3 papers
cs.SE2025
Understanding Code Agent Behaviour: An Empirical Study of Success and Failure Trajectories
Oorja Majgaonkar, Zhiwei Fei, Xiang Li +2
The increasing deployment of Large Language Model (LLM) agents for complex software engineering tasks has created a need to understand their problem-solving behaviours beyond simpl…
cs.SE2025
Generative AI for Testing of Autonomous Driving Systems: A Survey
Qunying Song, He Ye, Mark Harman +1
Autonomous driving systems (ADS) have been an active area of research, with the potential to deliver significant benefits to society. However, before large-scale deployment on publ…
cs.SE2025
Automated Repair of Ambiguous Problem Descriptions for LLM-Based Code Generation
Haoxiang Jia, Robbie Morris, He Ye +2
The growing use of large language models (LLMs) has increased the importance of natural language (NL) in software engineering. However, ambiguity of NL can harm software quality, a…