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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)
Sudoku is a very simple and well-known puzzle that has achieved international popularity in the recent past. This paper addresses the problem of encoding Sudoku puzzles into conjunctive normal form (CNF), and subsequently solving them using polynomial-time propositional satisfiability (SAT) inference techniques. We introduce two straightforward SAT(More)
Certifying a SAT solver for unsatisfiable instances is a computationally hard problem. Nevertheless, in the utilization of SAT in industrial settings, one often needs to be able to generate unsatisfiability proofs, either to guarantee the correctness of the SAT solver or as part of the utilization of SAT in some applications (e.g. in model checking). As(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)
Minimally Unsatisfiable Subformulas (MUS) find a wide range of practical applications, including product configuration, knowledge-based validation, and hardware and software design and verification. MUSes also find application in recent Maximum Satisfiability algorithms and in CNF formula redundancy removal. Besides direct applications in Propositional(More)
Backbones of propositional theories are literals that are true in every model. Backbones have been used for characterizing the hardness of decision and optimization problems. Moreover, backbones find other applications. For example, backbones are often identified during product configuration. Backbones can also improve the efficiency of solving(More)
The last two decades progresses have led Propositional Satisfiability (SAT) to be a competitive practical approach to solve a wide range of industrial and academic problems. Thanks to these advances, the size and difficulty of the SAT instances have grown significantly. The demand for more computational power led to the creation of new computer(More)
Haplotype inference from genotype data is a key computational problem in bioinformatics, since retrieving directly haplotype information from DNA samples is not feasible using existing technology. One of the methods for solving this problem uses the pure parsimony criterion, an approach known as Haplotype Inference by Pure Parsimony (HIPP). Initial work in(More)