Ecosystem-wide influences on pull request decisions: insights from NPM

• URL: http://arxiv.org/abs/2410.14695v2
• Date: Mon, 10 Mar 2025 07:29:00 GMT
• Title: Ecosystem-wide influences on pull request decisions: insights from NPM
• Authors: Willem Meijer, Mirela Riveni, Ayushi Rastogi,
• Abstract summary: We collect a dataset of approximately 1.8 million pull requests and 2.1 million issues from 20,052 GitHub projects within the NPM ecosystem.<n>We find that developers with ecosystem experience make different contributions than users without.<n>We find that combining ecosystem-wide factors with features studied in previous work to predict the outcome of pull requests reached an overall F1 score of 0.92.
• Score: 1.7205106391379021
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: The pull-based development model facilitates global collaboration within open-source software projects. However, whereas it is increasingly common for software to depend on other projects in their ecosystem, most research on the pull request decision-making process explored factors within projects, not the broader software ecosystem they comprise. We uncover ecosystem-wide factors that influence pull request acceptance decisions. We collected a dataset of approximately 1.8 million pull requests and 2.1 million issues from 20,052 GitHub projects within the NPM ecosystem. Of these, 98% depend on another project in the dataset, enabling studying collaboration across dependent projects. We employed social network analysis to create a collaboration network in the ecosystem, and mixed effects logistic regression and random forest techniques to measure the impact and predictive strength of the tested features. We find that gaining experience within the software ecosystem through active participation in issue-tracking systems, submitting pull requests, and collaborating with pull request integrators and experienced developers benefits all open-source contributors, especially project newcomers. These results are complemented with an exploratory qualitative analysis of 538 pull requests. We find that developers with ecosystem experience make different contributions than users without. Zooming in on a subset of 111 pull requests with clear ecosystem involvement, we find 3 overarching and 10 specific reasons why developers involve ecosystem projects in their pull requests. The results show that combining ecosystem-wide factors with features studied in previous work to predict the outcome of pull requests reached an overall F1 score of 0.92. However, the outcomes of pull requests submitted by newcomers are harder to predict.

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