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Wed 30 Apr 2025 11:15 - 11:30 at 210 - AI for User Experience Chair(s): Chunyang Chen

In industrial practice, UI (User Interface) functional bugs typically manifest as inconsistent UI input and corresponding response. Such bugs can deteriorate user experiences and are, therefore, a major target of industrial testing practice. For a long time, testing for UI functional bugs has relied on rule-based methods, which are labor-intensive for rule development and maintenance. Given that the UI functional bugs typically manifest where an app’s response deviates from the user’s expectations, we proposed the key point of reducing human efforts lies in simulating human expectations. Due to the vast in-the-wild knowledge of large language models (LLMs), they are well-suited for this simulation. By leveraging LLMs as UI testing oracle, we proposed KuiTest, the first rule-free UI functional testing tool we designed for Company M, one of the largest E-commerce app providers serving over 600 million users. KuiTest can automatically predict the effect of UI inputs and verify the post-interaction UI response. We evaluate the design of KuiTest via a set of ablation experiments. Moreover, real-world deployments demonstrate that KuiTest can effectively detect previously unknown UI functional bugs and significantly improve the efficiency of GUI testing.

Wed 30 Apr

Displayed time zone: Eastern Time (US & Canada) change

11:00 - 12:30
11:00
15m
Talk
Automated Generation of Accessibility Test Reports from Recorded User TranscriptsAward Winner
Research Track
Syed Fatiul Huq University of California, Irvine, Mahan Tafreshipour University of California at Irvine, Kate Kalcevich Fable Tech Labs Inc., Sam Malek University of California at Irvine
11:15
15m
Talk
KuiTest: Leveraging Knowledge in the Wild as GUI Testing Oracle for Mobile Apps
SE In Practice (SEIP)
Yongxiang Hu Fudan University, Yu Zhang Meituan, Xuan Wang Fudan University, Yingjie Liu School of Computer Science, Fudan University, Shiyu Guo Meituan, Chaoyi Chen Meituan, Xin Wang Fudan University, Yangfan Zhou Fudan University
11:30
15m
Talk
GUIWatcher: Automatically Detecting GUI Lags by Analyzing Mobile Application Screencasts
SE In Practice (SEIP)
Wei Liu Concordia University, Montreal, Canada, Feng Lin Concordia University, Linqiang Guo Concordia University, Tse-Hsun (Peter) Chen Concordia University, Ahmed E. Hassan Queen’s University
11:45
15m
Talk
GUIDE: LLM-Driven GUI Generation Decomposition for Automated Prototyping
Demonstrations
Kristian Kolthoff Institute for Software and Systems Engineering, Clausthal University of Technology, Felix Kretzer human-centered systems Lab (h-lab), Karlsruhe Institute of Technology (KIT) , Christian Bartelt , Alexander Maedche Human-Centered Systems Lab, Karlsruhe Institute of Technology, Simone Paolo Ponzetto Data and Web Science Group, University of Mannheim
Pre-print
12:00
15m
Talk
Agent for User: Testing Multi-User Interactive Features in TikTok
SE In Practice (SEIP)
Sidong Feng Monash University, Changhao Du Jilin University, huaxiao liu Jilin University, Qingnan Wang Jilin University, Zhengwei Lv ByteDance, Gang Huo ByteDance, Xu Yang ByteDance, Chunyang Chen TU Munich
12:15
7m
Talk
Bug Analysis in Jupyter Notebook Projects: An Empirical Study
Journal-first Papers
Taijara Santana Federal University of Bahia, Paulo Silveira Neto Federal University Rural of Pernambuco, Eduardo Santana de Almeida Federal University of Bahia, Iftekhar Ahmed University of California at Irvine
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