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Conference papers

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

Jasmin Blanchette 1, 2 Mathias Fleury 1, 2 Christoph Weidenbach 1, 2
2 VERIDIS - Modeling and Verification of Distributed Algorithms and Systems
MPII - Max-Planck-Institut für Informatik, Inria Nancy - Grand Est, LORIA - FM - Department of Formal Methods
Abstract : 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.
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Submitted on : Friday, September 22, 2017 - 5:14:37 PM
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Jasmin 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⟩



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