Towards Early Warning and Migration of High-Risk Dormant Open-Source Software Dependencies
Dormant open-source software (OSS) dependencies are no longer maintained or actively developed, their related code components are more vulnerable and error-prone since they can hardly keep up with evolving software dependents. Presently, their migration remains costly and challenging for practitioners. To tackle such a challenge, we intend to characterize, predict, and automatically migrate high-risk dormant OSS dependencies. Our pilot study of 4,945 Maven dependencies reveals over half of them are dormant, and 12.15% pose a high security risk. These high-risk dependencies can be predicted early based on their version release and usage characteristics. They are rarely migrated by developers, and simple one-to-one API migrations can be achieved with little context using Large Language Models (LLMs). Future research will be conducted on a more complete dataset, incorporate socio-technical features for improved high-risk prediction, and fine-tune a migration code generator.
Authors
- Lizhi Cai
- Zijie Huang (ORCID: https://orcid.org/0000-0002-8911-9889)
- Xuan Mao
- Kang Yang (ORCID: https://orcid.org/0000-0002-5863-1003)
Institutions
- East China University of Science and Technology (CN)
Publication Details
- Published
- 2025-04-27
- DOI
- https://doi.org/10.1109/icse-nier66352.2025.00030
- Citations
- 1
- Primary Topic
- Scientific Computing and Data Management
- Type
- article
- Field-Weighted Citation Impact
- 4.17
Funders
- China Postdoctoral Science Foundation
- State Grid Hebei Energy Technology Service