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Developer Micro Interaction Metrics for Software Defect Prediction

Authors
Lee, TaekNam, JaechangHan, DonggyunKim, SunghunIn, Hoh Peter
Issue Date
1-11월-2016
Publisher
IEEE COMPUTER SOC
Keywords
Defect prediction; software quality; software metrics; developer interaction; Mylyn
Citation
IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, v.42, no.11, pp.1015 - 1035
Indexed
SCIE
SCOPUS
Journal Title
IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
Volume
42
Number
11
Start Page
1015
End Page
1035
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/86890
DOI
10.1109/TSE.2016.2550458
ISSN
0098-5589
Abstract
To facilitate software quality assurance, defect prediction metrics, such as source code metrics, change churns, and the number of previous defects, have been actively studied. Despite the common understanding that developer behavioral interaction patterns can affect software quality, these widely used defect prediction metrics do not consider developer behavior. We therefore propose micro interaction metrics (MIMs), which are metrics that leverage developer interaction information. The developer interactions, such as file editing and browsing events in task sessions, are captured and stored as information by Mylyn, an Eclipse plug-in. Our experimental evaluation demonstrates that MIMs significantly improve overall defect prediction accuracy when combined with existing software measures, perform well in a cost-effective manner, and provide intuitive feedback that enables developers to recognize their own inefficient behaviors during software development.
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