5 papers · 1 filter
SWE-Doctor: Guiding Software Engineering Agents with Runtime Diagnosis from Multi-Faceted Bug Reproduction Tests
Yaoqi Guo, Yang Liu, Jie M. Zhang +3
Large language model (LLM)-based software engineering agents are increasingly developed to resolve software issues by generating patches from issue reports and code repositories. B…
EET: Experience-Driven Early Termination for Cost-Efficient Software Engineering Agents
Yaoqi Guo, Ying Xiao, Jie M. Zhang +4
Software engineering (SE) agents powered by large language models are increasingly adopted in practice, yet they often incur substantial monetary cost. We introduce EET, an experie…
LLMs Are Not a Silver Bullet: A Case Study on Software Fairness
Xinyue Li, Sixuan Li, Ying Xiao +4
Fairness is a critical requirement for human-related, high-stakes software systems, motivating extensive research on bias mitigation. Prior work has largely focused on tabular data…
LLM-Powered Test Case Generation for Detecting Bugs in Plausible Programs
Kaibo Liu, Zhenpeng Chen, Yiyang Liu +7
Detecting tricky bugs in plausible programs, those that pass existing test suites yet still contain bugs, remains a significant challenge in software testing. To address this probl…
Personality-Guided Code Generation Using Large Language Models
Yaoqi Guo, Zhenpeng Chen, Jie M. Zhang +2
Code generation, the automatic creation of source code from natural language descriptions, has garnered significant attention due to its potential to streamline software developmen…