Statistical debugging with elastic predicates

  • Authors:

  • Ross Gore;Paul F. Reynolds;David Kamensky

  • Affiliations:

  • Dept. of Computer Science, University of Virginia, Charlottesville, USA;Dept. of Computer Science, University of Virginia, Charlottesville, USA;Institute of Computational Engineering and Sciences, University of Texas at Austin, USA

  • Venue:
  • ASE '11 Proceedings of the 2011 26th IEEE/ACM International Conference on Automated Software Engineering
  • Year:
  • 2011

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Abstract

Traditional debugging and fault localization methods have addressed localization of sources of software failures. While these methods are effective in general, they are not tailored to an important class of software, including simulations and computational models, which employ floating-point computations and continuous stochastic distributions to represent, or support evaluation of, an underlying model. To address this shortcoming, we introduce elastic predicates, a novel approach to predicate-based statistical debugging. Elastic predicates introduce profiling of values assigned to variables within a failing program. These elastic predicates are better predictors of software failure than the static and uniform predicates used in existing techniques such as Cooperative Bug Isolation (CBI). We present experimental results for established fault localization benchmarks and widely used simulations that show improved effectiveness.