Decision heuristic for Davis Putnam, Loveland and Logemann algorithm satisfiability solving based on cube subtraction

This paper proposes a new decision heuristic for Davis Putnam, Loveland and Logemann algorithm (DPLL)-based satisfiability (SAT) solvers based on cube subtraction. Each negated clause is viewed as a cube in the n-dimensional Boolean search space denoting a subspace where no satisfying assignments ca...

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Bibliographic Details
Published inIET computers & digital techniques Vol. 2; no. 1; pp. 30 - 39
Main Authors ZUIM, R, DE SOUSA, J. T, COELHO, C. N
Format Journal Article
LanguageEnglish
Published Stevenage Institution of Engineering and Technology 01.01.2008
John Wiley & Sons, Inc
Subjects
Algorithms
Applied sciences
Boolean algebra
Cubes
Design. Technologies. Operation analysis. Testing
Electronics
Exact sciences and technology
Heuristic
Integrated circuits
Integrated circuits by function (including memories and processors)
Microprocessors
Searching
Semiconductor electronics. Microelectronics. Optoelectronics. Solid state devices
Solvers
Subtraction
Learning
Performance evaluation
Integrated circuit
Heuristic method
Subspace method
Microprocessor
Algorithm
Satisfiability
Execution time
Formal verification
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Summary:This paper proposes a new decision heuristic for Davis Putnam, Loveland and Logemann algorithm (DPLL)-based satisfiability (SAT) solvers based on cube subtraction. Each negated clause is viewed as a cube in the n-dimensional Boolean search space denoting a subspace where no satisfying assignments can be found. Cube subtraction systematically subtracts all clause-cubes from the universal cube that represents the entire n-dimensional Boolean search space. If the result is an empty cube then the problem is unsatisfiable; else the problem is satisfiable. This algorithm can be implemented by modifying the decision engine of a DPLL-based SAT solver. The test suite includes 1,252 instances from the DIMACs, IBM-CNF bounded model checking and microprocessor formal verification benchmarks. The significant improvements in execution time and number of timed-out instances have been observed in all cases. Given the breadth of the experimental evaluation, the disjoint cube subtraction search is claimed to be an effective algorithm for improving the performance of SAT solvers.
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ISSN:1751-8601
1751-861X
DOI:10.1049/iet-cdt:20060233