Deciding Quantifier-Free Presburger Formulas Using Parameterized Solution Bounds

  • Authors:
  • Sanjit A. Seshia;Randal E. Bryant

  • Affiliations:
  • Carnegie Mellon University, Pittsburgh, PA;Carnegie Mellon University, Pittsburgh, PA

  • Venue:
  • LICS '04 Proceedings of the 19th Annual IEEE Symposium on Logic in Computer Science
  • Year:
  • 2004

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Abstract

Given a formula 驴 in quantifier-free Presburger arithmetic, it is well known that, if there is a satisfying solution to 驴, there is one whose size, measured in bits, is polynomially bounded in the size of 驴. In this paper, we consider a special class of quantifier-free Presburger formulas in which most linear constraints are separation (difference-bound) constraints, and the non-separation constraints are sparse. This class has been observed to commonly occur in software verification problems. We derive a new solution bound in terms of parameters characterizing the sparseness of linear constraints and the number of non-separation constraints, in addition to traditional measures of formula size. In particular, the number of bits needed per integer variable is linear in the number of non-separation constraints and logarithmic in the number and size of non-zero coefficients in them, but is otherwise independent of the total number of linear constraints in the formula. The derived bound can be used in a decision procedure based on instantiating integer variables over a finite domain and translating the input quantifier-free Presburger formula to an equi-satisfiable Boolean formula, which is then checked using a Boolean satisfiability solver. We present empirical evidence indicating that this method can greatly outperform other decision procedures.