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.…
Explainable Fault Localization for Programming Assignments via LLM-Guided Annotation
Fang Liu, Tianze Wang, Li Zhang +3
Providing timely and personalized guidance for students' programming assignments, offers significant practical value for helping students complete assignments and enhance their lea…
FastFixer: An Efficient and Effective Approach for Repairing Programming Assignments
Fang Liu, Zhenwei Liu, Qianhui Zhao +6
Providing personalized and timely feedback for student's programming assignments is useful for programming education. Automated program repair (APR) techniques have been used to fi…
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…
Peer-aided Repairer: Empowering Large Language Models to Repair Advanced Student Assignments
Qianhui Zhao, Fang Liu, Li Zhang +6
Automated generation of feedback on programming assignments holds significant benefits for programming education, especially when it comes to advanced assignments. Automated Progra…