Analyzing multiple conflicts in SAT: an experimental evaluation

Unit propagation and conflict analysis are two essential ingredients of CDCL SAT Solving. The order in which unit propagation is computed does not matter when no conflict is found, because it is well known that there exists a unique unit-propagation fixpoint. However, when a conflict is found, current CDCL implementations stop and analyze that concrete conflict, even though other conflicts may exist in the unit-propagation closure. In this experimental evaluation, we report on our experience in modifying this concrete aspect in the CaDiCaL SAT Solver and try to answer the question of whether we can improve the performance of SAT Solvers by the analysis of multiple conflicts.All authors are supported by grant PID2021-122830OB-C43, funded by MCIN/AEI/ 10.13039/501100011033 and by “ERDF: A way of making Europe”Peer ReviewedPostprint (published version

Enumerating Disjoint Partial Models without Blocking Clauses

A basic algorithm for enumerating disjoint propositional models (disjoint AllSAT) is based on adding blocking clauses incrementally, ruling out previously found models. On the one hand, blocking clauses have the potential to reduce the number of generated models exponentially, as they can handle partial models. On the other hand, they need exponential space and slow down unit propagation. We propose a new approach that allows for enumerating disjoint partial models with no need for blocking clauses by integrating: Conflict-Driven Clause-Learning (CDCL), Chronological Backtracking (CB), and methods for shrinking models (Implicant Shrinking). Experiments clearly show the benefits of our novel approach

Proceedings of SAT Competition 2020 : Solver and Benchmark Descriptions

Non peer reviewe

Proceedings of SAT Race 2019 : Solver and Benchmark Descriptions

Non peer reviewe

Efficient local search for Pseudo Boolean Optimization

Algorithms and the Foundations of Software technolog