Refining abstract interpretation based value analysis with constraint programming techniques

  • Authors:
  • Olivier Ponsini;Claude Michel;Michel Rueher

  • Affiliations:
  • University of Nice---Sophia Antipolis, I3S/CNRS, Sophia Antipolis Cedex, France;University of Nice---Sophia Antipolis, I3S/CNRS, Sophia Antipolis Cedex, France;University of Nice---Sophia Antipolis, I3S/CNRS, Sophia Antipolis Cedex, France

  • Venue:
  • CP'12 Proceedings of the 18th international conference on Principles and Practice of Constraint Programming
  • Year:
  • 2012

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Abstract

Abstract interpretation based value analysis is a classical approach for verifying programs with floating-point computations. However, state-of-the-art tools compute an over-approximation of the variable values that can be very coarse. In this paper, we show that constraint solvers can significantly refine the approximations computed with abstract interpretation tools. We introduce a hybrid approach that combines abstract interpretation and constraint programming techniques in a single static and automatic analysis. rAiCp, the system we developed is substantially more precise than Fluctuat, a state-of-the-art static analyser. Moreover, it could eliminate 13 false alarms generated by Fluctuat on a standard set of benchmarks.