Deciding Combinations of Theories
Journal of the ACM (JACM)
Simplification by Cooperating Decision Procedures
ACM Transactions on Programming Languages and Systems (TOPLAS)
ICS: Integrated Canonizer and Solver
CAV '01 Proceedings of the 13th International Conference on Computer Aided Verification
The Quest for Efficient Boolean Satisfiability Solvers
CAV '02 Proceedings of the 14th International Conference on Computer Aided Verification
MathSAT: Tight Integration of SAT and Mathematical Decision Procedures
Journal of Automated Reasoning
Efficient theory combination via boolean search
Information and Computation - Special issue: Combining logical systems
LPAR'06 Proceedings of the 13th international conference on Logic for Programming, Artificial Intelligence, and Reasoning
A SAT-based decision procedure for the boolean combination of difference constraints
SAT'04 Proceedings of the 7th international conference on Theory and Applications of Satisfiability Testing
An incremental and layered procedure for the satisfiability of linear arithmetic logic
TACAS'05 Proceedings of the 11th international conference on Tools and Algorithms for the Construction and Analysis of Systems
SMT-COMP: satisfiability modulo theories competition
CAV'05 Proceedings of the 17th international conference on Computer Aided Verification
Efficient satisfiability modulo theories via delayed theory combination
CAV'05 Proceedings of the 17th international conference on Computer Aided Verification
Model-based Theory Combination
Electronic Notes in Theoretical Computer Science (ENTCS)
CAV '08 Proceedings of the 20th international conference on Computer Aided Verification
Development and evaluation of LAV: an SMT-based error finding platform
VSTTE'12 Proceedings of the 4th international conference on Verified Software: theories, tools, experiments
The strategy challenge in SMT solving
Automated Reasoning and Mathematics
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Satisfiability Modulo Theories is the problem of deciding the satisfiability of a formula with respect to a given background theory . When is the combination of two simpler theories and , a standard and general approach is to handle the integration of and by performing some form of search on the equalities between the shared variables. A frequent and very relevant sub-case of is when is the theory of Equality and Uninterpreted Functions . For this case, an alternative approach is to eliminate first all uninterpreted function symbols by means of Ackermann's expansion, and then to solve the resulting problem. In this paper we build on the empirical observation that there is no absolute winner between these two alternative approaches, and that the performance gaps between them are often dramatic, in either direction. We propose a simple technique for estimating a priori the costs and benefits, in terms of the size of the search space of an tool, of applying Ackermann's expansion to all or part of the function symbols. A thorough experimental analysis, including the benchmarks of the SMT'05 competition, shows that the proposed technique is extremely effective in improving the overall performance of the tool.