“Won’t we fix this issue?” : qualitative characterization and automated identification of wontfix issues on GitHub

Panichella, Sebastiano; Canfora, Gerardo; Di Sorbo, Andrea

doi:10.1016/j.infsof.2021.106665

Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-23352

Publication type:	Article in scientific journal
Type of review:	Peer review (publication)
Title:	“Won’t we fix this issue?” : qualitative characterization and automated identification of wontfix issues on GitHub
Authors:	Panichella, Sebastiano Canfora, Gerardo Di Sorbo, Andrea
et. al:	No
DOI:	10.1016/j.infsof.2021.106665 10.21256/zhaw-23352
Published in:	Information and Software Technology
Volume(Issue):	139
Issue:	106665
Issue Date:	2021
Publisher / Ed. Institution:	Elsevier
ISSN:	0950-5849
Language:	English
Subjects:	Issue tracking; Issue management; Empirical study; Machine learning
Subject (DDC):	005: Computer programming, programs and data
Abstract:	Context: Addressing user requests in the form of bug reports and Github issues represents a crucial task of any successful software project. However, user-submitted issue reports tend to widely differ in their quality, and developers spend a considerable amount of time handling them. Objective: By collecting a dataset of around 6,000 issues of 279 GitHub projects, we observe that developers take significant time (i.e., about five months, on average) before labeling an issue as a wontfix. For this reason, in this paper, we empirically investigate the nature of wontfix issues and methods to facilitate issue management process. Method: We first manually analyze a sample of 667 wontfix issues, extracted from heterogeneous projects, investigating the common reasons behind a “wontfix decision”, the main characteristics of wontfix issues and the potential factors that could be connected with the time to close them. Furthermore, we experiment with approaches enabling the prediction of wontfix issues by analyzing the titles and descriptions of reported issues when submitted. Results and conclusion: Our investigation sheds some light on the wontfix issues’ characteristics, as well as the potential factors that may affect the time required to make a “wontfix decision”. Our results also demonstrate that it is possible to perform prediction of wontfix issues with high average values of precision, recall, and F-measure (90%-93%).
URI:	https://digitalcollection.zhaw.ch/handle/11475/23352
Fulltext version:	Accepted version
License (according to publishing contract):	Licence according to publishing contract
Departement:	School of Engineering
Organisational Unit:	Institute of Computer Science (InIT)
Published as part of the ZHAW project:	COSMOS – DevOps for Complex Cyber-physical Systems of Systems
Appears in collections:	Publikationen School of Engineering

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2021_Panichella-etal_Wontfix-issues-GitHub.pdf	Accepted Version	1.04 MB	Adobe PDF	View/Open

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Panichella, S., Canfora, G., & Di Sorbo, A. (2021). “Won’t we fix this issue?” : qualitative characterization and automated identification of wontfix issues on GitHub. Information and Software Technology, 139(106665). https://doi.org/10.1016/j.infsof.2021.106665

Panichella, S., Canfora, G. and Di Sorbo, A. (2021) ‘“Won’t we fix this issue?” : qualitative characterization and automated identification of wontfix issues on GitHub’, Information and Software Technology, 139(106665). Available at: https://doi.org/10.1016/j.infsof.2021.106665.

S. Panichella, G. Canfora, and A. Di Sorbo, ““Won’t we fix this issue?” : qualitative characterization and automated identification of wontfix issues on GitHub,” Information and Software Technology, vol. 139, no. 106665, 2021, doi: 10.1016/j.infsof.2021.106665.

PANICHELLA, Sebastiano, Gerardo CANFORA und Andrea DI SORBO, 2021. “Won’t we fix this issue?” : qualitative characterization and automated identification of wontfix issues on GitHub. Information and Software Technology. 2021. Bd. 139, Nr. 106665. DOI 10.1016/j.infsof.2021.106665

Panichella, Sebastiano, Gerardo Canfora, and Andrea Di Sorbo. 2021. ““Won’t We Fix This Issue?” : Qualitative Characterization and Automated Identification of Wontfix Issues on GitHub.” Information and Software Technology 139 (106665). https://doi.org/10.1016/j.infsof.2021.106665.

Panichella, Sebastiano, et al. ““Won’t We Fix This Issue?” : Qualitative Characterization and Automated Identification of Wontfix Issues on GitHub.” Information and Software Technology, vol. 139, no. 106665, 2021, https://doi.org/10.1016/j.infsof.2021.106665.