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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)
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)
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)
In recent days, the complexity of software has increased significantly in embedded products in such a way that the verification of Embedded Software (ESW) now plays an important role to ensure the product's quality. Embedded systems engineers usually face the problems of verifying properties that have to meet the application's deadline, access the memory(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)
Many decision and optimization problems in Electronic Design Automation (EDA) can be solved with Boolean Satisfiability (SAT). Moreover, well-known extensions of SAT also find application in EDA, including Pseudo-Boolean Optimization, Quantified Boolean Formulas, Multi-Valued SAT and, more recently, Maximum Satisfiability (MaxSAT). Algorithms for MaxSAT are(More)
One of the main topics of research in genomics is determining the relevance of mutations, described in haplotype data, as causes of some genetic diseases. However, due to technological limitations, genotype data rather than haplotype data is usually obtained. The haplotype inference by pure parsimony (HIPP) problem consists in inferring haplotypes from(More)