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.

Project Start
Project End
Budget Start
2020-08-01
Budget End
2023-07-31
Support Year
Fiscal Year
2020
Total Cost
$495,774
Indirect Cost
Name
University of Southern California
Department
Type
DUNS #
City
Los Angeles
State
CA
Country
United States
Zip Code
90089