Abstract
We apply survival analysis methods to a dataset of publicly-available software projects in order to examine the attributes that might lead to their inactivity over time. We ran a Kaplan-Meier analysis and fit a Cox Proportional-Hazards model to a subset of Software Heritage Graph Dataset, consisting of 3052 popular Python projects hosted on GitLab/GitHub, Debian, and PyPI, over a period of 165 months. We show that projects with repositories on multiple hosting services, a timeline of publishing major releases, and a good network of developers, remain healthy over time and should be worthy of the effort put in by developers and contributors.
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Ali, R. H., Parlett-Pelleriti, C., & Linstead, E. (2020). Cheating Death: A Statistical Survival Analysis of Publicly Available Python Projects. In Proceedings - 2020 IEEE/ACM 17th International Conference on Mining Software Repositories, MSR 2020 (pp. 6–10). Association for Computing Machinery, Inc. https://doi.org/10.1145/3379597.3387511
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