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Giving Back: Contributions Congruent to Library Dependency Changes in a Software Ecosystem

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NIAID Data Ecosystem2026-03-14 收录
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https://zenodo.org/record/5677371
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Abstract:  Widespread adoption of third-party libraries for contemporary software development has led to the creation of large inter-dependency networks, where sustainability issues of a single library can have widespread network effects. Maintainers of these libraries are often overworked, relying on the contributions of volunteers to sustain these libraries. To understand these contributions, in this work, we leverage socio-technical techniques to introduce and formalise dependency-contribution congruence (DC congruence) at both ecosystem and library level, i.e., to understand the degree and origins of contributions congruent to dependency changes, analyze whether they contribute to library dormancy (i.e., a lack of activity), and investigate similarities between these congruent contributions compared to typical contributions. We conduct a large-scale empirical study to measure the DC congruence for the NPM ecosystem using 1.7 million issues, 970 thousand pull requests (PR), and over 5.3 million commits belonging to 107,242 NPM libraries. We find that the most congruent contributions originate from contributors who can only submit (not commit) to both a client and library. At the project level, we find that DC congruence shares an inverse relationship with the likelihood that a library becomes dormant, i.e., the lower the DC congruence, the more likely the project becomes dormant. Finally, by comparing source code of contributions, we find statistical differences in file path and added lines in source code of congruent contributions when compared to typical contributions. Our work has implications to encourage and sustain dependency change congruent contributions, especially to support library maintainers in sustaining their projects. Data Description: Datasets and source code related to (a) the ecosystem-level and package-level DC congruence results, (b) the metric data for our survival model analysis, and (c) the file path and source code similarities between contribution types. For each folder, it includes a text file to describe file details.
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2022-12-02
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