Revisiting common bug prediction findings using effort-aware models

Yasutaka Kamei, Shinsuke Matsumoto, Akito Monden, Ken Ichi Matsumoto, Bram Adams, Ahmed E. Hassan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

95 Citations (Scopus)

Abstract

Bug prediction models are often used to help allocate software quality assurance efforts (e.g. testing and code reviews). Mende and Koschke have recently proposed bug prediction models that are effort-aware. These models factor in the effort needed to review or test code when evaluating the effectiveness of prediction models, leading to more realistic performance evaluations. In this paper, we revisit two common findings in the bug prediction literature: 1) Process metrics (e.g., change history) outperform product metrics (e.g., LOC), 2) Packagelevel predictions outperform file-level predictions. Through a case study on three projects from the Eclipse Foundation, we find that the first finding holds when effort is considered, while the second finding does not hold. These findings validate the practical significance of prior findings in the bug prediction literature and encourage their adoption in practice.

Original languageEnglish
Title of host publicationProceedings - 2010 IEEE International Conference on Software Maintenance, ICSM 2010
DOIs
Publication statusPublished - Dec 20 2010
Event2010 IEEE International Conference on Software Maintenance, ICSM 2010 - Timisoara, Romania
Duration: Sep 12 2010Sep 18 2010

Publication series

NameIEEE International Conference on Software Maintenance, ICSM

Conference

Conference2010 IEEE International Conference on Software Maintenance, ICSM 2010
CountryRomania
CityTimisoara
Period9/12/109/18/10

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ASJC Scopus subject areas

  • Software

Cite this

Kamei, Y., Matsumoto, S., Monden, A., Matsumoto, K. I., Adams, B., & Hassan, A. E. (2010). Revisiting common bug prediction findings using effort-aware models. In Proceedings - 2010 IEEE International Conference on Software Maintenance, ICSM 2010 [5609530] (IEEE International Conference on Software Maintenance, ICSM). https://doi.org/10.1109/ICSM.2010.5609530