2024 39th IEEE/ACM International Conference on Automated Software Engineering (ASE)
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Abstract

This study evaluates OSS project survivability using the Kaplan-Meier Survival Function and polynomial regression models. The key factors identified include the number of contributors and project popularity, which significantly influence survivability. Traditional indicators like project age do not directly correlate with OSS survivability. Instead, community engagement and recognition are crucial, offering valuable guidelines for managing and selecting Survivable OSS projects.CCS Concepts• Software and its engineering → Software libraries and repositories; Maintaining software.
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