The Metamorphosis: Automatic Detection of Scaling Issues for Mobile Apps

Yuhui Su, Chun-Yu Chen, Junjie Wang, Zhe Liu, Dandan Wang, Shoubin Li, Qing Wang
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引用次数: 5

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.
变形:移动应用程序缩放问题的自动检测
图形用户界面(GUI)作为连接用户和软件的桥梁,对应用程序的可访问性至关重要。放大GUI的字体或显示大小可以帮助改善应用程序的视觉冲击力、可读性和可用性,老年人和视力障碍人士经常使用。然而,这很容易导致缩放问题,如文本截断,组件重叠,这对正确信息的获取和应用程序的流畅使用产生负面影响。以前的UI显示问题检测和跨平台不一致检测技术不能很好地解决这些缩放问题。在本文中,我们提出了一种自动化的方法,dVermin,用于缩放问题检测,通过检测默认和更大的显示规模下视图的不一致性。评估结果表明,dVermin在问题页面检测中达到了97%的准确率和97%的召回率,在问题视图检测中达到了84%的准确率和91%的召回率,大大优于两个最先进的基线。我们还在F-droid上用流行的Android应用程序评估了dVermin,并成功发现了21个以前未被发现的扩展问题,其中20个已被确认/修复。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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