Solving quantified linear arithmetic by counterexample-guided instantiation

The work

AuthorsAndrew Reynolds; Tim King; Viktor Kuncak
Editors
Typearticle
Year2017
Citekeyreynolds2017solving

Where it appeared

Published inFormal Methods in System Design
Volume51
Issue3
Pages500--532

Abstract

This paper presents a framework to derive instantiation-based decision procedures for satisfiability of quantified formulas in first-order theories, including its correctness, implementation, and evaluation. Using this framework we derive decision procedures for linear real arithmetic (LRA) and linear integer arithmetic (LIA) formulas with one quantifier alternation. We discuss extensions of these techniques for handling mixed real and integer arithmetic, and to formulas with arbitrary quantifier alternations. For the latter, we use a novel strategy that handles quantified formulas that are not in prenex normal form, which has advantages with respect to existing approaches. All of these techniques can be integrated within the solving architecture used by typical SMT solvers. Experimental results on standardized benchmarks from model checking, static analysis, and synthesis show that our implementation in the SMT solver CVC4 outperforms existing tools for quantified linear arithmetic.

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Added2026-08-05 00:00 UTC
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Cite it as

@article{reynolds2017solving,
  title        = {Solving quantified linear arithmetic by counterexample-guided instantiation},
  author       = {Andrew Reynolds and Tim King and Viktor Kuncak},
  year         = {2017},
  journal      = {Formal Methods in System Design},
  volume       = {51},
  number       = {3},
  pages        = {500--532},
  doi          = {10.1007/s10703-017-0290-y},
}

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