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The distribution of faults in a large industrial software system

Published: 01 July 2002 Publication History

Abstract

A case study is presented using thirteen releases of a large industrial inventory tracking system. Several types of questions are addressed in this study. The first involved examining how faults are distributed over the different files. This included making a distinction between the release during which they were discovered, the lifecycle stage at which they were first detected, and the severity of the fault. The second category of questions we considered involved studying how the size of modules affected their fault density. This included looking at questions like whether or not files with high fault densities at early stages of the lifecycle also had high fault densities during later stages. A third type of question we considered was whether files that contained large numbers of faults during early stages of development, also had large numbers of faults during later stages, and whether faultiness persisted from release to release. Finally, we examined whether newly written files were more fault-prone than ones that were written for earlier releases of the product. The ultimate goal of this study is to help identify characteristics of files that can be used as predictors of fault-proneness, thereby helping organizations determine how best to use their testing resources.

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N. E. Fenton and N. Ohlsson. Quantitative Analysis of Faults and Failures in a Complex Software System. IEEE Trans. on Software Engineering, Vol 26, No 8, Aug 2000, pp.797-814.
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T. L. Graves, A. F. Karr, J. S. Marron, and H. Siy. Predicting Fault Incidence Using Software Change History. IEEE Trans. on Software Engineering, Vol 26, No 7, Jul 2000, pp.653-661.
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K-H. Moller and D. J. Paulish. An Empirical Investigation of Software Fault Distribution. Proc. IEEE First Internation Software Metrics Symposium, Baltimore, Md., May 21-22, 1993, pp.82-90.
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cover image ACM Conferences
ISSTA '02: Proceedings of the 2002 ACM SIGSOFT international symposium on Software testing and analysis
July 2002
248 pages
ISBN:1581135629
DOI:10.1145/566172
  • cover image ACM SIGSOFT Software Engineering Notes
    ACM SIGSOFT Software Engineering Notes  Volume 27, Issue 4
    July 2002
    242 pages
    ISSN:0163-5948
    DOI:10.1145/566171
    Issue’s Table of Contents
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Publication History

Published: 01 July 2002

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Author Tags

  1. empirical study
  2. fault-prone
  3. pareto
  4. software faults
  5. software testing

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