sharpSAT – counting models with advanced component caching and implicit BCP. We introduce sharpSAT, a new #SAT solver that is based on the well known DPLL algorithm and techniques from SAT and #SAT solvers. Most importantly, we introduce an entirely new approach of coding components, which reduces the cache size by at least one order of magnitude, and a new cache management scheme. Furthermore, we apply a well known look ahead based on BCP in a manner that is well suited for #SAT solving. We show that these techniques are highly beneficial, especially on large structured instances, such that our solver performs significantly better than other #SAT solvers.
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References in zbMATH (referenced in 9 articles )
Showing results 1 to 9 of 9.
- Lagniez, Jean-Marie; Marquis, Pierre: On preprocessing techniques and their impact on propositional model counting (2017)
- Toda, Takahisa: Dualization of Boolean functions using ternary decision diagrams (2017)
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- Aziz, Rehan Abdul; Chu, Geoffrey; Muise, Christian; Stuckey, Peter: $\#\existsSAT$: projected model counting (2015)
- Wang, Jinyan; Yin, Minghao; Wu, Jingli: Approximate model counting via extension rule (2015)
- Zulkoski, Edward; Ganesh, Vijay; Czarnecki, Krzysztof: MathCheck: a math assistant via a combination of computer algebra systems and SAT solvers (2015)
- Castaño, José M.; Castaño, Rodrigo: A finite state intersection approach to propositional satisfiability (2012)
- Baarir, Souheib; Braunstein, Cécile; Encrenaz, Emmanuelle; Ilié, Jean-Michel; Mounier, Isabelle; Poitrenaud, Denis; Younes, Sana: Feasibility analysis for robustness quantification by symbolic model checking (2011)
- Thurley, Marc: sharpSAT -- counting models with advanced component caching and implicit BCP (2006) ioport