Revisiting the correlation between alerts and software defects: a case study on MyFaces, Camel, and CXF

Meng Yan, Xiaohong Zhang, Ling Xu, Haibo Hu, Song Sun, Xin Xia

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

1 Citation (Scopus)


Static analysis tools (e.g., FindBugs) are widely used to detect potential defects in software development. A recent study suggests that there is a moderate correlation between the alerts reported by static analysis tools and software defects [1]. However, despite the actionable alerts reported by static analysis tools, they may report too many meaningless unactionable alerts. Actionable alert refers to the alert which is meaningful and fixable. Unactionable alert (i.e., false positive alert) refers to the alert which is regarded as unimportant to developers, inessential to source code, or will not be fixed by developers. Are all alerts (including both actionable and unactionable alerts) suitable for indicating software defects? To address this question, we classify all the alerts into two categories, namely actionable alerts and unactionable alerts. By the following, we conduct an empirical study to evaluate the degree of correlation between defects and alerts on the evolution of three open source projects with totally 40 releases. The objective of the study is to explore two kinds of correlation analysis: One is the correlation between all the alerts reported by FindBugs and defects among the release history of a project, the other is the correlation between the actionable alerts and defects. As a result, we find that not all the alerts but the actionable alerts are suitable to be an early predictor of defects.

Original languageEnglish
Title of host publicationProceedings - 2017 IEEE 41st Annual Computer Software and Applications Conference, COMPSAC 2017
Subtitle of host publication4–8 July 2017 Torino, Italy
EditorsSorel Reisman, Sheikh Iqbal Ahamed, Claudio Demartini, Thomas Conte, Ling Liu, William Claycomb, Motonori Nakamura, Edmundo Tovar, Stelvio Cimato, Chung-Horng Lung, Hiroki Takakura, Ji-Jiang Yang, Toyokazu Akiyama, Zhiyong Zhang, Kamrul Hasan
Place of PublicationPiscataway NJ USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages6
ISBN (Electronic)9781538603673
Publication statusPublished - 2017
Externally publishedYes
EventInternational Computer Software and Applications Conference 2017 - Torino, Italy
Duration: 4 Jul 20178 Jul 2017
Conference number: 41st (Proceedings)


ConferenceInternational Computer Software and Applications Conference 2017
Abbreviated titleCOMPSAC 2017
Internet address


  • actionable alert
  • software alert
  • software defect
  • unactionable alert

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