Proceedings of the conference on Design, automation and test in Europe - Volume 1
Comparison of schemes for encoding unobservability in translation to SAT
Proceedings of the 2005 Asia and South Pacific Design Automation Conference
Propositional satisfiability: techniques, algorithms and applications
AI Communications
MINIMAXSAT: an efficient weighted max-SAT solver
Journal of Artificial Intelligence Research
On Modern Clause-Learning Satisfiability Solvers
Journal of Automated Reasoning
MiniMaxSAT: a new weighted Max-SAT solver
SAT'07 Proceedings of the 10th international conference on Theory and applications of satisfiability testing
Failed literal detection for QBF
SAT'11 Proceedings of the 14th international conference on Theory and application of satisfiability testing
Effective preprocessing in SAT through variable and clause elimination
SAT'05 Proceedings of the 8th international conference on Theory and Applications of Satisfiability Testing
Optimizations for compiling declarative models into boolean formulas
SAT'05 Proceedings of the 8th international conference on Theory and Applications of Satisfiability Testing
Coprocessor 2.0: a flexible CNF simplifier
SAT'12 Proceedings of the 15th international conference on Theory and Applications of Satisfiability Testing
Augmenting clause learning with implied literals
SAT'12 Proceedings of the 15th international conference on Theory and Applications of Satisfiability Testing
Soundness of inprocessing in clause sharing SAT solvers
SAT'13 Proceedings of the 16th international conference on Theory and Applications of Satisfiability Testing
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Preprocessing is an often used approach for solving hard instances of propositional satisfiability (SAT). Preprocessing can be used for reducing the number of variables and for drastically modifying the set of clauses, either by eliminating irrelevant clauses or by inferring new clauses. Over the years, a large number of formula manipulation techniques has been proposed, that in some situations have allowed solving instances not otherwise solvable with state-of-the-art SAT solvers. This paper proposes probing-based preprocessing, an integrated approach for preprocessing propositional formulas, that for the first time integrates in a single algorithm most of the existing formula manipulation techniques. Moreover, the new unified framework can be used to develop new techniques. Preliminary experimental results illustrate that probing-based preprocessing can be effectively used as a preprocessing tool instate-of-the-art SAT solvers.