Efficient satisfiability solver

dc.contributor.advisor Ting Zhang
dc.contributor.advisor Wensheng Zhang
dc.contributor.author Jiang, Chuan
dc.contributor.department Computer Science
dc.date 2018-08-11T11:01:42.000
dc.date.accessioned 2020-06-30T02:52:44Z
dc.date.available 2020-06-30T02:52:44Z
dc.date.copyright Wed Jan 01 00:00:00 UTC 2014
dc.date.embargo 2001-01-01
dc.date.issued 2014-01-01
dc.description.abstract <p>The past few decades saw great improvements in the performance of satisfiability (SAT) solvers. In this thesis, we discuss the state-of-the-art techniques used in building an efficient SAT solver. Modern SAT solvers are mainly constituted by the following components: decision heuristics, Boolean constraint propagation, conflict analysis, restart, clause deletion and preprocessing. Various algorithms and implementations in each component will be discussed and analyzed. Then we propose a new backtracking strategy, partial backtracking, which can be easily implemented in SAT solvers. It is essentially an extension of the backtracking strategy used in most SAT solvers. With partial backtracking, the solver consecutively amends the variable assignments instead of discarding them completely so that it does not backtrack as many levels as the classic strategy does after analyzing a conflict. We implemented this strategy in our solver Nigma and the experiments show that the solver benefits from this adjustment.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/etd/13869/
dc.identifier.articleid 4876
dc.identifier.contextkey 5777583
dc.identifier.doi https://doi.org/10.31274/etd-180810-2105
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath etd/13869
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/28056
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/etd/13869/Jiang_iastate_0097M_14035.pdf|||Fri Jan 14 20:02:50 UTC 2022
dc.subject.disciplines Computer Sciences
dc.subject.keywords backtracking
dc.subject.keywords conflict-driven clause learning
dc.subject.keywords satisfiability
dc.title Efficient satisfiability solver
dc.type article
dc.type.genre thesis
dspace.entity.type Publication
relation.isOrgUnitOfPublication f7be4eb9-d1d0-4081-859b-b15cee251456
thesis.degree.level thesis
thesis.degree.name Master of Science
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