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Chaff: engineering an efficient SAT solver

Chaff: engineering an efficient SAT solver 33.1 &KDII (QJLQHHULQJ DQ (IILFLHQW 6$7 6ROYHU 0DWWKHZ : 0RVNHZLF] 'HSDUWPHQW RI ((&6 8& %HUNHOH\ &RQRU ) 0DGLJDQ 'HSDUWPHQW RI ((&6 0,7 FPDGLJDQ#PLWHGX <LQJ =KDR /LQWDR =KDQJ 6KDUDG 0DOLN 'HSDUWPHQW RI (OHFWULFDO (QJLQHHULQJ 3ULQFHWRQ 8QLYHUVLW\ PRVNHZF]#DOXPQLSULQFHWRQHGX ^\LQJ]KDR OLQWDR] VKDUDG`#HHSULQFHWRQHGX developed, most employing some combination of two main strategies: the Davis-Putnam (DP) backtrack search and heuristic local search. Heuristic local search techniques are not guaranteed to be complete (i.e. they are not guaranteed to find a satisfying assignment if one exists or prove unsatisfiability); as a result, complete SAT solvers (including ours) are based almost exclusively on the DP search algorithm. ABSTRACT 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 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Chaff: engineering an efficient SAT solver

Association for Computing Machinery — Jun 22, 2001

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References (108)

Datasource
Association for Computing Machinery
Copyright
Copyright © 2001 by ACM Inc.
ISBN
1-58113-297-2
doi
10.1145/378239.379017
Publisher site
See Article on Publisher Site

Abstract

33.1 &KDII (QJLQHHULQJ DQ (IILFLHQW 6$7 6ROYHU 0DWWKHZ : 0RVNHZLF] 'HSDUWPHQW RI ((&6 8& %HUNHOH\ &RQRU ) 0DGLJDQ 'HSDUWPHQW RI ((&6 0,7 FPDGLJDQ#PLWHGX <LQJ =KDR /LQWDR =KDQJ 6KDUDG 0DOLN 'HSDUWPHQW RI (OHFWULFDO (QJLQHHULQJ 3ULQFHWRQ 8QLYHUVLW\ PRVNHZF]#DOXPQLSULQFHWRQHGX ^\LQJ]KDR OLQWDR] VKDUDG`#HHSULQFHWRQHGX developed, most employing some combination of two main strategies: the Davis-Putnam (DP) backtrack search and heuristic local search. Heuristic local search techniques are not guaranteed to be complete (i.e. they are not guaranteed to find a satisfying assignment if one exists or prove unsatisfiability); as a result, complete SAT solvers (including ours) are based almost exclusively on the DP search algorithm. ABSTRACT 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

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