6 papers
GraphAlignCoder: Aligning Program and Proof Graphs for Code Generation
Yueke Zhang, Zihan Fang, Kevin Leach +1
Code large language models (LLMs) can generate syntactically plausible programs that nevertheless violate hidden semantic constraints. Existing execution-feedback training methods…
AgentForge: An Immersive Role-Playing Platform for Learning Agentic Software Engineering
Zihan Fang, Yueke Zhang, Yu Huang
Agentic AI is increasingly used to coordinate planning, implementation, review, and testing in software development, yet it often offers limited transparency into its decisions and…
SCOPE: Leveraging Subgoal Critiques for Code Generation
Yueke Zhang, Yifan Zhang, Zihan Fang +3
Code generation with large language models (LLMs) remains unreliable because generated programs can appear correct while still violating key semantic requirements in the natural la…
From Conversation to Contribution: Characterizing Coding Agent in Open-Source Software
Zihan Fang, Yueke Zhang, Ningzhi Tang +3
AI coding assistants such as GitHub Copilot and Cursor have evolved from code-suggestion tools into conversational collaborators, enabling vibe-coding workflows in which developers…
Programming by Chat: A Large-Scale Behavioral Analysis of 11,579 Real-World AI-Assisted IDE Sessions
Ningzhi Tang, Chaoran Chen, Zihan Fang +6
IDE-integrated AI coding assistants, which operate conversationally within developers' working codebases with access to project context and multi-file editing, are rapidly reshapin…
DPO-F+: Aligning Code Repair Feedback with Developers' Preferences
Zihan Fang, Yifan Zhang, Yueke Zhang +2
Large Language Models (LLMs) are increasingly used in software engineering tasks, especially code repair. However, developers often struggle to interpret model outputs, limiting ef…