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2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC), 2017, Vol.1, p.103-108
2017

Details

Autor(en) / Beteiligte
Titel
Revisiting the Correlation Between Alerts and Software Defects: A Case Study on MyFaces, Camel, and CXF
Ist Teil von
  • 2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC), 2017, Vol.1, p.103-108
Ort / Verlag
IEEE
Erscheinungsjahr
2017
Link zum Volltext
Quelle
IEEE Electronic Library Online
Beschreibungen/Notizen
  • 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.
Sprache
Englisch
Identifikatoren
ISSN: 0730-3157
DOI: 10.1109/COMPSAC.2017.201
Titel-ID: cdi_ieee_primary_8029597

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