How Early Participation Determines Long-Term Sustained Activity in GitHub Projects?

TL;DR

This study uses machine learning to analyze how early participation influences long-term sustainability of GitHub projects, highlighting the importance of experienced contributors, focused effort, and detailed documentation.

Contribution

It introduces a novel predictive approach combining the Blumberg model and machine learning to identify early factors that determine open source project sustainability.

Findings

Early experienced contributors positively impact long-term activity.

Concentrated focus and steady commitment promote sustainability.

Community composition with core and peripheral developers is crucial for organizational projects.

Abstract

Although the open source model bears many advantages in software development, open source projects are always hard to sustain. Previous research on open source sustainability mainly focuses on projects that have already reached a certain level of maturity (e.g., with communities, releases, and downstream projects). However, limited attention is paid to the development of (sustainable) open source projects in their infancy, and we believe an understanding of early sustainability determinants is crucial for project initiators, incubators, newcomers, and users. In this paper, we aim to explore the relationship between early participation factors and long-term project sustainability. We leverage a novel methodology combining the Blumberg model of performance and machine learning to predict the sustainability of 290,255 GitHub projects. Specificially, we train an XGBoost model based on early participation (first three months of activity) in 290,255 GitHub projects and we interpret the model using LIME. We quantitatively show that early participants have a positive effect on project's future sustained activity if they have prior experience in OSS project incubation and demonstrate concentrated focus and steady commitment. Participation from non-code contributors and detailed contribution documentation also promote project's sustained activity. Compared with individual projects, building a community that consists of more experienced core developers and more active peripheral developers is important for organizational projects. This study provides unique insights into the incubation and recognition of sustainable open source projects, and our interpretable prediction approach can also offer guidance to open source project initiators and newcomers.