A Verified SAT Solver Framework with Learn, Forget, Restart, and Incrementality

Jasmin Christian Blanchette (1, 2) , Mathias Fleury (1, 2) , Christoph Weidenbach (1, 2)

1 MPII - Max-Planck-Institut für Informatik
2 VERIDIS - Modeling and Verification of Distributed Algorithms and Systems

We developed a formal framework for SAT solving using the Isabelle/HOL proof assistant. Through a chain of refinements, an abstract CDCL (conflict-driven clause learning) calculus is connected to a SAT solver that always terminates with correct answers. The framework offers a convenient way to prove theorems about the SAT solver and experiment with variants of the calculus. Compared with earlier verifications, the main novelties are the inclusion of the CDCL rules for forget, restart, and incremental solving and the use of refinement.

Domaines: Logique en informatique [cs.LO]

Jasmin Christian Blanchette, Mathias Fleury, Christoph Weidenbach. A Verified SAT Solver Framework with Learn, Forget, Restart, and Incrementality. IJCAI 2017 - 26th International Joint Conference on Artificial Intelligence, Aug 2017, Melbourne, Australia. pp.4786-4790, ⟨10.24963/ijcai.2017/667⟩. ⟨hal-01592164⟩