Year: 2024
Type: conference-paper
Abstract: Many web applications today use responsive design to adjust the view of web pages to match the screen size of end users. People with disabilities often use an alternative view either due to zooming on a desktop device to enlarge text or viewing within a smaller viewport when using assistive technologies. When web pages are not implemented to correctly adjust the page's content across different screen sizes, it can lead to both a loss of content and functionalities between the different versions. Recent studies show that these reflow accessibility issues are among the most prevalent modern web accessibility issues. In this paper, we present a novel automated technique to automatically detect reflow accessibility issues in web pages for keyboard users. The evaluation of our approach on real-world web pages demonstrated its effectiveness in detecting reflow accessibility issues, outperforming state-of-the-art techniques.
Authors: Paul T. Chiou, Robert Winn, Ali S. Alotaibi, William G. J. Halfond
Institution: University of Southern California
Language: English
Subfield: Human Factors and Ergonomics
Field: Social Sciences
Domain: Social Sciences
Open Access status: hybrid
Funder: National Science Foundation
OpenAlex ID: W4394769476