Satisfiability Modulo Theories (SMT(T)) is the problem of deciding the satisfiability of a formula with respect to a given background theory T. When T is the combination of two simpler theories T1 and T2 (SMT(T1 ∪ T2)), a standard and general approach is to handle the integration of T1 and T2 by performing some form of search on the equalities between the shared variables. A frequent and very relevant sub-case of SMT(T1 ∪ T2) is when T 1 is the theory of Equality and Uninterpreted Functions (EUF). 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 SMT (T2) 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...

To Ackermann-ize or Not to Ackermann-ize? On Efficiently Handling Uninterpreted Function Symbols in SMT (EUF ÈT)

Bruttomesso, Roberto;Franzen, Per Anders;Griggio, Alberto;Sebastiani, Roberto
2006-01-01

Abstract

Satisfiability Modulo Theories (SMT(T)) is the problem of deciding the satisfiability of a formula with respect to a given background theory T. When T is the combination of two simpler theories T1 and T2 (SMT(T1 ∪ T2)), a standard and general approach is to handle the integration of T1 and T2 by performing some form of search on the equalities between the shared variables. A frequent and very relevant sub-case of SMT(T1 ∪ T2) is when T 1 is the theory of Equality and Uninterpreted Functions (EUF). 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 SMT (T2) 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...
2006
Logic for Programming, Artificial Intelligence, and Reasoning: 13th International Conference, LPAR 2006, Phnom Penh, Cambodia, November 13-17, 2006, Proceedings
Berlin/Heidelberg
Springer
9783540482819
Bruttomesso, Roberto; A., Cimatti; Franzen, Per Anders; Griggio, Alberto; A., Santuari; Sebastiani, Roberto
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/78045
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