14 papers
Towards Reliable C-to-Rust Translation with Rule-Guided Reasoning and Reinforcement Learning
Feng Luo, Jiachen Liu, Cuiyun Gao +2
The migration of legacy C programs to Rust has become an important direction for improving software memory safety while alleviating the high cost of manual rewriting. Leveraging la…
Dependency-Guided Repository-Level C-to-Rust Translation with Reinforcement Alignment
Jia Feng, Wenjie Gan, Cuiyun Gao +5
Automating C-to-Rust migration is critical for improving software security without sacrificing performance. Traditional rule-based methods struggle with diverse C idioms, often pro…
SR-Eval: Evaluating LLMs on Code Generation under Stepwise Requirement Refinement
Zexun Zhan, Shuzheng Gao, Ruida Hu +1
Large language models (LLMs) have achieved remarkable progress in code generation. However, existing benchmarks mainly formalize the task as a static, single-turn problem, overlook…
SPVR: syntax-to-prompt vulnerability repair based on large language models
Ruoke Wang, Zongjie Li, Cuiyun Gao +3
Purpose: In the field of vulnerability repair, previous research has leveraged pretrained models and LLM-based prompt engineering, among which LLM-based approaches show better gene…
Automated Prompt Generation for Code Intelligence: An Empirical study and Experience in WeChat
Kexing Ji, Shiyun Fu, Cuiyun Gao +4
Large Code Models (LCMs) show potential in code intelligence, but their effectiveness is greatly influenced by prompt quality. Current prompt design is mostly manual, which is time…
RepoMasterEval: Evaluating Code Completion via Real-World Repositories
Qinyun Wu, Chao Peng, Pengfei Gao +9
With the growing reliance on automated code completion tools in software development, the need for comprehensive evaluation benchmarks has become critical. Existing benchmarks focu…