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Finding failures by cluster analysis of execution profiles

Published: 01 July 2001 Publication History

Abstract

We experimentally evaluate the effectiveness of using cluster analysis of execution profiles to find failures among the executions induced by a set of potential test cases. We compare several filtering procedures for selecting executions to evaluate for conformance to requirements. Each filtering procedure involves a choice of a sampling strategy and a clustering metric. The results suggest that filtering procedures based on clustering are more effective than simple random sampling for identifying failures in populations of operational executions, with adaptive sampling from clusters being the most effective sampling strategy. The results also suggest that clustering metrics that give extra weight to unusual profile features are most effective. Scatter plots of execution populations, produced by multidimensional scaling, are used to provide intuition for these results.

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Published In

cover image ACM Conferences
ICSE '01: Proceedings of the 23rd International Conference on Software Engineering
July 2001
844 pages
ISBN:0769510507

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IEEE Computer Society

United States

Publication History

Published: 01 July 2001

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Author Tags

  1. beta testing
  2. cluster analysis
  3. multidimensional scaling
  4. observation-based testing
  5. operational testing
  6. software testing

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ICSE01
Sponsor:
ICSE01: 23rd International Conference on Software Engineering
May 12 - 19, 2001
Ontario, Toronto, Canada

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ICSE '01 Paper Acceptance Rate 47 of 268 submissions, 18%;
Overall Acceptance Rate 276 of 1,856 submissions, 15%

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  • (2020)How C++ Templates Are Used for Generic ProgrammingACM Transactions on Software Engineering and Methodology10.1145/335657929:1(1-49)Online publication date: 30-Jan-2020
  • (2019)Failure clustering without coverageProceedings of the 28th ACM SIGSOFT International Symposium on Software Testing and Analysis10.1145/3293882.3330561(134-145)Online publication date: 10-Jul-2019
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  • (2018)FPA-FLJournal of Systems and Software10.1016/j.jss.2017.11.002136:C(39-58)Online publication date: 1-Feb-2018
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