The Configurable SAT Solver Challenge (CSSC)

It is well known that different solution strategies work well for different types of instances of hard combinatorial problems. As a consequence, most solvers for the propositional satisfiability problem (SAT) expose parameters that allow them to be customized to a particular family of instances. In the international SAT competition series, these parameters are ignored: solvers are run using a single default parameter setting (supplied by the authors) for all benchmark instances in a given track. While this competition format rewards solvers with robust default settings, it does not reflect the situation faced by a practitioner who only cares about performance on one particular application and can invest some time into tuning solver parameters for this application. The new Configurable SAT Solver Competition (CSSC) compares solvers in this latter setting, scoring each solver by the performance it achieved after a fully automated configuration step. This article describes the CSSC in more detail, and reports the results obtained in its two instantiations so far, CSSC 2013 and 2014

Proceedings of SAT Competition 2021 : Solver and Benchmark Descriptions

Non peer reviewe

Combining VSIDS and CHB Using Restarts in SAT

Conflict Driven Clause Learning (CDCL) solvers are known to be efficient on structured instances and manage to solve ones with a large number of variables and clauses. An important component in such solvers is the branching heuristic which picks the next variable to branch on. In this paper, we evaluate different strategies which combine two state-of-the-art heuristics, namely the Variable State Independent Decaying Sum (VSIDS) and the Conflict History-Based (CHB) branching heuristic. These strategies take advantage of the restart mechanism, which helps to deal with the heavy-tailed phenomena in SAT, to switch between these heuristics thus ensuring a better and more diverse exploration of the search space. Our experimental evaluation shows that combining VSIDS and CHB using restarts achieves competitive results and even significantly outperforms both heuristics for some chosen strategies