10 papers
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…
SAGE: Signal-Amplified Guided Embeddings for LLM-based Vulnerability Detection
Zhengyang Shan, Xu Qian, Jiayun Xin +5
Software vulnerabilities are a primary threat to modern infrastructure. While static analysis and Graph Neural Networks have long served as the foundation for vulnerability detecti…
Contamination Means Overestimation? A Fine-Grained Empirical Study in Code Intelligence
Zhen Yang, Hongyi Lin, Yifan He +7
In recent years, code intelligence has gained increasing importance in the field of automated software engineering. Meanwhile, the widespread adoption of Pretrained Language Models…
Parameter-Efficient Fine-Tuning with Attributed Patch Semantic Graph for Automated Patch Correctness Assessment
Zhenyu Yang, Jingwen Wu, Zhen Yang +1
Automated program repair (APR) aims to automatically repair program errors without human intervention, and recent years have witnessed a growing interest on this research topic. Wh…
R2ComSync: Improving Code-Comment Synchronization with In-Context Learning and Reranking
Zhen Yang, Hongyi Lin, Xiao Yu +5
Code-Comment Synchronization (CCS) aims to synchronize the comments with code changes in an automated fashion, thereby significantly reducing the workload of developers during soft…