The Metamorphosis: Automatic Detection of Scaling Issues for Mobile Apps

TL;DR

This paper introduces dVermin, an automated tool for detecting scaling issues in mobile app GUIs, significantly improving accuracy over existing methods and uncovering previously unknown issues.

Contribution

The paper presents dVermin, a novel automated approach for detecting GUI scaling issues in mobile apps, outperforming existing techniques in precision and recall.

Findings

dVermin achieves 97% precision and recall in issue page detection.

It attains 84% precision and 91% recall in view detection.

Successfully uncovers 21 previously unknown scaling issues in real apps.

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.