4 papers
LLM-Driven Collaborative Model for Untangling Commits via Explicit and Implicit Dependency Reasoning
Bo Hou, Xin Tan, Kai Zheng +3
The paper introduces ColaUntangle, a framework that uses multiple LLM-driven agents to identify both explicit and implicit dependencies among code changes in order to separate tang…
Beyond Functional Correctness: Exploring Hallucinations in LLM-Generated Code
Fang Liu, Yang Liu, Lin Shi +5
The rise of Large Language Models (LLMs) has significantly advanced various applications on software engineering tasks, particularly in code generation. Despite the promising perfo…
RepoScope: Leveraging Call Chain-Aware Multi-View Context for Repository-Level Code Generation
Yang Liu, Li Zhang, Fang Liu +6
Repository-level code generation aims to generate code within the context of a specified repository. Existing approaches typically employ retrieval-augmented generation (RAG) techn…
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…