Enhancement schemes for constraint processing: backjumping, learning, and cutset decomposition
Artificial Intelligence
GRASP—a new search algorithm for satisfiability
Proceedings of the 1996 IEEE/ACM international conference on Computer-aided design
A Computing Procedure for Quantification Theory
Journal of the ACM (JACM)
A machine program for theorem-proving
Communications of the ACM
Chaff: engineering an efficient SAT solver
Proceedings of the 38th annual Design Automation Conference
An Overview of Backtrack Search Satisfiability Algorithms
Annals of Mathematics and Artificial Intelligence
SATO: An Efficient Propositional Prover
CADE-14 Proceedings of the 14th International Conference on Automated Deduction
BerkMin: A Fast and Robust Sat-Solver
Proceedings of the conference on Design, automation and test in Europe
Performance measurement and analysis of certain search algorithms.
Performance measurement and analysis of certain search algorithms.
Conflict-directed backjumping revisited
Journal of Artificial Intelligence Research
Domain filtering can degrade intelligent backtracking search
IJCAI'93 Proceedings of the 13th international joint conference on Artifical intelligence - Volume 1
Domain-independent extensions to GSAT: solving large structured satisfiability problems
IJCAI'93 Proceedings of the 13th international joint conference on Artifical intelligence - Volume 1
Using CSP look-back techniques to solve real-world SAT instances
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Propositional Satisfiability and Constraint Programming: A comparative survey
ACM Computing Surveys (CSUR)
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Propositional Satisfiability (SAT) solvers have been the subject of remarkable improvements in the last few years. Currently, the most successful SAT solvers share a number of similarities, being based on backtrack search, applying unit propagation, and incorporating a number of additional search pruning techniques. Most, if not all, of the search reduction techniques used by state-of-the-art SAT solvers have been imported from the Constraint Satisfaction Problem (CSP) domain and, most significantly, include forms of back jumping and of no good recording. This paper proposes to investigate the actual usefulness of these CSP techniques in SAT solvers, with the objective of evaluating the actual role played by each individual technique.