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Boolean Satisfiability is probably the most studied of combinatorial optimization/search problems. Significant effort has been devoted to trying to provide practical solutions to this problem for problem instances encountered in a range of applications in Electronic Design Automation (EDA), as well as in Artificial Intelligence (AI). This study has(More)
One of the most important features of current state-of-the-art SAT solvers is the use of conflict based backtracking and learning techniques. In this paper, we generalize various conflict driven learning strategies in terms of different partitioning schemes of the implication graph. We re-examine the learning techniques used in various SAT solvers and(More)
As the use of SAT solvers as core engines in EDA applications grows, it becomes increasingly important to validate their correctness. In this paper, we describe the implementation of an independent resolution-based checking procedure that can check the validity of unsatisfiable claims produced by the SAT solver zchaff. We examine the practical(More)
MODIST is the first model checker designed for transparently checking unmodified distributed systems running on unmodified operating systems. It achieves this transparency via a novel architecture: a thin interposition layer exposes all actions in a distributed system and a centralized, OS-independent model checking engine explores these actions(More)
Within the verification community, there has been a recent increase in interest in Quantified Boolean Formula evaluation (QBF) as many interesting sequential circuit verification problems can be formulated as QBF instances. A closely related research area to QBF is Boolean Satisfiability (SAT). Recent advances in SAT research have resulted in some very(More)
— Peer-to-peer (P2P) worms exploit common vul-nerabilities in member hosts of a P2P network and spread topologically in the P2P network, a potentially more effective strategy than random scanning for locating victims. This paper describes the danger posed by P2P worms and initiates the study of possible mitigation mechanisms. In particular, the paper(More)
Propositional Satisfiability (SAT) and Constraint Programming (CP) have developed as two relatively independent threads of research cross-fertilizing occasionally. These two approaches to problem solving have a lot in common as evidenced by similar ideas underlying the branch and prune algorithms that are most successful at solving both kinds of problems.(More)