HaifaSat: A new robust SAT solver 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.
References in zbMATH (referenced in 4 articles , 1 standard article )
Showing results 1 to 4 of 4.
- Liang, Jia Hui; Ganesh, Vijay; Poupart, Pascal; Czarnecki, Krzysztof: Learning rate based branching heuristic for SAT solvers (2016)
- Biere, Armin; Fröhlich, Andreas: Evaluating CDCL variable scoring schemes (2015)
- Gershman, Roman; Strichman, Ofer: HaifaSat: a SAT solver based on an abstraction/refinement model (2009)
- Gershman, Roman; Strichman, Ofer: \ssfHaifaSat: A new robust SAT solver (2006)