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Computing All Implied Equalities via SMT-Based Partition Refinement

  • Josh Berdine
  • Nikolaj Bjørner
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8562)

Abstract

Consequence finding is used in many applications of deduction. This paper develops and evaluates a suite of optimized SMT-based algorithms for computing equality consequences over arbitrary formulas and theories supported by SMT solvers. It is inspired by an application in the SLAyer analyzer, where our new algorithms are commonly 10–100x faster than simpler algorithms. The main idea is to incrementally refine an initially coarse partition using models extracted from a solver. Our approach requires only O(N) solver calls for N terms, but in the worst case creates O(N 2) fresh subformulas. Simpler algorithms, in contrast, require O(N 2) solver calls. We also describe an asymptotically superior algorithm that requires O(N) solver calls and only O(NlogN) fresh subformulas. We evaluate algorithms which reduce the number of fresh formulas required either by using specialized data structures or by relying on subformula sharing.

Keywords

Implied Equalities Consequence Finding Satisfiability Modulo Theories Decision Procedures Congruence Closure Software Verification 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Josh Berdine
    • 1
  • Nikolaj Bjørner
    • 1
  1. 1.Microsoft ResearchUSA

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