aqua-s2v

Submitter: Paolo Marin
Description: Devised by Paolo Marin, it is a search-based QBF solver for prenex conjunctive normal form (PCNF) formulas. Literal propagation is performed through unit, pure, and don't care literal detection using lazy data structures. For backtracking, a conflict and solution driven constraint learning approach is used. A restart strategy and phase saving are also implemented. This version uses first semantic UIP (S-UIP) learning, 2 literals watching, and VSIDS decision heuristic. The solver is coupled with the QBF preprocessor sQueezeBF, which is given a timeout of 100 seconds.
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