The Metamorphosis: Automatic Detection of Scaling Issues for Mobile Apps

Yuhui Su, Chunyang Chen, Junjie Wang, Zhe Liu, Dandan Wang, Shoubin Li, Qing Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations

Abstract

As the bridge between users and software, Graphical User Interface (GUI) is critical to the app accessibility. Scaling up the font or display size of GUI can help improve the visual impact, readability, and usability of an app, and is frequently used by the elderly and people with vision impairment. Yet this can easily lead to scaling issues such as text truncation, component overlap, which negatively influence the acquirement of the right information and the fluent usage of the app. Previous techniques for UI display issue detection and cross-platform inconsistency detection cannot work well for these scaling issues. In this paper, we propose an automated method, dVermin, for scaling issue detection, through detecting the inconsistency of a view under the default and a larger display scale. The evaluation result shows that dVermin achieves 97% precision and 97% recall in issue page detection, and 84% precision and 91% recall for issue view detection, outperforming two state-of-the-art baselines by a large margin. We also evaluate dVermin with popular Android apps on F-droid, and successfully uncover 21 previously-undetected scaling issues with 20 of them being confirmed/fixed.

Original languageEnglish
Title of host publication37th IEEE/ACM International Conference on Automated Software Engineering, ASE 2022
EditorsMario Aehnelt, Thomas Kirste
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450396240
DOIs
StatePublished - 19 Sep 2022
Externally publishedYes
Event37th IEEE/ACM International Conference on Automated Software Engineering, ASE 2022 - Rochester, United States
Duration: 10 Oct 202214 Oct 2022

Publication series

NameACM International Conference Proceeding Series

Conference

Conference37th IEEE/ACM International Conference on Automated Software Engineering, ASE 2022
Country/TerritoryUnited States
CityRochester
Period10/10/2214/10/22

Keywords

  • Accessibility Testing
  • Android Testing
  • Software Testing
  • UI Inconsistency Issue

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