Uncovering Scientific Software Sustainability through Community Engagement and Software Quality Metrics
November 11, 2025 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Sharif Ahmed, Addi Malviya Thakur, Gregory R. Watson, Nasir U. Eisty
arXiv ID
2511.07851
Category
cs.SE: Software Engineering
Citations
0
Venue
arXiv.org
Last Checked
5 months ago
Abstract
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.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Software Engineering
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Microservices: yesterday, today, and tomorrow
π
π
The Cartographer
A Survey of Machine Learning for Big Code and Naturalness
R.I.P.
π»
Ghosted
An Overview on Smart Contracts: Challenges, Advances and Platforms
R.I.P.
π»
Ghosted
Slither: A Static Analysis Framework For Smart Contracts
R.I.P.
π»
Ghosted
ContractFuzzer: Fuzzing Smart Contracts for Vulnerability Detection
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted