Refining Abstract Interpretation Based Value Analysis with Constraint Programming Techniques

  • Olivier Ponsini
  • Claude Michel
  • Michel Rueher
Conference paper

DOI: 10.1007/978-3-642-33558-7_43

Part of the Lecture Notes in Computer Science book series (LNCS, volume 7514)
Cite this paper as:
Ponsini O., Michel C., Rueher M. (2012) Refining Abstract Interpretation Based Value Analysis with Constraint Programming Techniques. In: Milano M. (eds) Principles and Practice of Constraint Programming. Lecture Notes in Computer Science, vol 7514. Springer, Berlin, Heidelberg

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.

Keywords

Program verification Floating-point computation Constraint solvers over floating-point numbers Constraint solvers over real number intervals Abstract interpretation-based approximation 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Olivier Ponsini
    • 1
  • Claude Michel
    • 1
  • Michel Rueher
    • 1
  1. 1.University of Nice–Sophia Antipolis, I3S/CNRSSophia Antipolis CedexFrance

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