Efficient theory combination via boolean search
Information and Computation - Special issue: Combining logical systems
New inference rules for Max-SAT
Journal of Artificial Intelligence Research
MINIMAXSAT: an efficient weighted max-SAT solver
Journal of Artificial Intelligence Research
TACAS'08/ETAPS'08 Proceedings of the Theory and practice of software, 14th international conference on Tools and algorithms for the construction and analysis of systems
Computing small unsatisfiable cores in satisfiability modulo theories
Journal of Artificial Intelligence Research
Solving MAXSAT by solving a sequence of simpler SAT instances
CP'11 Proceedings of the 17th international conference on Principles and practice of constraint programming
Splitting on demand in SAT modulo theories
LPAR'06 Proceedings of the 13th international conference on Logic for Programming, Artificial Intelligence, and Reasoning
On SAT modulo theories and optimization problems
SAT'06 Proceedings of the 9th international conference on Theory and Applications of Satisfiability Testing
On solving the partial MAX-SAT problem
SAT'06 Proceedings of the 9th international conference on Theory and Applications of Satisfiability Testing
Satisfiability modulo the theory of costs: foundations and applications
TACAS'10 Proceedings of the 16th international conference on Tools and Algorithms for the Construction and Analysis of Systems
Improvements to core-guided binary search for MaxSAT
SAT'12 Proceedings of the 15th international conference on Theory and Applications of Satisfiability Testing
Optimization in SMT with LA(Q) cost functions
IJCAR'12 Proceedings of the 6th international joint conference on Automated Reasoning
Artificial Intelligence
TACAS'13 Proceedings of the 19th international conference on Tools and Algorithms for the Construction and Analysis of Systems
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In this paper we present a novel "modular" approach for (weighted partial) MaxSAT Modulo Theories. The main idea is to combine a lazy SMT solver with a purely-propositional (weighted partial) MaxSAT solver, by making them exchange information iteratively: the former produces an increasing set of theory lemmas which are used by the latter to progressively refine an approximation of the final subset of the soft clauses, which is eventually returned as output. The approach has several practical features. First, it is independent from the theories addressed. Second, it is simple to implement and to update, since both SMT and MaxSAT solvers can be used as blackboxes. Third, it can be interfaced with external MaxSAT and SMT solvers in a plug-and-play manner, so that to benefit for free of tools which are or will be made available. We have implemented our approach on top of the MathSAT5 SMT solver and of a selection of external MaxSAT solvers, and we have evaluated it by means of an extensive empirical test on SMT-LIB benchmarks. The results confirm the validity and potential of this approach.