Abstract. Work by Kilby, Slaney, Thiebaux and Walsh [1] showed that the backdoors and backbones of unstructured Random 3SAT instances are largely disjoint. In this work we extend t...
Propositional satisfiability (SAT) is a success story in Computer Science and Artificial Intelligence: SAT solvers are currently used to solve problems in many different applicati...
— Modern SAT solvers have proved highly successful in finding counterexamples to temporal properties of systems, using a method known as ”bounded model checking”. It is natu...
Abstract— Learning is an essential pruning technique in modern SAT solvers, but it exploits a relatively small amount of information that can be deduced from the conflicts. Rece...
Abstract. Polynomial interpretations are one of the most popular techniques for automated termination analysis and the search for such interpretations is a main bottleneck in most ...
Minimizing learned clauses is an effective technique to reduce memory usage and also speed up solving time. It has been implemented in MINISAT since 2005 and is now adopted by mos...
Boolean satisfiability (SAT) solving has become an enabling technology with wide-ranging applications in numerous disciplines. These applications tend to be most naturally encode...
Benjamin Chambers, Panagiotis Manolios, Daron Vroo...
In this work, we improve on existing work that studied the relationship between the proof system of modern SAT solvers and general resolution. Previous contributions such as those ...
Bounded Model Checking (BMC) relies on solving a sequence of highly correlated Boolean satisfiability (SAT) problems, each of which corresponds to the existence of counter-example...
Chao Wang, HoonSang Jin, Gary D. Hachtel, Fabio So...