Using dynamic analysis to discover polynomial and array invariants

  • Authors:
  • ThanhVu Nguyen;Deepak Kapur;Westley Weimer;Stephanie Forrest

  • Affiliations:
  • University of New Mexico, USA;University of New Mexico, USA;University of Virginia, USA;University of New Mexico, USA

  • Venue:
  • Proceedings of the 34th International Conference on Software Engineering
  • Year:
  • 2012

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Abstract

Dynamic invariant analysis identifies likely properties over variables from observed program traces. These properties can aid programmers in refactoring, documenting, and debugging tasks by making dynamic patterns visible statically. Two useful forms of invariants involve relations among polynomials over program variables and relations among array variables. Current dynamic analysis methods support such invariants in only very limited forms. We combine mathematical techniques that have not previously been applied to this problem, namely equation solving, polyhedra construction, and SMT solving, to bring new capabilities to dynamic invariant detection. Using these methods, we show how to find equalities and inequalities among nonlinear polynomials over program variables, and linear relations among array variables of multiple dimensions. Preliminary experiments on 24 mathematical algorithms and an implementation of AES encryption provide evidence that the approach is effective at finding these invariants.