This study is concluded.
- The study has been published at ICSE 2026 (publication).
- Publication website
We want to thank all participants, it was a great experience to interview you. We appreciate you sharing your knowledge, experience, expertise, and most importantly your valuable time that you have generously given.
We hope that with this work and your contribution, both the research and open source community are one step closer to more secure and trustworthy software.
We perform a need-finding interview study with 22 open source maintainers to explore what makes the abandonment of certain dependencies impactful to their project, as well as their information needs and design requirements for such an automated notification tool.
Our results show that the classifier is effective at predicting whether a dependency’s abandonment would be impactful to a project, and that theory-based explanations given by the LLM are useful to developers when making judgments about the potential impactfulness of a given dependency’s abandonment.
Researchers
| Courtney Miller | PhD Student (Carnegie Mellon University) |
| Hao He | PhD Student (Carnegie Mellon University) |
| Weigen Chen | Carnegie Mellon University |
| Elizabeth Lin | PhD Student (North Carolina State University) |
| Chenyang Yang | PhD Student (Carnegie Mellon University) |
| Bogdan Vasilescu | Associate Professor (Carnegie Mellon University) |
| Christian Kästner | Associate Professor (Carnegie Mellon University) |