GUIWatcher: Automatically Detecting GUI Lags by Analyzing Mobile Application Screencasts
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arXiv
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| Auteurs principaux: | , , , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866913681659396096 |
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| author | Liu, Wei Lin, Feng Guo, Linqiang Chen, Tse-Hsun Hassan, Ahmed E. |
| author_facet | Liu, Wei Lin, Feng Guo, Linqiang Chen, Tse-Hsun Hassan, Ahmed E. |
| contents | 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 accuracy 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_04202 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | GUIWatcher: Automatically Detecting GUI Lags by Analyzing Mobile Application Screencasts Liu, Wei Lin, Feng Guo, Linqiang Chen, Tse-Hsun Hassan, Ahmed E. Software Engineering 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 accuracy 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. |
| title | GUIWatcher: Automatically Detecting GUI Lags by Analyzing Mobile Application Screencasts |
| topic | Software Engineering |
| url | https://arxiv.org/abs/2502.04202 |