collaborators

21 papers

cs.SE2026

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…

cs.SE2026

Towards Iterative End-to-End Software Development: A Feature-Driven Multi-Agent Framework

Junwei Liu, Chen Xu, Chong Wang +5

Recent advances in large language model agents offer the promise of automating end-to-end software development from natural language requirements. However, existing approaches larg…

cs.AI2026

Taming System Complexity: Demystifying Software Engineering Agents in Diagnosing Linux Kernel Faults

Zhenhao Zhou, Zhuochen Huang, Yike He +5

The Linux kernel is a critical system, serving as the foundation for numerous systems. Bugs in the Linux kernel can cause serious consequences, affecting billions of users. Fault l…

cs.SE2026

Project-Level C-to-Rust Translation via Pointer Knowledge Graphs

Zhiqiang Yuan, Wenjun Mao, Zhuo Chen +4

Translating C code into safe Rust is an effective way to ensure memory safety. Compared to rule-based approaches, which often produce largely unsafe Rust code, LLM-based methods ge…

cs.CY2026

Fairness Testing of Large Language Models in Role-Playing

Xinyue Li, Zhenpeng Chen, Jie M. Zhang +6

Large Language Models (LLMs) have become foundational in modern language-driven software applications, profoundly influencing daily life. A critical technique in leveraging their p…

cs.SE2026

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…