Handbook of theoretical computer science (vol. A): algorithms and complexity
Handbook of theoretical computer science (vol. A): algorithms and complexity
A hierarchy of tractable satisfiability problems
Information Processing Letters
Backtrack programming techniques
Communications of the ACM
A machine program for theorem-proving
Communications of the ACM
Implementing the Davis–Putnam Method
Journal of Automated Reasoning
Integrating Equivalency Reasoning into Davis-Putnam Procedure
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
The complexity of theorem-proving procedures
STOC '71 Proceedings of the third annual ACM symposium on Theory of computing
CP '02 Proceedings of the 8th International Conference on Principles and Practice of Constraint Programming
Some Dichotomy Theorems for Neural Learning Problems
The Journal of Machine Learning Research
UnitWalk: A New SAT Solver that Uses Local Search Guided by Unit Clause Elimination
Annals of Mathematics and Artificial Intelligence
Annals of Mathematics and Artificial Intelligence
Boolean satisfiability on a graphics processor
Proceedings of the 20th symposium on Great lakes symposium on VLSI
SAT solving with reference points
SAT'10 Proceedings of the 13th international conference on Theory and Applications of Satisfiability Testing
A Threshold for a Polynomial Solution of #2SAT
Fundamenta Informaticae - Latin American Workshop on Logic Languages, Algorithms and New Methods of Reasoning (LANMR)
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Propositional satisfiability (SAT) is a fundamental problem of immense practical importance. While SAT is NP-complete when clauses can contain 3 literals or more, the problem can be solved in linear time when the given formula contains only binary clauses (2SAT). Many complete search algorithms for SAT solving have taken advantage of 2SAT information that occurs in the statement of the problem in order to simplify the solving process, only one that we are aware of uses 2SAT information that arises in the process of the search, as clauses are simplified. There are a number of possibilities for making use of 2SAT information to improve the SAT solving process: maintaining 2SAT satisfiability during search, detecting unit consequences of the 2SAT clauses, and Krom subsumption using 2SAT clauses. In this paper we investigate the tradeoffs of increasing complex 2SAT handling versus the search space reduction and execution time. We give experimental results illustrating that the SAT solver resulting from the best tradeoff is competitive with state of the art Davis-Putnam methods, on hard problems involving a substantial 2SAT component.