Using Visual Symptoms for Debugging Presentation Failures in Web Applications

TL;DR: This work proposes a novel automated approach for debugging web sites that is based on image processing and probabilistic techniques and predicts the elements and styling properties most likely to cause the observed failure for the page under test and reports these to the developer.

Abstract: Presentation failures in a website can undermine its success by giving users a negative perception of the trustworthiness of the site and the quality of the services it delivers. Unfortunately, existing techniques for debugging presentation failures do not provide developers with automated and broadly applicable solutions for finding the site's faulty HTML elements and CSS properties. To address this limitation, we propose a novel automated approach for debugging web sites that is based on image processing and probabilistic techniques. Our approach first builds a model that links observable changes in the web site's appearance to faulty elements and styling properties. Then using this model, our approach predicts the elements and styling properties most likely to cause the observed failure for the page under test and reports these to the developer. In evaluation, our approach was more accurate and faster than prior techniques for identifying faulty elements in a website.