Conflict driven learning in a quantified Boolean Satisfiability solver
Within the verification community, there has been a recent increase in interest in Quantified Boolean Formula evaluation (QBF) as many interesting sequential circuit verification problems can be formulated as QBF instances. A closely related research area to QBF is Boolean Satisfiability (SAT). Rece...
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| Veröffentlicht in: | Digest of technical papers - IEEE/ACM International Conference on Computer-Aided Design S. 442 - 449 |
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New York, NY, USA
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10.11.2002
IEEE |
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| ISBN: | 0780376072, 9780780376076 |
| ISSN: | 1092-3152 |
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| Abstract | Within the verification community, there has been a recent increase in interest in Quantified Boolean Formula evaluation (QBF) as many interesting sequential circuit verification problems can be formulated as QBF instances. A closely related research area to QBF is Boolean Satisfiability (SAT). Recent advances in SAT research have resulted in some very efficient SAT solvers. One of the critical techniques employed in these solvers is Conflict Driven Learning. In this paper, we adapt conflict driven learning for application in a QBF setting. We show that conflict driven learning can be regarded as a resolution process on the clauses. We prove that under certain conditions, tautology clauses obtained from resolution in QBF also obey the rules for implication and conflicts of regular (non-tautology) clauses; and therefore they can be treated as regular clauses and used in future search. We have implemented this idea in a new QBF solver called Quaffle and our initial experiments show that conflict driven learning can greatly speed up the solution process for most of the benchmarks we tested. |
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| AbstractList | Within the verification community, there has been a recent increase in interest in Quantified Boolean Formula evaluation (QBF) as many interesting sequential circuit verification problems can be formulated as QBF instances. A closely related research area to QBF is Boolean Satisfiability (SAT). Recent advances in SAT research have resulted in some very efficient SAT solvers. One of the critical techniques employed in these solvers is Conflict Driven Learning. In this paper, we adapt conflict driven learning for application in a QBF setting. We show that conflict driven learning can be regarded as a resolution process on the clauses. We prove that under certain conditions, tautology clauses obtained from resolution in QBF also obey the rules for implication and conflicts of regular (non-tautology) clauses; and therefore they can be treated as regular clauses and used in future search. We have implemented this idea in a new QBF solver called Quaffle and our initial experiments show that conflict driven learning can greatly speed up the solution process for most of the benchmarks we tested. |
| Author | Zhang, Lintao Malik, Sharad |
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| Keywords | Learning Sequential circuit Circuit design Test Constraint satisfaction Computer aided design Satisfiability |
| Language | English |
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| SubjectTerms | Applied sciences Computing methodologies -- Symbolic and algebraic manipulation Computing methodologies -- Symbolic and algebraic manipulation -- Symbolic and algebraic algorithms Design. Technologies. Operation analysis. Testing Electronics Exact sciences and technology Hardware -- Hardware validation -- Functional verification Hardware -- Integrated circuits -- Logic circuits -- Sequential circuits Integrated circuits Semiconductor electronics. Microelectronics. Optoelectronics. Solid state devices Testing, measurement, noise and reliability Theory of computation -- Design and analysis of algorithms |
| Title | Conflict driven learning in a quantified Boolean Satisfiability solver |
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