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Vision-Based Mobile App GUI Testing: A Survey

delete2026-04-01
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PRE
AI
S
Shengcheng Yu
房春荣 (Chunrong Fang) *
Z
Ziyuan Tuo
Q
Quanjun Zhang
C
Chunyang Chen
陈振宇 (Zhenyu Chen)
Z
Zhendong Su
DOI:10.1145/3773027delete
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Abstract

Abstract

En 中文
Graphical User Interface (GUI) has become one of the most significant parts of mobile applications (apps). It is a direct bridge between mobile apps and end users, which directly affects the end user's experience. Neglecting GUI quality can undermine the value and effectiveness of the entire mobile app solution. Significant research efforts have been devoted to GUI testing, one effective method to ensure mobile app quality. By conducting rigorous GUI testing, developers can ensure that the visual and interactive elements of the mobile apps not only meet functional requirements but also provide a seamless and user-friendly experience. However, traditional solutions, relying on the source code or layout files, have met challenges in both effectiveness and efficiency due to the gap between what is obtained and what app GUI actually presents. Vision-based mobile app GUI testing approaches emerged with the development of computer vision technologies and have achieved promising progress. In this survey article, we provide a comprehensive investigation of the state-of-the-art techniques on 271 articles, among which 92 are vision-based studies. This survey covers different topics of GUI testing, like GUI test generation, GUI test record & replay, GUI testing framework, and so on. In particular, we highlight the emerging role of vision-based techniques and analyze how they reshape traditional approaches to mobile app GUI testing. Based on the investigation of existing studies, we outline the challenges and opportunities of (vision-based) mobile app GUI testing and propose promising research directions with the combination of emerging techniques.
Keywords:
Mobile app testing
GUI testing
GUI image understanding

Journal

ACM Computing Surveys cover
ACM Computing Surveys
IF:
28
Papers:
2.4K
Citations:
3.5W

Organization

S
swiss federal institutes of technology domain
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9.0W
Papers: 8.0W
Citations: 163
N
nanjing university
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7.7W
Papers: 5.6W
Citations: 87
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monash university
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8.6K
Papers: 3.8K
Citations: 0
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