Minimizing models for tseitin-encoded SAT instances

Authors:
Markus Iser;Carsten Sinz;Mana Taghdiri
Affiliations:
Karlsruhe Institute of Technology (KIT), Germany;Karlsruhe Institute of Technology (KIT), Germany;Karlsruhe Institute of Technology (KIT), Germany
Venue:
SAT'13 Proceedings of the 16th international conference on Theory and Applications of Satisfiability Testing
Year:
2013

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Abstract

Many applications of SAT solving can profit from minimal models--a partial variable assignment that is still a witness for satisfiability. Examples include software verification, model checking, and counterexample-guided abstraction refinement. In this paper, we examine how a given model can be minimized for SAT instances that have been obtained by Tseitin encoding of a full propositional logic formula. Our approach uses a SAT solver to efficiently minimize a given model, focusing on only the input variables. Experiments show that some models can be reduced by over 50 percent.