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Can File Level Characteristics Help Identify System Level Fault-Proneness?

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Part of the Lecture Notes in Computer Science book series (LNPSE,volume 7261)

Abstract

In earlier studies of multiple-release systems, we observed that the number of changes and the number of faults in a file in the past release, the size of a file, and the maturity of a file are all useful predictors of the file’s fault proneness in the next release. In each case the data needed to make predictions have been extracted from a configuration management system which provides integrated change management and version control functionality. In this paper we investigate analogous questions for the system as a whole, rather than looking at its constituent files. Using two large industrial software systems, each with many field releases, we examine a number of questions relating defects to system maturity, how often the system has changed, the size difference of a release from the prior release, and the length of time a release has been under development before the start of system testing. Most of our observations match neither our intuition, nor the relations observed for these two systems when similar questions were asked at the file level.

Keywords

  • software fault prediction
  • fault density
  • system maturity
  • system size
  • system changes
  • elapsed development time

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References

  1. Weyuker, E.J., Ostrand, T.J.: The Distribution of Faults in a Large Industrial Software System. In: Proc. ACM/International Symposium on Software Testing and Analysis (ISSTA 2002), Rome, Italy, pp. 55–64 (July 2002)

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  2. Ostrand, T.J., Weyuker, E.J., Bell, R.M.: Predicting the Location and Number of Faults in Large Software Systems. IEEE Trans. on Software Engineering 31(4) (April 2005)

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  3. Weyuker, E.J., Ostrand, T.J., Bell, R.M.: Comparing the Effectiveness of Several Modeling Methods for Fault Prediction. Empirical Software Eng. (June 2009)

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  4. Bell, R.M., Ostrand, T.J., Weyuker, E.J.: Does Measuring Code Change Improve Fault Prediction? In: Proc. 7th International Conference on Predictive Models in Software Engineering (Promise 2011), Banff, Canada (September 2011)

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© 2012 Springer-Verlag Berlin Heidelberg

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Ostrand, T.J., Weyuker, E.J. (2012). Can File Level Characteristics Help Identify System Level Fault-Proneness?. In: Eder, K., Lourenço, J., Shehory, O. (eds) Hardware and Software: Verification and Testing. HVC 2011. Lecture Notes in Computer Science, vol 7261. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34188-5_16

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  • DOI: https://doi.org/10.1007/978-3-642-34188-5_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34187-8

  • Online ISBN: 978-3-642-34188-5

  • eBook Packages: Computer ScienceComputer Science (R0)