GUIWatcher: Automatically Detecting GUI Lags by Analyzing Mobile Application Screencasts
This program is tentative and subject to change.
The Graphical User Interface (GUI) plays a central role in mobile applications, directly affecting usability and user satisfaction. Poor GUI performance, such as lag or unresponsiveness, can lead to negative user experience and decreased mobile application (app) ratings. In this paper, we present GUIWatcher, a framework designed to detect GUI lags by analyzing screencasts recorded during mobile app testing. GUIWatcher uses computer vision techniques to identify three types of lag-inducing frames (i.e., janky frames, long loading frames, and frozen frames) and prioritizes the most severe ones that significantly impact user experience. Our approach was evaluated using real-world mobile application tests, achieving high results in detecting GUI lags in screencasts, with an average precision of 0.91 and recall of 0.96. The comprehensive bug reports generated from the lags detected by GUIWatcher help developers focus on the more critical issues and debug them efficiently. Additionally, GUIWatcher has been deployed in a real-world production environment, continuously monitoring app performance and successfully identifying critical GUI performance issues. By offering a practical solution for identifying and addressing GUI lags, GUIWatcher contributes to enhancing user satisfaction and the overall quality of mobile apps.
This program is tentative and subject to change.
Wed 30 AprDisplayed time zone: Eastern Time (US & Canada) change
11:00 - 12:30 | AI for User ExperienceSE In Practice (SEIP) / Demonstrations / Journal-first Papers / Research Track at 210 Chair(s): Chunyang Chen TU Munich | ||
11:00 15mTalk | 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 15mTalk | 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 15mTalk | 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 15mTalk | 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 | ||
12:00 15mTalk | 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 7mTalk | 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 |