HaifaSat: A New Robust SAT Solver
Author(s) -
Roman Gershman,
Ofer Strichman
Publication year - 2006
Publication title -
lecture notes in computer science
Language(s) - English
Resource type - Book series
SCImago Journal Rank - 0.249
H-Index - 400
eISSN - 1611-3349
pISSN - 0302-9743
ISBN - 3-540-32604-9
DOI - 10.1007/11678779_6
Subject(s) - computer science , heuristics , abstraction , solver , heuristic , graph , boolean satisfiability problem , theoretical computer science , function (biology) , programming language , algorithm , artificial intelligence , epistemology , philosophy , evolutionary biology , biology , operating system
The popular abstraction/refinement model frequently used in verification, can also explain the success of a SAT decision heuristic like Berkmin. According to this model, conflict clauses are abstractions of the clauses from which they were derived. We suggest a clause-based decision heuristic called Clause-Move-To-Front (CMTF), which attempts to follow an abstraction/refinement strategy (based on the resolve-graph) rather than satisfying the clauses in the chronological order in which they were created, as done in Berkmin. We also show a resolution-based score function for choosing the variable from the selected clause and a similar function for choosing the sign. We implemented the suggested heuristics in our SAT solver HaifaSat. Experiments on hundreds of industrial benchmarks demonstrate the superiority of this method comparing to the Berkmin heuristic. There is still room for research on how to explore better the resolve-graph information, based on the abstraction/refinement model that we propose.
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