An analysis of developer metrics for fault prediction

Shinsuke Matsumoto, Yasutaka Kamei, Akito Monden, Ken Ichi Matsumoto, Masahide Nakamura

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

45 Citations (Scopus)

Abstract

Background: Software product metrics have been widely used as independent variables for constructing a fault prediction model. However, fault injection depends not only on characteristics of the products themselves, but also on characteristics of developers involved in the project. Aims: The goal of this paper is to study the effects of developer features on software reliability. Method: This paper proposes developer metrics such as the number of code churns made by each developer, the number of commitments made by each developer and the number of developers for each module. By using the eclipse project dataset, we experimentally analyzed the relationship between the number of faults and developer metrics. Second, the effective of developer metrics for performance improvements of fault prediction models were evaluated. Results: The result revealed that the modules touched by more developer contained more faults. Compared with conventional fault prediction models, developer metrics improved the prediction performance. Conclusions: We conclude that developer metrics are good predictor of faults and we must consider the human factors for improving the software reliability.

Original languageEnglish
Title of host publication6th International Conference on Predictive Models in Software Engineering, PROMISE 2010
DOIs
Publication statusPublished - Dec 10 2010
Externally publishedYes
Event6th International Conference on Predictive Models in Software Engineering, PROMISE 2010 - Timisoara, Romania
Duration: Sep 12 2010Sep 13 2010

Publication series

NameACM International Conference Proceeding Series

Conference

Conference6th International Conference on Predictive Models in Software Engineering, PROMISE 2010
CountryRomania
CityTimisoara
Period9/12/109/13/10

Keywords

  • Developer metrics
  • Fault prediction
  • Human factor

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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