7 papers · 1 filter
CausalRepair: Bridging the Causality Gap in Large Language Model-Based Automated Program Repair via Dual-Slicing
Linhao Wu, Yizhou Chen, Zhen Yang +2
Automated Program Repair (APR) has recently benefited from Large Language Models (LLMs), yet their effectiveness heavily depends on repair context. Existing LLM-based APR methods s…
DebugRepair: Enhancing LLM-Based Automated Program Repair via Self-Directed Debugging
Linhao Wu, Yifei Pei, Zhen Yang +9
Automated Program Repair (APR) has benefited from the code understanding and generation capabilities of Large Language Models (LLMs). Existing feedback-based APR methods iterativel…
Search-Induced Issues in Web-Augmented LLM Code Generation: Detecting and Repairing Error-Inducing Pages
Guoqing Wang, Zeyu Sun, Xiaofei Xie +4
Web-augmented large language models (LLMs) offer promising capabilities for automatic code generation. However, integrating live web search exposes models to unreliable or maliciou…
Directional Diffusion-Style Code Editing Pre-training
Qingyuan Liang, Zeyu Sun, Qihao Zhu +6
Code pre-trained models have shown promising effectiveness in various software engineering tasks. Among these tasks, many tasks are related to software evolution and/or code editin…
Condor: A Code Discriminator Integrating General Semantics with Code Details
Qingyuan Liang, Zhao Zhang, Chen Liu +9
LLMs demonstrate significant potential across various software engineering tasks. However, they still face challenges in generating correct code on the first attempt when addressin…
GramTrans: A Better Code Representation Approach in Code Generation
Zhao Zhang, Qingyuan Liang, Zeyu Sun +6
Code generation has shown great promise in assisting software development. A fundamental yet underexplored question is how the choice of code representation affects model performan…