An Empirical Study of Multi-discussing Pattern in Open-Source Software Development
Authors: 
Cheng Yang, Dongyang Hu, Yang Zhang, Tao Wang, Yue YuAuthors Info & Claims
Pages 1 - 10
Abstract
GitHub enables developers to expediently contribute their comments on multiple issues and switch their discussion between issues, i.e., multi-discussing. Discussing multiple issues simultaneously is able to enhance work efficiency. However, multi-discussing also relies on developers’ rationally allocating their focus, which may result in the different influence on the resolution of issues. Therefore, investigating how multi-discussing affects the issue resolution is a meaningful research question that can help developers understand the benefits and limitations of multi-discussing. Using quantitative and qualitative methods, this paper proposes a groundbreaking study of the impact of multi-discussing on issue resolution in GitHub. First, we collect and analyze data from 624 GitHub projects to explore how multi-discussing affects the overall issue resolution of the project. Further, we investigate how multi-discussing affects the resolution of a single issue. We find that multi-discussing is a common behavior in GitHub. Also, multi-discussing is connected to a shorter average issue resolution latency of the project. However, during a single issue resolution, more multi-discussing behaviors tend to bring longer issue resolution latency. We also conduct the qualitative analysis to explore the developers’ experiences and expectations of multi-discussing.
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Published In
November 2020
264 pages
ISBN:9781450388191
DOI:10.1145/3457913
Copyright © 2020 ACM.
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Published: 21 July 2021
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- Program of A New Generation of Artificial Intelligence 2030
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Internetware'20
Internetware'20: 12th Asia-Pacific Symposium on Internetware
November 1 - 3, 2020
Singapore, Singapore
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