Zhixing Li

Dr. Zhixing Li


Research Focus & Metrics

Academic Career Length

13Years (2014-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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21 January 2021 in IEEE Transactions on Software Engineering
Verified
Journal Article
Closed access
ZLZhixing Li
Zhixing Li
YYYue Yu
Yue Yu
TWTao Wang
Tao Wang
GYGang Yin
Gang Yin
SLShanshan Li
Shanshan Li
HWHuaimin Wang
Huaimin Wang
The great success of numerous community-based open source software (OSS) is based on volunteers continuously submitting contributions, but ensuring sustainability is a persistent challenge in OSS communities. Although the motivations behind and barriers to OSS contributors’ joining and retention have been extensively studied, the impacts of, reasons for and solutions to contribution abandonment at the individual level have not been well studied, especially for pull-based development. To bridge this gap, we present an empirical study on pull request abandonment based on a sizable dataset. We manually examine 321 abandoned pull requests on GitHub and then quantify the manual observations by surveying 710 OSS developers. We find that while the lack of integrators’ responsiveness and the lack of contributors’ time and interest remain the main reasons that deter contributors from participation, limitations during the processes of patch updating and consensus reaching can also cause abandonment. We also show the significant impacts of pull request abandonment on project management and maintenance. Moreover, we elucidate the strategies used by project integrators to cope with abandoned pull requests and highlight the need for a practical handover mechanism. We discuss the actionable suggestions and implications for OSS practitioners and tool builders, which can help to upgrade the infrastructure and optimize the mechanisms of OSS communities.

24 August 2020 in IEEE Transactions on Software Engineering
Verified
Journal Article
Closed access
ZLZhixing Li
Zhixing Li
YYYue Yu
Yue Yu
MZMinghui Zhou
Minghui Zhou
TWTao Wang
Tao Wang
GYGang Yin
Gang Yin
HWHuaimin Wang
Huaimin Wang
OSS projects are being developed by globally distributed contributors, who often collaborate through the pull-based model today. While this model lowers the barrier to entry for OSS developers by synthesizing, automating and optimizing the contribution process, coordination among an increasing number of contributors remains as a challenge due to the asynchronous and self-organized nature of distributed development. In particular, duplicate contributions, where multiple different contributors unintentionally submit duplicate pull requests to achieve the same goal, are an elusive problem that may waste effort in automated testing, code review and software maintenance. While the issue of duplicate pull requests has been highlighted, to what extent duplicate pull requests affect the development in OSS communities has not been well investigated. In this paper, we conduct a mixed-approach study to bridge this gap. Based on a comprehensive dataset constructed from 26 popular GitHub projects, we obtain the following findings: (a) Duplicate pull requests result in redundant human and computing resources, exerting a significant impact on the contribution and evaluation process. (b) Contributors’ inappropriate working patterns and the drawbacks of their collaborating environment might result in duplicate pull requests. (c) Compared to non-duplicate pull requests, duplicate pull requests have significantly different features, e.g., being submitted by inexperienced contributors, being fixing bugs, touching cold files, and solving tracked issues. (d) Integrators choosing between duplicate pull requests prefer to accept those with early submission time, accurate and high-quality implementation, broad coverage, test code, high maturity, deep discussion, and active response. Finally, actionable suggestions and implications are proposed for OSS practitioners.

23 November 2022 in IEEE Transactions on Software Engineering
Verified
Journal Article
Closed access
ZLZhixing Li
Zhixing Li
YYYue Yu
Yue Yu
TWTao Wang
Tao Wang
YLYan Lei
Yan Lei
YWYing Wang
Ying Wang
HWHuaimin Wang
Huaimin Wang
For most Open Source Software (OSS) projects, issues and Pull-requests (PR) are the primary means by which stakeholders of a project report and discuss software problems and code changes, and their descriptions are important for people to understand them. To help ensure the informational quality of issue/PR descriptions, GitHub introduced the issue/PR template feature, which pre-populates the description for anyone trying to open a new issue/PR. To better understand this feature, we report on a large-scale, mixed-methods empirical study of templates that explores contents, impacts, and perceptions. Our results show that templates typically contain elements to greet contributors, explain project guidelines, and collect relevant information. After template adoption, the monthly volume of incoming issues and PRs decreases, and issues have fewer monthly discussion comments and longer resolution duration. Although both contributors and maintainers positively rated the usefulness of templates from various aspects, they also reported challenges in using templates ( e . g . excessive and irrelevant information request) and suggested potential improvements of the template feature ( e . g . better user interaction and advanced automation). This work contributes to the informed use and targeted improvement of templates to enhance OSS practitioners' collaboration and interaction.

1 November 2017 in Journal of Computer Science and Technology
Verified
Journal Article
Closed access
PDF file
ZLZhixing Li
Zhixing Li
YYYue Yu
Yue Yu
GYGang Yin
Gang Yin
TWTao Wang
Tao Wang
HWHuai-Min Wang
Huai-Min Wang

20 September 2022 in Empirical Software Engineering
Verified
Journal Article
Closed access
PDF file
TZTanghaoran Zhang
Tanghaoran Zhang
YYYue Yu
Yue Yu
MXMao Xinjun
Mao Xinjun
YLYao Lu
Yao Lu
ZLZhixing Li
Zhixing Li
HWHuaimin Wang
Huaimin Wang

30 January 2021 in Journal of Computer Science and Technology
Verified
Journal Article
Closed access
PDF file
ZLZhixing Li
Zhixing Li
YYYue Yu
Yue Yu
TWTao Wang
Tao Wang
GYGang Yin
Gang Yin
MXMao Xinjun
Mao Xinjun
HWHuai-Min Wang
Huai-Min Wang