Zhe Liu

Zhe Liu is an Assistant Scientist at the Institute of Software, Chinese Academy of Sciences, and is affiliated with the University of Chinese Academy of Sciences. With a PhD from the University of Chinese Academy of Sciences, Liu focuses on innovative research at the intersection of software engineering, mobile testing, and artificial intelligence.

Liu's research interests span multiple areas including:

• Software Engineering
• Mobile Testing
• Deep Learning
• Human-Computer Interaction
• Machine Learning
• Computer Vision
• UI Testing
• Crowd Testing

Liu applies AI and lightweight program analysis technology in several key directions:

• AI/LLM-assisted automated mobile app development (requirement elicitation, app GUI testing, usability, bug replay)
• Human-machine collaborative testing (testing guides for testers)
• AI-empowered mining of software repositories (issue report mining)

Liu has published 15 papers at top international Software Engineering and Human-Computer Interaction conferences/journals (CCF-A) with over 1,300 Google Scholar citations. The research shows a strong trend toward leveraging large language models for mobile app testing, with significant contributions in automated GUI testing, crash reproduction, and text input generation.

Notable scientific achievements include:

• ACM Student Research Competition (SRC) 2023 Grand Finals Winners, 1st Place, Graduate Category
• Best Paper Honourable Mention in CHI'24
• ACM Student Research Competition (SRC) at ICSE 2022, 1st Place
• ACM Student Research Competition (SRC) at ASE 2020, 1st Place
• Excellent Doctoral Dissertation of Chinese Academy of Sciences in 2024

Liu has served as a program committee member for ASE 2025 and has been involved in multiple research projects funded by the National Key Research and Development Program of China, National Natural Science Foundation of China, and Populus Innovation Research Funding. Current research focuses on advancing the integration of large language models with mobile application testing frameworks to improve app quality and user experience.