Accessibility checkers are tools in support of accessible app development, and their use is encouraged by accessibility best practices. However, most current checkers evaluate static or mechanically-generated contexts, failing to capture common accessibility errors impacting mobile app functionality. In this work, we define functiona11ity errors as accessibility barriers that only manifest through interaction (i.e., named according to a blend of "functionality" and "accessibility"). We introduce TaskAudit, which comprises three components: a Task Generator that constructs interactive tasks from app screens, a Task Executor that uses agents with a screen reader proxy to perform these tasks, and an Accessibility Analyzer that detects and reports accessibility errors by examining interaction traces. Our evaluation on real-world apps shows that TaskAudit detects 48 functiona11ity errors from 54 app screens, compared to between 4 and 20 with existing checkers. Our analysis demonstrates common error patterns that TaskAudit can detect in addition to those from prior work, including label-functionality mismatch, cluttered navigation, and inappropriate feedback.

翻译：可访问性检查器是辅助无障碍应用开发的工具，其使用受到无障碍最佳实践的鼓励。然而，当前大多数检查器评估的是静态或机械生成的上下文，无法捕获影响移动应用功能的常见无障碍错误。在本工作中，我们将“功能可访问性错误”定义为仅通过交互才显现的无障碍障碍（即根据“功能”与“可访问性”的融合命名）。我们提出了TaskAudit，它包含三个组件：从应用屏幕构建交互式任务的“任务生成器”、使用配备屏幕阅读器代理的智能体来执行这些任务的“任务执行器”，以及通过检查交互轨迹来检测和报告无障碍错误的“可访问性分析器”。我们在真实应用上的评估表明，TaskAudit从54个应用屏幕中检测出48个功能可访问性错误，而现有检查器仅能检测4到20个错误。我们的分析展示了TaskAudit能够检测到的常见错误模式，这些模式超出了先前工作的范围，包括标签功能不匹配、导航混乱以及不恰当的反馈。