Journal of the ACM (JACM)
ECAI '92 Proceedings of the 10th European conference on Artificial intelligence
Fast planning through planning graph analysis
Artificial Intelligence
Chaff: engineering an efficient SAT solver
Proceedings of the 38th annual Design Automation Conference
Solving difficult SAT instances in the presence of symmetry
Proceedings of the 39th annual Design Automation Conference
Journal of Symbolic Computation
The complexity of theorem-proving procedures
STOC '71 Proceedings of the third annual ACM symposium on Theory of computing
Constraint Processing
Satisfiability and integer programming as complementary tools
Proceedings of the 2004 Asia and South Pacific Design Automation Conference
Optimal and suboptimal singleton arc consistency algorithms
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
CGRASS: a system for transforming constraint satisfaction problems
ERCIM'02/CologNet'02 Proceedings of the 2002 Joint ERCIM/CologNet international conference on Constraint solving and constraint logic programming
Inference-based constraint satisfaction supports explanation
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
HAIFASAT: a new robust SAT solver
HVC'05 Proceedings of the First Haifa international conference on Hardware and Software Verification and Testing
A new FPGA detailed routing approach via search-based Boolean satisfiability
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
A Global Filtration for Satisfying Goals in Mutual Exclusion Networks
Recent Advances in Constraints
Solving difficult SAT problems by using OBDDs and greedy clique decomposition
FAW-AAIM'12 Proceedings of the 6th international Frontiers in Algorithmics, and Proceedings of the 8th international conference on Algorithmic Aspects in Information and Management
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We are dealing with solving difficult SAT instances in this paper. We propose a method for preprocessing SAT instances (CNF formulas) by using consistency techniques known from constraint programming methodology and by using our own consistency technique based on clique decomposition of a graph representing conflicts in the input formula. If the clique decomposition is of a good quality (cliques are appropriately large) it then allows us to make a strong reasoning over the SAT instance, which can in some cases even decide the satisfiability of the SAT instance without search. We implemented our preprocessing method in C++ and compared it with several state-of-the-art SAT solvers on selected difficult SAT instances. The result was a speedup in the order of magnitude compared to the tested SAT solvers.