Extended Resolution Proofs for Symbolic SAT Solving with Quantification

Toni Jussila, Carsten Sinz, Armin Biere

Research output: Chapter in Book/Report/Conference proceedingConference proceedingspeer-review

Abstract

Symbolic SAT solving is an approach where the clauses of a CNF formula are represented using BDDs. These BDDs are then conjoined, and finally checking satisfiability is reduced to the question of whether the final BDD is identical to false. We present a method combining symbolic SAT solving with BDD quantification (variable elimination) and generation of extended resolution proofs. Proofs are fundamental to many applications, and our results allow the use of BDDs instead of---or in combination with---established proof generation techniques like clause learning. % We have implemented a symbolic SAT solver with variable elimination that produces extended resolution proofs. We present details of our implementation, called EBDDRES, which is an extension of the system presented in [1], and also report on experimental results.
Original languageEnglish
Title of host publicationProc. 9th Intl. Conf. on Theory and Applications of Satisfiability Testing (SAT'06)
PublisherSpringer
Pages54-60
Number of pages7
Volume4121
ISBN (Print)3540372067, 9783540372066
DOIs
Publication statusPublished - 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4121 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Fields of science

  • 102 Computer Sciences

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