3 papers
cs.SE2025
RepoDebug: Repository-Level Multi-Task and Multi-Language Debugging Evaluation of Large Language Models
Jingjing Liu, Zeming Liu, Zihao Cheng +7
Large Language Models (LLMs) have exhibited significant proficiency in code debugging, especially in automatic program repair, which may substantially reduce the time consumption o…
cs.SE2025
Flow2Code: Evaluating Large Language Models for Flowchart-based Code Generation Capability
Mengliang He, Jiayi Zeng, Yankai Jiang +4
While large language models (LLMs) show promise in code generation, existing benchmarks neglect the flowchart-based code generation. To promote further research on flowchart-based…
cs.CL2025
Mis-prompt: Benchmarking Large Language Models for Proactive Error Handling
Jiayi Zeng, Yizhe Feng, Mengliang He +5
Large language models (LLMs) have demonstrated significant advancements in error handling. Current error-handling works are performed in a passive manner, with explicit error-handl…