Uncovering Scientific Software Sustainability through Community Engagement and Software Quality Metrics

Fuente: arXiv
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Main Authors: Ahmed, Sharif, Thakur, Addi Malviya, Watson, Gregory R., Eisty, Nasir U.
Format: Preprint
Published: 2025
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author Ahmed, Sharif
Thakur, Addi Malviya
Watson, Gregory R.
Eisty, Nasir U.
author_facet Ahmed, Sharif
Thakur, Addi Malviya
Watson, Gregory R.
Eisty, Nasir U.
contents Scientific open-source software (Sci-OSS) projects are critical for advancing research, yet sustaining these projects long-term remains a major challenge. This paper explores the sustainability of Sci-OSS hosted on GitHub, focusing on two factors drawn from stewardship organizations: community engagement and software quality. We map sustainability to repository metrics from the literature and mined data from ten prominent Sci-OSS projects. A multimodal analysis of these projects led us to a novel visualization technique, providing a robust way to display both current and evolving software metrics over time, replacing multiple traditional visualizations with one. Additionally, our statistical analysis shows that even similar-domain projects sustain themselves differently. Natural language analysis supports claims from the literature, highlighting that project-specific feedback plays a key role in maintaining software quality. Our visualization and analysis methods offer researchers, funders, and developers key insights into long-term software sustainability.
format Preprint
id arxiv_https___arxiv_org_abs_2511_07851
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Uncovering Scientific Software Sustainability through Community Engagement and Software Quality Metrics
Ahmed, Sharif
Thakur, Addi Malviya
Watson, Gregory R.
Eisty, Nasir U.
Software Engineering
Scientific open-source software (Sci-OSS) projects are critical for advancing research, yet sustaining these projects long-term remains a major challenge. This paper explores the sustainability of Sci-OSS hosted on GitHub, focusing on two factors drawn from stewardship organizations: community engagement and software quality. We map sustainability to repository metrics from the literature and mined data from ten prominent Sci-OSS projects. A multimodal analysis of these projects led us to a novel visualization technique, providing a robust way to display both current and evolving software metrics over time, replacing multiple traditional visualizations with one. Additionally, our statistical analysis shows that even similar-domain projects sustain themselves differently. Natural language analysis supports claims from the literature, highlighting that project-specific feedback plays a key role in maintaining software quality. Our visualization and analysis methods offer researchers, funders, and developers key insights into long-term software sustainability.
title Uncovering Scientific Software Sustainability through Community Engagement and Software Quality Metrics
topic Software Engineering
url https://arxiv.org/abs/2511.07851