4 papers
Learning Globally Reusable Skills for Coding Agents
Chen Yang, Jiashuo Tian, Ziqi Wang +3
Automated skill evolution enables Large Language Model (LLM) agents to continuously improve without expensive retraining. However, existing approaches typically treat skill evoluti…
Clarifying Semantics of In-Context Examples for Unit Test Generation
Chen Yang, Lin Yang, Ziqi Wang +3
Recent advances in large language models (LLMs) have enabled promising performance in unit test generation through in-context learning (ICL). However, the quality of in-context exa…
Reflective Unit Test Generation for Precise Type Error Detection with Large Language Models
Chen Yang, Ziqi Wang, Yanjie Jiang +4
Type errors in Python often lead to runtime failures, posing significant challenges to software reliability and developer productivity. Existing static analysis tools aim to detect…
Advancing Code Coverage: Incorporating Program Analysis with Large Language Models
Chen Yang, Junjie Chen, Bin Lin +2
Automatic test generation plays a critical role in software quality assurance. While the recent advances in Search-Based Software Testing (SBST) and Large Language Models (LLMs) ha…