Nidhi Chahal,
Rajnish,
Sachin,
- Assistant Professor, Department of Electronics and Communication Engineering, Chandigarh Engineering College-CGC, Punjab, India
- Student, Department of Electronics and Communication Engineering, Chandigarh Engineering College-CGC, Punjab, India
- Student, Department of Electronics and Communication Engineering, Chandigarh Engineering College-CGC, Punjab, India
Abstract
Maintenance concentration in a small number of contributors, commonly called the bus factor or truck factor, is a recognized risk indicator in open-source software engineering. Existing estimation methods report this quantity as a single value computed from the current state of a project’s history, which does not capture how the underlying risk moves over the project’s lifetime. This paper proposes measuring the bus factor repeatedly across fixed checkpoints in a project’s commit history, producing a trajectory rather than a single value, and defines three summary indicators over that trajectory: volatility, mean recovery time, and floor persistence. The measurement pipeline is applied to the complete public commit history of three widely used JavaScript packages, computing genuine, non-simulated trajectories directly from cloned repository data rather than illustrative figures. The measured results show substantial variation in floor persistence across the three packages, ranging from just under two-thirds to more than ninety-five percent of checkpoints at a bus factor of one, despite each package being under continuous active maintenance throughout its history. A full-scale application of the same pipeline to a larger, stratified sample of npm and PyPI packages is specified as the natural extension of this pilot and is described as a concrete, reproducible protocol rather than executed within the present study. The paper’s contribution is therefore twofold: a trajectory-based reformulation of bus-factor measurement, and a demonstrated, reproducible pipeline validated on genuine repository data.
Keywords: bus factor, truck factor, open-source sustainability, software supply chain, maintainer risk, GitHub mining, longitudinal software analytics
[This article belongs to Journal of Open Source Developments ]
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Journal of Open Source Developments
| Volume | 13 | |
| Issue | 02 | |
| Received | 12/09/2026 | |
| Accepted | 26/09/2026 | |
| Published | 28/09/2026 | |
| Publication Time | 16 Days |