Noise strategies for improving local search
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Circuit-based Boolean Reasoning
Proceedings of the 38th annual Design Automation Conference
An adaptive noise mechanism for walkSAT
Eighteenth national conference on Artificial intelligence
Managing Don't Cares in Boolean Satisfiability
Proceedings of the conference on Design, automation and test in Europe - Volume 1
UnitWalk: A New SAT Solver that Uses Local Search Guided by Unit Clause Elimination
Annals of Mathematics and Artificial Intelligence
Discrete Applied Mathematics
Building structure into local search for SAT
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Evidence for invariants in local search
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Robust Boolean reasoning for equivalence checking and functional property verification
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Justification-Based Local Search with Adaptive Noise Strategies
LPAR '08 Proceedings of the 15th International Conference on Logic for Programming, Artificial Intelligence, and Reasoning
Propelling SAT and SAT-based BMC using careset
Proceedings of the 2010 Conference on Formal Methods in Computer-Aided Design
Improved local search for circuit satisfiability
SAT'10 Proceedings of the 13th international conference on Theory and Applications of Satisfiability Testing
Depth-driven circuit-level stochastic local search for SAT
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume One
On the violation of circuits in decomposable negation normal form
AI'12 Proceedings of the 25th Australasian joint conference on Advances in Artificial Intelligence
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While stochastic local search (SLS) techniques are very efficient in solving hard randomly generated propositional satisfiability (SAT) problem instances, a major challenge is to improve SLS on structured problems. Motivated by heuristics applied in complete circuit-level SAT solvers in electronic design automation, we develop novel SLS techniques by harnessing the concept of justification frontiers. This leads to SLS heuristics which concentrate the search into relevant parts of instances, exploit observability don't cares and allow for an early stopping criterion. Experiments with a prototype implementation of the framework presented in this paper show up to a four orders of magnitude decrease in the number of moves on real-world bounded model checking instances when compared to WalkSAT on the standard CNF encodings of the instances.