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access icon openaccess Empirical study on developer factors affecting tossing path length of bug reports

This is an open access article published by the IET under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)
Received 24/08/2017, Accepted 09/03/2018, Revised 09/02/2018, Published 12/03/2018

Bug reassignment (also known bug tossing) is a common activity in the life cycle of bug reports, and it increases the cost of time and labour to fix bugs in software projects. In large-scale projects, about 6–10% of bug reports are tossed at least three times. However, the nature of repeatedly-tossed bug reports was usually overlooked in previous works. This study focuses on developer features from four aspects, namely network centrality, developer workspace, developer expertise, and transmissibility of developers, to investigate which factors affect the tossing path length (TPL). By using statistical methods, this study finds that working theme, product, component, and degree centrality are key impact factors affecting the change of TPL. The four key features are then simplified to three core features, namely working theme, product, and component, which contribute about 90% of the variance of TPL. Finally, the two feature groups mentioned above are applied in six machine learning algorithms to predict potential developers for bug reports from Eclipse and Mozilla, and the results validate the effectiveness of the feature groups for developer recommendation. Hence, this study provides an easy-to-use feature selection method to train quality developer recommenders for automatic bug triage in an efficient way.

Inspec keywords: learning (artificial intelligence); software engineering; software maintenance; public domain software; regression analysis; program debugging

Other keywords: developer features; bugs; bug tossing; automatic bug triage; tossing path length; bug reassignment; TPL; repeatedly-tossed bug reports; feature groups; developer factors

Subjects: Software engineering techniques; Diagnostic, testing, debugging and evaluating systems; Other topics in statistics; Knowledge engineering techniques

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