一句话：提出 A11yNavigator，模拟屏幕阅读器导航，自动检测无法定位或激活的 UI 元素。
现有 Web 可访问性自动化工具（如 WAVE、Lighthouse）主要基于静态规则分析，多能发现标注错误，却难以捕捉动态问题：屏幕阅读器用户能否定位并激活 UI 元素。本文提出 A11yNavigator，通过模拟屏幕阅读器导航来自动检测既无法定位又无法激活的 UI 元素；工具基于常用屏幕阅读器 NVDA，支持 Tab、Arrow 和快速导航键三种策略。作者在 26 个真实网站上评估，表明其能发现现有工具遗漏的障碍，并在检测这类导航障碍上具有较高精确率和召回率。
An estimated 43.3 million people worldwide live with blindness and rely on screen readers (SRs) to access the web. To support accessible development, software teams often rely on automated tools like WAVE and Lighthouse to detect accessibility issues. However, these tools primarily rely on static rule-based analysis and are largely limited to detecting labeling errors relevant to screen reader users. They fail to capture dynamic accessibility issues—specifically, whether user interface (UI) elements can be located and activated using a screen reader, which is essential for accessing core webpage functionality. To address this gap, we present A1 1yNavigator, an automated accessibility testing tool that simulates screen reader navigation to detect UI elements that cannot be either (1) located or (2) activated via the screen reader. A11yNavigator leverages NVDA, one of the most widely used screen readers, and supports three common navigation strategies: Tab, Arrow, and quick Navigation keys. We evaluate A1 1yNavigator across 26 real-world websites and demonstrate its effectiveness in uncovering issues missed by existing tools. Our results highlight its high precision and recall in detecting barriers that go beyond static analysis.
DOI 原文 ·
@inproceedings{paperbot9502,
title = {Automated Detection of Web Application Navigation Barriers for Screen Reader Users},
author = {Shubhi Jain and Syed Fatiul Huq and Ziyao He and Sam Malek},
booktitle = {ASE},
year = {2025},
doi = {10.1109/ase63991.2025.00159}
}