Chaff:engineering an efficient SAT solver. Boolean Satisfiability is probably the most studied of combinatorial optimization/search problems. Significant effort has been devoted to trying to provide practical solutions to this problem for problem instances encountered in a range of applications in Electronic Design Automation (EDA), as well as in Artificial Intelligence (AI). This study has culminated in the development of several SAT packages, both proprietary and in the public domain (e.g. GRASP, SATO) which find significant use in both research and industry. Most existing complete solvers are variants of the Davis-Putnam (DP) search algorithm. In this paper we describe the development of a new complete solver, Chaff, which achieves significant performance gains through careful engineering of all aspects of the search - especially a particularly efficient implementation of Boolean constraint propagation (BCP) and a novel low overhead decision strategy. Chaff has been able to obtain one to two orders of magnitude performance improvement on difficult SAT benchmarks in comparison with other solvers (DP or otherwise), including GRASP and SATO.

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  1. Bonacina, Ilario; Talebanfard, Navid: Strong ETH and resolution via games and the multiplicity of strategies (2017)
  2. Cabodi, G.; Camurati, P.E.; Mishchenko, A.; Palena, M.; Pasini, P.: SAT solver management strategies in IC3: an experimental approach (2017)
  3. Chihani, Zakaria; Marre, Bruno; Bobot, François; Bardin, Sébastien: Sharpening constraint programming approaches for bit-vector theory (2017)
  4. de Nivelle, Hans: Theorem proving for classical logic with partial functions by reduction to Kleene logic (2017)
  5. Hebrard, Emmanuel; Siala, Mohamed: Explanation-based weighted degree (2017)
  6. Jovanović, Dejan: Solving nonlinear integer arithmetic with MCSAT (2017)
  7. Lagniez, Jean-Marie; Marquis, Pierre: On preprocessing techniques and their impact on propositional model counting (2017)
  8. Lammich, Peter: The GRAT tool chain -- efficient (UN)SAT certificate checking with formal correctness guarantees (2017)
  9. Lee, Jimmy H.M.; Zhu, Zichen: Towards breaking more composition symmetries in partial symmetry breaking (2017)
  10. Le Frioux, Ludovic; Baarir, Souheib; Sopena, Julien; Kordon, Fabrice: Painless: a framework for parallel SAT solving (2017)
  11. Lindauer, Marius; Hoos, Holger; Leyton-Brown, Kevin; Schaub, Torsten: Automatic construction of parallel portfolios via algorithm configuration (2017)
  12. Nightingale, Peter; Akgün, Özgür; Gent, Ian P.; Jefferson, Christopher; Miguel, Ian; Spracklen, Patrick: Automatically improving constraint models in Savile row (2017)
  13. Steinmetz, Marcel; Hoffmann, Jörg: State space search nogood learning: online refinement of critical-path dead-end detectors in planning (2017)
  14. Thimm, Matthias; Villata, Serena: The first international competition on computational models of argumentation: results and analysis (2017)
  15. Atserias, Albert; Lauria, Massimo; Nordström, Jakob: Narrow proofs may be maximally long (2016)
  16. Audemard, Gilles; Simon, Laurent: Extreme cases in SAT problems (2016)
  17. Balyo, Tomáš; Biere, Armin; Iser, Markus; Sinz, Carsten: SAT race 2015 (2016)
  18. Beame, Paul; Beck, Chris; Impagliazzo, Russell: Time-space trade-offs in resolution: superpolynomial lower bounds for superlinear space (2016)
  19. Blanchette, Jasmin Christian; Fleury, Mathias; Weidenbach, Christoph: A verified SAT solver framework with learn, forget, restart, and incrementality (2016)
  20. Bonacina, Maria Paola; Plaisted, David A.: Semantically-guided goal-sensitive reasoning: model representation (2016)

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