SHF: Small: Detecting and Repairing Accessibility Failures in Web Applications

公司创建Web应用程序是为了覆盖广大受众，并使客户能够访问服务和信息。对于许多美国人，特别是26%的残疾人来说，访问网络应用程序尤其重要，可以代表他们的关键生命线，为他们提供访问原本无法访问的资源的途径。然而，最近的一项研究发现，70%的互联网网站都有“可访问性拦截器”，使残疾用户无法访问关键功能。这些类型的可访问性问题对残疾Web用户成功导航Web应用程序的用户界面的能力产生负面影响，并且可能导致物理上不能使用标准的基于鼠标的点击界面的用户几乎完全无法使用网站。该项目将导致在Web应用程序中自动发现这类可访问性问题的技术的开发。这些技术将使软件开发人员能够有效和准确地在大型Web应用程序中进行搜索，以发现潜在的可访问性问题，并为开发人员提供有用的信息，使修复问题的过程更快、更准确。该项目将包括四项技术研究。第一个推力将定义一个键抽象，键盘导航流程图(KNFG)，它将表示基于键盘的用户导航Web应用程序的方式，并开发可以分析网页并自动提取KNFG的自动化技术。第二个推力将设计基于图形的算法来分析KNFG，这种算法可以高精度地检测出网页中存在的一系列可访问性问题。第三个推力将导致本地化技术的开发，该技术可以识别网页中导致可访问性问题的特定HTML或JavaScript元素。第四个也是最后一个重点将探索自动修复可访问性问题的技术设计。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Companies create web applications to reach a broad audience and enable customers to access services and information. For many Americans, particularly the 26% with some type of disability, access to web applications is particularly important and can represent a critical lifeline for them, providing access to resources that would otherwise be inaccessible. However, a recent study found that 70% of internet sites have “accessibility blockers” that make critical functionality inaccessible to disabled users. These kinds of accessibility problems negatively affect the ability of disabled web users to successfully navigate a web application’s user interface and can cause a web site to become almost completely unusable to users who are physically unable to use the standard point-and-click mouse-based interfaces. This project will lead to the development of techniques for automatically finding these kinds of accessibility problems in web applications. These techniques will enable software developers to efficiently and accurately search through large web applications to find potential accessibility problems and provide the developers with useful information that will make the process of repairing the problems faster and more accurate.The project will encompass four technical research thrusts. The first thrust will define a key abstraction, the Keyboard Navigation Flow Graph (KNFG), which will represent the ways a keyboard-based user can navigate a web application, and develop automated techniques that can analyze a web page and automatically extract the KNFG. The second thrust will design graph-based algorithms for analyzing the KNFG that, with high accuracy, can detect a range of accessibility problems present in a web page. The third thrust will lead to the development of localization techniques that can identify the specific HTML or JavaScript elements in a web page that are responsible for the accessibility problems. The fourth and final thrust will explore the design of techniques for automatically repairing accessibility problems.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.