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cs.AI2025
Intention Chain-of-Thought Prompting with Dynamic Routing for Code Generation
Shen Li, Li Huang, Shaoxiong Zhan +4
Large language models (LLMs) exhibit strong generative capabilities and have shown great potential in code generation. Existing chain-of-thought (CoT) prompting methods enhance mod…
cs.SE2025
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.SE2025
PSearch: Search-based Patch Generation in the Era of LLM-based Automated Program Repair
Haichuan Hu, Ye Shang, Weifeng Sun +1
Large Language Models (LLMs) have substantially advanced Automated Program Repair (APR), yet most existing LLM-based APR methods still rely on trial-and-error to generate patches.…