3 papers
cs.SE2026
SGCR: A Specification-Grounded Framework for Trustworthy LLM Code Review
Kai Wang, Bingcheng Mao, Shuai Jia +4
Automating code review with Large Language Models (LLMs) shows immense promise, yet practical adoption is hampered by their lack of reliability, context-awareness, and control. To…
cs.SE2026
ArchAgent: Scalable Legacy Software Architecture Recovery with LLMs
Rusheng Pan, Bingcheng Mao, Tianyi Ma +1
Recovering accurate architecture from large-scale legacy software is hindered by architectural drift, missing relations, and the limited context of Large Language Models (LLMs). We…
cs.AI2026
GUITester: Enabling GUI Agents for Exploratory Defect Discovery
Yifei Gao, Jiang Wu, Xiaoyi Chen +5
Exploratory GUI testing is essential for software quality but suffers from high manual costs. While Multi-modal Large Language Model (MLLM) agents excel in navigation, they fail to…