Assessing Open Source Software Survivability using Kaplan-Meier Survival Function and Polynomial Regression

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.

BibTeX

@inproceedings{Park-al:ASE24,
  author    = {Sohee Park and
               Ryeonggu Kwon and
               Gihwon Kwon},
  title     = {Assessing Open Source Software Survivability using {Kaplan-Meier} Survival Function and Polynomial Regression},
  booktitle = {ASE},
  pages     = {2470--2471},
  publisher = {{ACM}},
  year      = {2024},
}

Assessing Open Source Software Survivability using Kaplan-Meier Survival Function and Polynomial Regression

Abstract

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