7 papers
DeepGuard: Secure Code Generation via Multi-Layer Semantic Aggregation
Li Huang, Zhongxin Liu, Yifan Wu +6
Large Language Models (LLMs) for code generation can replicate insecure patterns from their training data. To mitigate this, a common strategy for security hardening is to fine-tun…
Persistent Cross-Attempt State Optimization for Repository-Level Code Generation
Ruwei Pan, Jiangshuai Wang, Qisheng Zhang +6
Large language models (LLMs) have achieved substantial progress in repository-level code generation. However, solving the same repository-level task often requires multiple attempt…
Toward Executable Repository-Level Code Generation via Environment Alignment
Ruwei Pan, Junlei Shen, Linhao Wu +5
Large language models (LLMs) have achieved strong performance on code generation, but existing methods still struggle with repository-level code generation under executable validat…
Boosting Redundancy-based Automated Program Repair by Fine-grained Pattern Mining
Jiajun Jiang, Fengjie Li, Zijie Zhao +5
Redundancy-based automated program repair (APR), which generates patches by referencing existing source code, has gained much attention since they are effective in repairing real-w…
Improving Compiler Bug Isolation by Leveraging Large Language Models
Yixian Qi, Jiajun Jiang, Fengjie Li +3
Compilers play a foundational role in building reliable software systems, and bugs within them can lead to catastrophic consequences. The compilation process typically involves hun…
Empirical Evaluation of Large Language Models in Automated Program Repair
Jiajun Sun, Fengjie Li, Xinzhu Qi +2
The increasing prevalence of software bugs has made automated program repair (APR) a key research focus. Large language models (LLMs) offer new opportunities for APR, but existing…