DAC '96 Proceedings of the 33rd annual Design Automation Conference
GRASP—a new search algorithm for satisfiability
Proceedings of the 1996 IEEE/ACM international conference on Computer-aided design
Boosting combinatorial search through randomization
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
A Computing Procedure for Quantification Theory
Journal of the ACM (JACM)
Boolean satisfiability in electronic design automation
Proceedings of the 37th Annual Design Automation Conference
A machine program for theorem-proving
Communications of the ACM
Chaff: engineering an efficient SAT solver
Proceedings of the 38th annual Design Automation Conference
SATO: An Efficient Propositional Prover
CADE-14 Proceedings of the 14th International Conference on Automated Deduction
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: techniques, algorithms and applications
AI Communications
MINIMAXSAT: an efficient weighted max-SAT solver
Journal of Artificial Intelligence Research
MiniMaxSAT: a new weighted Max-SAT solver
SAT'07 Proceedings of the 10th international conference on Theory and applications of satisfiability testing
DPLL+ROBDD Derivation applied to inversion of some cryptographic functions
SAT'11 Proceedings of the 14th international conference on Theory and application of satisfiability testing
Speedup techniques utilized in modern SAT solvers
SAT'05 Proceedings of the 8th international conference on Theory and Applications of Satisfiability Testing
An overview of parallel SAT solving
Constraints
Optimal implementation of watched literals and more general techniques
Journal of Artificial Intelligence Research
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The implementation of efficient Propositional Satisfiability (SAT) solvers entails the utilization of highly efficient data structures, as illustrated by most of the recent state-of-the-art SAT solvers. However, it is in general hard to compare existing data structures, since different solvers are often characterized by fairly different algorithmic organizations and techniques, and by different search strategies and heuristics. This paper aims the evaluation of data structures for backtrack search SAT solvers, under a common unbiased SAT framework. In addition, advantages and drawbacks of each existing data structure are identified. Finally, new data structures are proposed, that are competitive with the most efficient data structures currently available, and that may be preferable for the next generation SAT solvers.