14 papers
Maintenance Signals in AI-Assisted GitHub Repositories: Evidence from GenAI Adopters
Rikuto Tsuchida, Youmei Fan, Kazumasa Shimari +3
Generative artificial intelligence (GenAI) can reduce code-generation effort, but it may shift work to documentation, validation, debugging, and maintenance. We study observable ma…
A Longitudinal Analysis of Good First Issue Practices and Newcomer Pull Requests in Popular OSS Projects
Hirotatsu Hoshikawa, Hidetake Tanaka, Kazumasa Shimari +2
Open-source software (OSS) projects rely on effective newcomer onboarding to sustain their communities. OSS projects widely adopt "good first issue" (GFI) labels to highlight begin…
How Do Developers Use Migration Guides? A Case Study of Log4j
Takahiro Monno, Kazumasa Shimari, Tetsuya Kanda +2
Migration guides are a form of software documentation that helps developers address breaking changes introduced in library version updates. Prior studies have examined documents su…
How AI Coding Agents Communicate: A Study of Pull Request Description Characteristics and Human Review Responses
Kan Watanabe, Rikuto Tsuchida, Takahiro Monno +5
The rapid adoption of large language models has led to the emergence of AI coding agents that autonomously create pull requests on GitHub. However, how these agents differ in their…
Forecasting Developer Environments with GenAI: A Research Perspective
Raula Gaikovina Kula, Christoph Treude, Xing Hu +28
Generative Artificial Intelligence (GenAI) models are achieving remarkable performance in various tasks, including code generation, testing, code review, and program repair. The ab…
Who Writes the Docs in SE 3.0? Agent vs. Human Documentation Pull Requests
Kazuma Yamasaki, Joseph Ayobami Joshua, Tasha Settewong +3
As software engineering moves toward SE3.0, AI agents are increasingly used to carry out development tasks and contribute changes to software projects. It is therefore important to…