Comparative Analysis of Fully Automated Testing Techniques for Android Applications

Abstract

The software testing community has continued to research and develop new ways of testing Android mobile applications to ensure an application function as expected and serves its purpose. Given that every testing technique/tool has its strengths and weaknesses. This study aims to present a comparative analysis of fully automated techniques which automatically generate and execute test cases concurrently during runtime. We selected 10 fully automated techniques published from 2013 to 2023 techniques to identify the similarities and differences that exist among them. We clearly define the comparative criteria (such as the exploration method, systematic method, termination criterion, extraction criterion, and scheduling method) used for comparing the selected techniques. The analysis shows that most fully automated techniques adopt an active learning exploration approach for exploring the application under test (AUT). We also observed that only the techniques utilizing the active learning approach are capable of modelling and abstracting the graphic user interface (GUI) of the AUT, others randomly select events to be fired into the AUT.