CoreCast: Leveraging Project Metrics to Predict Core Contributor Trends in Open Source C57
The collaborative model of open-source software (OSS) development significantly enhances efficiency and fosters innovation by enabling diverse global contributors to collaborate seamlessly.Core contributors, who provide the majority of code commits, are crucial for maintaining project direction, quality, and momentum.Despite their importance, there is limited research on the dynamics and prediction of changes in core contributors over time, which is essential for sustaining project growth and stability.To bridge this gap, we introduce CoreCast, an innovative predictive model designed to forecast future core contributor numbers using comprehensive project data.By analyzing multidimensional metrics from high-quality OSS projects, CoreCast trains models that outperform traditional methods, achieving a mean absolute error (MAE) of 0.7866.Our findings reveal seven significant growth trends that are crucial for understanding and sustaining OSS project development.All data and scripts are open-sourced, providing valuable resources for future research and further advancements in the field.
Authors
- Wu Lian (ORCID: https://orcid.org/0000-0003-0183-7542)
- Q. Chelsea Song (ORCID: https://orcid.org/0000-0003-0910-1281)
- Zhiling Zhu (ORCID: https://orcid.org/0000-0003-3878-0391)
- Tieming Chen (ORCID: https://orcid.org/0000-0003-4664-3311)
Institutions
- Zhejiang University of Science and Technology (CN)
- Zhejiang University of Technology (CN)
Publication Details
- Journal
- Proceedings/Proceedings of the ... International Conference on Software Engineering and Knowledge Engineering
- Published
- 2024-10-28
- DOI
- https://doi.org/10.18293/seke2024-010
- Primary Topic
- Scientific Computing and Data Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China