategorier

Datavetenskap (datalogi)

DOI

10.1007/978-3-031-63498-7_24

Mer information

Senast uppdaterat

2024-08-09