Validation of network measures as indicators of defective modules in software systems

Ayşe Tosun*, Burak Turhan, Ayşe Bener

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

74 Citations (Scopus)

Abstract

In ICSE'08, Zimmermann and Nagappan show that network measures derived from dependency graphs are able to identify critical binaries of a complex system that are missed by complexity metrics. The system used in their analysis is a Windows product. In this study, we conduct additional experiments on public data to reproduce and validate their results. We use complexity and network metrics from five additional systems. We examine three small scale embedded software and two versions of Eclipse to compare defect prediction performance of these metrics. We select two different granularity levels to perform our experiments: function-level and source file-level. In our experiments, we observe that network measures are important indicators of defective modules for large and complex systems, whereas they do not have significant effects on small scale projects.

Original languageEnglish
Title of host publicationPROMISE 2009 - International Conference on Predictor Models in Software Engineering
DOIs
Publication statusPublished - 2009
Externally publishedYes
Event5th International Conference on Predictor Models in Software Engineering, PROMISE '09 - Vancouver, BC, Canada
Duration: 18 May 200919 May 2009

Publication series

NameACM International Conference Proceeding Series

Conference

Conference5th International Conference on Predictor Models in Software Engineering, PROMISE '09
Country/TerritoryCanada
CityVancouver, BC
Period18/05/0919/05/09

Keywords

  • code metrics
  • defect prediction
  • network metrics
  • public datasets

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