Automated Detection of TalkBack Interactive Accessibility Failures in Android Applications

Ali S. Alotaibi · Paul Chiou · William G. J. Halfond

18 citations0/0 files storedIEEE Conference on Software Testing, Verification and Validation (ICST)

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Digital Accessibility for Disabilities Usability and User Interface Design Software Testing and Debugging Techniques

Abstract

TalkBack is one of the most popular screen readers for the 304 million visually impaired users worldwide to access Android devices. Yet, many popular Android apps lack a proper TalkBack accessible mechanism, which could cause failures that make apps unusable. Existing accessibility related techniques are limited in terms of detecting these issues. In this paper, we present a novel approach for automatically detecting TalkBack interactive accessibility failures that prevent TalkBack users from interacting with core functionalities in Android apps. Our evaluation of our technique on real-world Android apps showed that it is able to detect these TalkBack accessibility failures with high precision and recall.

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References

2019The Current Status of Accessibility in Mobile Apps 2021Screen Recognition: Creating Accessibility Metadata for Mobile Applications from Pixels 2018Examining Image-Based Button Labeling for Accessibility in Android Apps through Large-Scale Analysis 2019Can Everyone use my app? An Empirical Study on Accessibility in Android Apps 2021Accessible or Not? An Empirical Investigation of Android App Accessibility 2017Epidemiology as a Framework for Large-Scale Mobile Application Accessibility Assessment 2017Interaction Proxies for Runtime Repair and Enhancement of Mobile Application Accessibility 2020An Epidemiology-inspired Large-scale Analysis of Android App Accessibility

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