7 citations · 7 across the 4 of their papers we have counts for
5 papers
Predicting Developer Acceptance of AI-Generated Code Suggestions
Jing Jiang, Liehao Li, Jinyun Hou +2
AI-assisted programming tools are widely adopted, yet their practical utility is often undermined by undesired suggestions that interrupt developer workflows and cause frustration.…
An Empirical Study on Failures in Automated Issue Solving
Simiao Liu, Fang Liu, Liehao Li +4
Automated issue solving seeks to autonomously identify and repair defective code snippets across an entire codebase. SWE-Bench has emerged as the most widely adopted benchmark for…
LLM-Driven Collaborative Model for Untangling Commits via Explicit and Implicit Dependency Reasoning
Bo Hou, Xin Tan, Kai Zheng +3
Atomic commits, which address a single development concern, are a best practice in software development. In practice, however, developers often produce tangled commits that mix unr…
Revolutionizing Newcomers' Onboarding Process in OSS Communities: The Future AI Mentor
Xin Tan, Xiao Long, Yinghao Zhu +3
Onboarding newcomers is vital for the sustainability of open-source software (OSS) projects. To lower barriers and increase engagement, OSS projects have dedicated experts who prov…
How far are AI-powered programming assistants from meeting developers' needs?
Xin Tan, Xiao Long, Xianjun Ni +3
Recent In-IDE AI coding assistant tools (ACATs) like GitHub Copilot have significantly impacted developers' coding habits. While some studies have examined their effectiveness, the…