Experimental results on the application of satisfiability algorithms to scheduling problems
AAAI'94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 2)
Act, and the rest will follow: exploiting determinism in planning as satisfiability
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
A machine program for theorem-proving
Communications of the ACM
Logical Cryptanalysis as a SAT Problem
Journal of Automated Reasoning
Symbolic Model Checking without BDDs
TACAS '99 Proceedings of the 5th International Conference on Tools and Algorithms for Construction and Analysis of Systems
Integrating BDD-Based and SAT-Based Symbolic Model Checking
FroCoS '02 Proceedings of the 4th International Workshop on Frontiers of Combining Systems
Tuning SAT Checkers for Bounded Model Checking
CAV '00 Proceedings of the 12th International Conference on Computer Aided Verification
Benefits of Bounded Model Checking at an Industrial Setting
CAV '01 Proceedings of the 13th International Conference on Computer Aided Verification
NuSMV 2: An OpenSource Tool for Symbolic Model Checking
CAV '02 Proceedings of the 14th International Conference on Computer Aided Verification
Applying the Davis-Putnam Procedure to Non-clausal Formulas
AI*IA '99 Proceedings of the 6th Congress of the Italian Association for Artificial Intelligence on Advances in Artificial Intelligence
Evaluating Search Heuristics and Optimization Techniques in Propositional Satisfiability
IJCAR '01 Proceedings of the First International Joint Conference on 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
Automatic SAT-compilation of planning problems
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
Ten challenges in propositional reasoning and search
IJCAI'97 Proceedings of the 15th international joint conference on Artifical intelligence - Volume 1
Heuristics based on unit propagation for satisfiability problems
IJCAI'97 Proceedings of the 15th international joint conference on Artifical intelligence - Volume 1
A backbone-search heuristic for efficient solving of hard 3-SAT formulae
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Complexity results on DPLL and resolution
ACM Transactions on Computational Logic (TOCL)
Propositional Satisfiability and Constraint Programming: A comparative survey
ACM Computing Surveys (CSUR)
Artificial Intelligence
SAT graph-based representation: A new perspective
Journal of Algorithms
Solving QBF with combined conjunctive and disjunctive normal form
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Towards understanding and harnessing the potential of clause learning
Journal of Artificial Intelligence Research
Circuit based encoding of CNF formula
SAT'07 Proceedings of the 10th international conference on Theory and applications of satisfiability testing
Limitations of restricted branching in clause learning
CP'07 Proceedings of the 13th international conference on Principles and practice of constraint programming
Propelling SAT and SAT-based BMC using careset
Proceedings of the 2010 Conference on Formal Methods in Computer-Aided Design
Effective preprocessing in SAT through variable and clause elimination
SAT'05 Proceedings of the 8th international conference on Theory and Applications of Satisfiability Testing
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Propositional reasoning (SAT) is central in many applications of Computer Science. Several decision procedures for SAT have been proposed, along with optimizations and heuristics to speed them up. Currently, the most effective implementations are based on the Davis, Logemann, Loveland method. In this method, the input formula is represented as a set of clauses, and the space of truth assignments is searched by iteratively assigning a literal until all the clauses are satisfied, or a clause is violated and backtracking occurs. Once a new literal is assigned, pruning techniques (e.g., unit propagation) are used to cut the search space by inferring truth values for other variables.In this paper, we investigate the "independent variable selection (IVS) heuristic", i.e., given a formula on the set of variables N, the selection is restricted to a - possibly small - subset S which is sufficient to determine a truth value for all the variables in N. During the search phase, scoring and selection of the literal to assign next are restricted to S, and the truth values for the remaining variables are determined by the pruning techniques of the solver. We discuss the possible advantages and disadvantages of the IVS heuristic. Our experimental analysis shows that obtaining either positive or negative results strictly depends on the type of problems considered, on the underlying scoring and selection technique, and also on the backtracking scheme.