Pursuing failure: the distribution of program failures in a profile space

  • Authors:

  • William Dickinson;David Leon;Andy Podgurski

  • Affiliations:

  • Electrical Engineering & Computer Science Department, Case Western Reserve University, Cleveland, Ohio;Electrical Engineering & Computer Science Department, Case Western Reserve University, Cleveland, Ohio;Electrical Engineering & Computer Science Department, Case Western Reserve University, Cleveland, Ohio

  • Venue:
  • Proceedings of the 8th European software engineering conference held jointly with 9th ACM SIGSOFT international symposium on Foundations of software engineering
  • Year:
  • 2001

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Abstract

Observation-based testing calls for analyzing profiles of executions induced by potential test cases, in order to select a subset of executions to be checked for conformance to requirements. A family of techniques for selecting such a subset is evaluated experimentally. These techniques employ automatic cluster analysis to partition executions, and they use various sampling techniques to select executions from clusters. The experimental results support the hypothesis that with appropriate profiling, failures often have unusual profiles that are revealed by cluster analysis. The results also suggest that failures often form small clusters or chains in sparsely-populated areas of the profile space. A form of adaptive sampling called failure-pursuit sampling is proposed for revealing failures in such regions, and this sampling method is evaluated experimentally. The results suggest that failure-pursuit sampling is effective.