Multi-Ecosystem Modeling of OSS Project Sustainability

TL;DR

This paper presents a comprehensive empirical analysis and modeling approach for assessing and forecasting the sustainability of open-source software projects across multiple ecosystems, including foundations and GitHub.

Contribution

It introduces foundation-specific sustainability models and a triage framework based on sociotechnical profiles, applicable across diverse OSS ecosystems.

Findings

Models effectively forecast project sustainability outcomes.

Framework generalizes across foundations and GitHub projects.

Actionable recovery strategies improve project sustainability.

Abstract

Many OSS projects join foundations such as Apache, Eclipse, and OSGeo, to aid their immediate plans and improve long-term prospects by getting governance advice, incubation support, and community-building mechanisms. But foundations differ in their policies, funding models, and support strategies. Moreover, since projects joining these foundations are diverse, coming at different lifecycle stages and having different needs, it can be challenging to decide on the appropriate project-foundation match and on the project-specific plan for sustainability. Here, we present an empirical study and quantitative analysis of the sustainability of incubator projects in the Apache, Eclipse, and OSGeo foundations, and, additionally, of OSS projects from GitHub outside of foundations. We develop foundation-specific sustainability models and a project triage, based on projects' sociotechnical trace profiles, and demonstrate their effectiveness across the foundations. Our results show that our models with triage can effectively forecast sustainability outcomes not only within but across foundations. In addition, the generalizability of the framework allows us to apply the approach to GitHub projects outside the foundations. We complement our findings with actionable recovery strategies from previous work and apply them to case studies of failed incubator projects. Our study highlights the value of sociotechnical frameworks in characterizing and addressing software project sustainability issues.