Vision-Based Mobile App GUI Testing: A Survey Article Swipe
Shengcheng Yu
,
Chunrong Fang
,
Ziyuan Tuo
,
Quanjun Zhang
,
Chunyang Chen
,
Zhenyu Chen
,
Zhendong Su
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2310.13518
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2310.13518
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 paper, we provide a comprehensive investigation of the state-of-the-art techniques on 271 papers, 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, etc. Specifically, the research emphasis of this survey is placed mostly on how vision-based techniques outperform traditional solutions and have gradually taken a vital place in the GUI testing field. 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.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2310.13518
- https://arxiv.org/pdf/2310.13518
- OA Status
- green
- Cited By
- 1
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4387892121
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4387892121Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.2310.13518Digital Object Identifier
- Title
-
Vision-Based Mobile App GUI Testing: A SurveyWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-10-20Full publication date if available
- Authors
-
Shengcheng Yu, Chunrong Fang, Ziyuan Tuo, Quanjun Zhang, Chunyang Chen, Zhenyu Chen, Zhendong SuList of authors in order
- Landing page
-
https://arxiv.org/abs/2310.13518Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2310.13518Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2310.13518Direct OA link when available
- Concepts
-
Graphical user interface testing, Computer science, Graphical user interface, Mobile apps, Human–computer interaction, User interface, Quality (philosophy), User experience design, Multimedia, World Wide Web, User interface design, Operating system, Epistemology, PhilosophyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1Per-year citation counts (last 5 years)
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.outline | 229 |
| abstract_inverted_index.papers, | 164 |
| abstract_inverted_index.propose | 241 |
| abstract_inverted_index.provide | 91, 154 |
| abstract_inverted_index.quality | 36 |
| abstract_inverted_index.relying | 100 |
| abstract_inverted_index.replay, | 187 |
| abstract_inverted_index.testing | 134, 189, 219, 239 |
| abstract_inverted_index.However, | 97 |
| abstract_inverted_index.achieved | 146 |
| abstract_inverted_index.actually | 128 |
| abstract_inverted_index.computer | 141 |
| abstract_inverted_index.directly | 28 |
| abstract_inverted_index.elements | 79 |
| abstract_inverted_index.emerging | 249 |
| abstract_inverted_index.emphasis | 195 |
| abstract_inverted_index.existing | 226 |
| abstract_inverted_index.obtained | 123 |
| abstract_inverted_index.quality. | 65 |
| abstract_inverted_index.research | 50, 194, 243 |
| abstract_inverted_index.rigorous | 68 |
| abstract_inverted_index.seamless | 93 |
| abstract_inverted_index.studies, | 227 |
| abstract_inverted_index.studies. | 170 |
| abstract_inverted_index.testing, | 57, 70, 178 |
| abstract_inverted_index.Graphical | 0 |
| abstract_inverted_index.Interface | 2 |
| abstract_inverted_index.different | 174 |
| abstract_inverted_index.effective | 59 |
| abstract_inverted_index.gradually | 211 |
| abstract_inverted_index.presents. | 129 |
| abstract_inverted_index.progress. | 148 |
| abstract_inverted_index.promising | 147, 242 |
| abstract_inverted_index.solution. | 48 |
| abstract_inverted_index.solutions | 208 |
| abstract_inverted_index.undermine | 38 |
| abstract_inverted_index.Neglecting | 34 |
| abstract_inverted_index.approaches | 135 |
| abstract_inverted_index.challenges | 110, 231 |
| abstract_inverted_index.conducting | 67 |
| abstract_inverted_index.developers | 71 |
| abstract_inverted_index.directions | 244 |
| abstract_inverted_index.efficiency | 115 |
| abstract_inverted_index.framework, | 190 |
| abstract_inverted_index.functional | 87 |
| abstract_inverted_index.outperform | 206 |
| abstract_inverted_index.solutions, | 99 |
| abstract_inverted_index.techniques | 161, 205 |
| abstract_inverted_index.Significant | 49 |
| abstract_inverted_index.combination | 247 |
| abstract_inverted_index.development | 139 |
| abstract_inverted_index.experience. | 33, 96 |
| abstract_inverted_index.generation, | 182 |
| abstract_inverted_index.interactive | 78 |
| abstract_inverted_index.significant | 10 |
| abstract_inverted_index.techniques. | 250 |
| abstract_inverted_index.traditional | 98, 207 |
| abstract_inverted_index.Vision-based | 130 |
| abstract_inverted_index.applications | 14 |
| abstract_inverted_index.requirements | 88 |
| abstract_inverted_index.technologies | 143 |
| abstract_inverted_index.vision-based | 169, 204 |
| abstract_inverted_index.Specifically, | 192 |
| abstract_inverted_index.comprehensive | 156 |
| abstract_inverted_index.effectiveness | 42, 113 |
| abstract_inverted_index.investigation | 157, 224 |
| abstract_inverted_index.opportunities | 233 |
| abstract_inverted_index.user-friendly | 95 |
| abstract_inverted_index.(vision-based) | 235 |
| abstract_inverted_index.state-of-the-art | 160 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 7 |
| citation_normalized_percentile |