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Where do bugs come from?

Published: 01 November 2006 Publication History

Abstract

"Where do bugs in programs come from?"---this is one of the pivotal research questions in software engineering. To answer it, one can find out which parts of a program are more defect-prone than others, and then investigate which properties correlate with defect density. In other words, once we can measure the effect, we can search for its causes. Bug databases of open-source projects are a good place to begin search because they record all the problems that occurred during the projects's lifetime. However, the location of the fix (and thus the defect) is hidden in version archives and has to be extracted separately [5]. As a result one obtains a mapping from defects to code locations.

References

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S. R. Chidamber and C. F. Kemerer. A metrics suite for object oriented design. IEEE Transactions on Software Engineering, 20(6):476--493, 1994.
[2]
N. Nagappan, T. Ball, and A. Zeller. Mining metrics to predict component failures. In Procs. of the 28th International Conference on Software Engineering (ICSE 2006), ACM, May 2006.
[3]
A. Schröter, T. Zimmermann, R. Premraj, and A. Zeller. If your bug database could talk.In Procs. 5th International Symposium on Empirical Software Engineering (ISESE 2006), Rio de Janeiro, Brazil, Sept. 2006.
[4]
A. Schröter, T. Zimmermann, and A. Zeller. Predicting component failures at design time. In Procs. 5th International Symposium on Empirical Software Engineering (ISESE 2006), Rio de Janeiro, Brazil, Sept. 2006.
[5]
T. Zimmermann, P. Weißgerber, S. Diehl, and A. Zeller. Mining version histories to guide software changes. IEEE Transactions on Software Engineering, 31(6):429--445, June 2005.

Cited By

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  • (2022)An Evaluation of Cross-Project Defect Prediction Approaches on Cross-Personalized Defect PredictionProduct-Focused Software Process Improvement10.1007/978-3-031-21388-5_30(433-448)Online publication date: 14-Nov-2022
  • (2021)Searching for Bellwether Developers for Cross-Personalized Defect PredictionProduct-Focused Software Process Improvement10.1007/978-3-030-91452-3_12(183-198)Online publication date: 26-Nov-2021
  • (2012)A Systematic Literature Review on Fault Prediction Performance in Software EngineeringIEEE Transactions on Software Engineering10.1109/TSE.2011.10338:6(1276-1304)Online publication date: 1-Nov-2012
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Published In

cover image ACM SIGSOFT Software Engineering Notes
ACM SIGSOFT Software Engineering Notes  Volume 31, Issue 6
November 2006
182 pages
ISSN:0163-5948
DOI:10.1145/1218776
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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 November 2006
Published in SIGSOFT Volume 31, Issue 6

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Cited By

View all
  • (2022)An Evaluation of Cross-Project Defect Prediction Approaches on Cross-Personalized Defect PredictionProduct-Focused Software Process Improvement10.1007/978-3-031-21388-5_30(433-448)Online publication date: 14-Nov-2022
  • (2021)Searching for Bellwether Developers for Cross-Personalized Defect PredictionProduct-Focused Software Process Improvement10.1007/978-3-030-91452-3_12(183-198)Online publication date: 26-Nov-2021
  • (2012)A Systematic Literature Review on Fault Prediction Performance in Software EngineeringIEEE Transactions on Software Engineering10.1109/TSE.2011.10338:6(1276-1304)Online publication date: 1-Nov-2012
  • (2011)iProblems - An Integrated Instrument for Reporting Design Flaws, Vulnerabilities and DefectsProceedings of the 2011 18th Working Conference on Reverse Engineering10.1109/WCRE.2011.65(437-438)Online publication date: 17-Oct-2011
  • (2010)Evaluating three approaches to extracting fault data from software change repositoriesProceedings of the 11th international conference on Product-Focused Software Process Improvement10.1007/978-3-642-13792-1_10(107-115)Online publication date: 21-Jun-2010

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