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ÐThis paper introduces GRASP (Generic seaRch Algorithm for the Satisfiability Problem), a new search algorithm for Propositional Satisfiability (SAT). GRASP incorporates several search-pruning techniques that proved to be quite powerful on a wide variety of SAT problems. Some of these techniques are specific to SAT, whereas others are similar in spirit to(More)
One of the main reasons for the widespread use of SAT in many applications is that Conflict-Driven Clause Learning (CDCL) Boolean Satisfiability (SAT) solvers are so effective in practice. Since their inception in the mid-90s, CDCL SAT solvers have been applied, in many cases with remarkable success, to a number of practical applications. Examples of(More)
We propose two novel approaches for using Counterexample-Guided Abstraction Refinement (CEGAR) in Quantified Boolean Formula (QBF) solvers. The first approach develops a recursive algorithm whose search is driven by CEGAR (rather than by DPLL). The second approach employs CEGAR as an additional learning technique in an existing DPLL-based QBF solver.(More)
Propositional bounded model checking has been applied successfully to verify embedded software but is limited by the increasing propositional formula size and the loss of structure during the translation. These limitations can be reduced by encoding word-level information in theories richer than propositional logic and using SMT solvers for the generated(More)
This paper addresses the interaction between randomization, with restart strategies, and learning, an often crucial technique for proving unsatisfiability. We use instances of SAT from the hardware verification domain to provide evidence that randomization can indeed be essential in solving real-world satisfiable instances of SAT. More interestingly , our(More)
A set of constraints that cannot be simultaneously satisfied is over-constrained. Minimal relaxations and minimal explanations for over-constrained problems find many practical uses. For Boolean formulas, minimal relaxations of over-constrained problems are referred to as Minimal Correction Subsets (MCSes). MCSes find many applications, including the(More)
In recent years several highly effective algorithms have been proposed for Automatic Test Pattern Generation (ATPG). Nevertheless, most of these algorithms too often rely on different types of heuristics to achieve good empirical performance. Moreover there has not been significant research work on developing algorithms that are robust, in the sense that(More)
The Pseudo-Boolean Optimization (PBO) and Maximum Satisfiability (MaxSAT) problems are natural optimization extensions of Boolean Satisfiability (SAT). In the recent past, different algorithms have been proposed for PBO and for MaxSAT, despite the existence of straightforward mappings from PBO to MaxSAT and vice-versa. This papers proposes Weighted Boolean(More)