Incremental instance generation in local reasoning

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Abstract

Many verification approaches use SMT solvers in some form, and are limited by their incomplete handling of quantified formulas. Local reasoning allows to handle SMT problems involving a certain class of universally quantified formulas in a complete way by instantiation to a finite set of ground formulas. We present a method to generate these instances incrementally, in order to provide a more efficient way of solving these satisfiability problems. The incremental instantiation is guided semantically, inspired by the instance generation approach to first-order theorem proving. Our method is sound and complete, and terminates on both satisfiable and unsatisfiable input after generating a subset of the instances needed in standard local reasoning. Experimental results show that for a large class of examples the incremental approach is substantially more efficient than eager generation of all instances. © 2009 Springer Berlin Heidelberg.

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APA

Jacobs, S. (2009). Incremental instance generation in local reasoning. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5643 LNCS, pp. 368–382). https://doi.org/10.1007/978-3-642-02658-4_29

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