Modern web applications 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. Unfortunately, data shows that many web pages today are designed or implemented in ways that can lead to Responsive Accessibility Failures (RAFs) – a situation where keyboard-based users are unable to access core functionalities in a web page on these alternative views.

Our approach models the UI functionalities of web pages and simulates the keyboard interaction on these pages to identify RAFs. The artifact presents a Java prototype tool called SALAD, which is the implementation of our approach. Given a web page, SALAD automatically builds a User Interface Interactive Model and then analyzes this model to detect RAFs. The artifact is to help users understand and run the tool SALAD on a selected set of real-world subject web pages to reproduce its detection results, as presented in our research.

The tool SALAD is configured and ready to run, self-contained inside a VirtualBox VM image. The OS of the VM is Ubuntu 18.04.6 LTS, and the project itself is being run from an Eclipse IDE version 2023-09. No special technology skill is required besides basic knowledge of Linux, Java, and IDEs. SALAD is a demanding program to run efficiently but can be configured to run on lower-end machines. We recommend running the VM on a desktop rather than a laptop (not required) for better performance. We are claiming only the Reusable (results reproduced) badge.