Xuan Wang

Xuan Wang

PhD Student

Fudan University

Research Interests

Automated GUI Testing
LLM-driven Testing Agents

About

I am a PhD student at the College of Computer Science and Artificial Intelligence, Fudan University, advised by Prof. Yangfan Zhou.

My research focuses on software engineering for mobile applications, particularly automated GUI testing and LLM-driven testing agents.

Selected Publications

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SwipeGen: Bridging the Execution Gap in GUI Agents via Human-like Swipe Synthesis

Xuan Wang*, Siyuan Su*, Quantong Fu*, Yongxiang Hu, Yangfan Zhou

arXiv, Computer Vision and Pattern Recognition (cs.CV), 2601.18305

This work decomposes human swipe gestures into multiple quantifiable dimensions and proposes an automated pipeline SwipeGen to synthesize human-like swipe interactions through GUI exploration and proposes GUISwiper, a GUI agent with enhanced interaction execution capabilities.

From Redundancy to Efficiency: Exploiting Shared UI Interactions towards Efficient LLM-Based Testing

Xuan Wang, Yingchuan Wang, Yongxiang Hu, Yu Zhang, Hailiang Jin, Shiyu Guo, Juxing Yuan, Yangfan Zhou

2025 40th IEEE/ACM International Conference on Automated Software Engineering (ASE'25)

TestWeaver exploits shared UI interactions across test cases to enhance the efficiency of LLM-based UI testing agents, significantly reducing costs and improving testing speed.

AUITestAgent: Automatic Requirements Oriented GUI Function Testing

Yongxiang Hu, Xuan Wang, Yingchuan Wang, Yu Zhang, Shiyu Guo, Chaoyi Chen, Xin Wang, Yangfan Zhou

arXiv, Software Engineering (cs.SE), 2407.09018

AUITestAgent is the first automatic, natural language-driven GUI testing tool for mobile apps, capable of fully automating the entire process of GUI interaction and function verification.

News

2025-09

Our work is accepted by the Industry Showcase Track of The 40th IEEE/ACM International Conference on Automated Software Engineering (ASE'25). ๐ŸŽ‰

2025-09

Starting my PhD at Fudan University

2024-12

Our work is accepted by the Software in Practice track of The 47th ACM/IEEE International Conference on Software Engineering (ICSE-SEIP'25). ๐ŸŽ‰

2023-12

Our work is accepted by the Software in Practice track of The 46th ACM/IEEE International Conference on Software Engineering (ICSE-SEIP'24). ๐ŸŽ‰

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