Graph-Walk-based Selective Regression Testing of Web Applications Created with Google Web Toolkit.
Matthias Hirzel, Herbert Alois Klaeren · Software Engineering (Workshops) · 2016
Modern web applications are usually based on JavaScript. Due to its loosely typed, dynamic nature, test execution is time expensive and costly. Techniques for regression testing and fault-localization as well as frameworks like the Google Web Toolkit (GWT) ease the development and testing process, but still require approaches to reduce the testing effort. In this paper, we investigate the efficiency of a specialized, graph-walk based selective regression testing technique that aims to detect code changes on the client side in order to determine a reduced set of web tests. To do this, we analyze web applications created with GWT on different precision levels and with varying lookaheads. We examine how these parameters affect the localization of client-side code changes, run time, memory consumption and the number of web tests selected for re-execution. In addition, we propose a dynamic heuristics which targets an analysis that is as exact as possible while reducing memory consumption. The results are partially applicable on non-GWT applications. In the context of web applications,we see that the efficiency relies to a great degree on both the structure of the application and the code modifications, which is why we propose further measures tailored to the results of our approach.