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[2602.09064] Predicting Open Source Software Sustainability with Deep Temporal Neural Hierarchical Architectures and Explainable AI
Summary
This paper introduces a predictive framework for assessing the sustainability of Open Source Software (OSS) projects, utilizing deep temporal neural architectures and explainable AI to analyze project lifecycle stages.
Why It Matters
Understanding OSS sustainability is crucial for developers and stakeholders to ensure project longevity and community engagement. This research provides a novel approach that integrates temporal data and community dynamics, offering deeper insights into OSS health and sustainability.
Key Takeaways
- Proposes a hierarchical framework to model OSS lifecycle stages.
- Integrates contribution activity and community participation as key sustainability metrics.
- Achieves over 94% accuracy in classifying OSS lifecycle stages.
- Utilizes explainable AI to enhance transparency in model predictions.
- Highlights the importance of collective participation dynamics in OSS sustainability.
Computer Science > Software Engineering arXiv:2602.09064 (cs) [Submitted on 9 Feb 2026 (v1), last revised 13 Feb 2026 (this version, v2)] Title:Predicting Open Source Software Sustainability with Deep Temporal Neural Hierarchical Architectures and Explainable AI Authors:S M Rakib Ul Karim, Wenyi Lu, Enock Kasaadha, Sean Goggins View a PDF of the paper titled Predicting Open Source Software Sustainability with Deep Temporal Neural Hierarchical Architectures and Explainable AI, by S M Rakib Ul Karim and 3 other authors View PDF HTML (experimental) Abstract:Open Source Software (OSS) projects follow diverse lifecycle trajectories shaped by evolving patterns of contribution, coordination, and community engagement. Understanding these trajectories is essential for stakeholders seeking to assess project organization and health at scale. However, prior work has largely relied on static or aggregated metrics, such as project age or cumulative activity, providing limited insight into how OSS sustainability unfolds over time. In this paper, we propose a hierarchical predictive framework that models OSS projects as belonging to distinct lifecycle stages grounded in established socio-technical categorizations of OSS development. Rather than treating sustainability solely as project longevity, these lifecycle stages operationalize sustainability as a multidimensional construct integrating contribution activity, community participation, and maintenance dynamics. The framework combines e...
