3 papers
cs.SE2026
DynaFix: Iterative Automated Program Repair Driven by Execution-Level Dynamic Information
Zhili Huang, Ling Xu, Chao Liu +5
Automated Program Repair (APR) aims to automatically generate correct patches for buggy programs. Recent approaches leveraging large language models (LLMs) have shown promise but f…
cs.SE2026
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…
cs.SE2025
Fixing Function-Level Code Generation Errors for Foundation Large Language Models
Hao Wen, Yueheng Zhu, Chao Liu +3
Function-level code generation leverages foundation Large Language Models (LLMs) to automatically produce source code with expected functionality. It has been widely investigated a…