Extending Clause Learning SAT Solvers with Complete Parity Reasoning (extended version)
نویسندگان
چکیده
Instances of logical cryptanalysis, circuit verification, and bounded model checking can often be succinctly represented as a combined satisfiability (SAT) problem where an instance is a combination of traditional clauses and parity constraints. This paper studies how such combined problems can be efficiently solved by augmenting a modern SAT solver with an xor-reasoning module in the DPLL(XOR) framework. A new xorreasoning module that deduces all possible implied literals using incremental Gauss-Jordan elimination is presented. A decomposition technique that can greatly reduce the size of parity constraint matrices while allowing still to deduce all implied literals is presented. It is shown how to eliminate variables occuring only in parity constraints while preserving the decomposition. The proposed techniques are evaluated experimentally.
منابع مشابه
Extending Sat Solver with Parity Constraints
Current methods for solving Boolean satisfiability problem (SAT) are scalable enough to solve discrete nonlinear problems involving hundreds of thousands of variables. However, modern SAT solvers scale poorly with problems involving parity constraints (linear equations modulo 2). Gaussian elimination can be used to solve a system of linear equation effectively but it cannot be applied as such w...
متن کاملExtending SAT Solver with Parity Reasoning
Aalto University, P.O. Box 11000, FI-00076 Aalto www.aalto.fi Author Tero Laitinen Name of the doctoral dissertation Extending SAT Solver with Parity Reasoning Publisher School of Science Unit Department of Information and Computer Science Series Aalto University publication series DOCTORAL DISSERTATIONS 177/2014 Field of research Theoretical Computer Science Manuscript submitted 10 September 2...
متن کاملThe long way from CDClL
Current SAT solvers are powerful enough to be used as engines in real applications. Those applications made the success of a special kind of SAT solvers, namely Conflict Driven Clause Learning SAT solvers (CDClL for short), developed initially by Joao Marques Silva with GRASP [8], and popularized by the SAT solver Chaff [9]. Despite SAT being a NP-complete problem in theory, it might look tract...
متن کاملConflict-Driven XOR-Clause Learning (extended version)
Modern conflict-driven clause learning (CDCL) SAT solvers are very good in solving conjunctive normal form (CNF) formulas. However, some application problems involve lots of parity (xor) constraints which are not necessarily efficiently handled if translated into CNF. This paper studies solving CNF formulas augmented with xor-clauses in the DPLL(XOR) framework where a CDCL SAT solver is coupled...
متن کاملA Restriction of Extended Resolution for Clause Learning SAT Solvers
Modern complete SAT solvers almost uniformly implement variations of the clause learning framework introduced by Grasp and Chaff. The success of these solvers has been theoretically explained by showing that the clause learning framework is an implementation of a proof system which is as poweful as resolution. However, exponential lower bounds are known for resolution, which suggests that signi...
متن کامل