Novelty-Driven Evolutionary Scriptless Testing

In recent years, scriptless Graphical User Interface (GUI) testing has been positioned as a complement to traditional testing techniques. Automated scriptless GUI testing approaches use Action Selection Rules (ASR) to generate on-the-fly test sequences when testing a software system. Currently, random is the standard selection approach in scriptless testing, provoking drawbacks in the testing process, such as test sequences that do not reflect the human strategies for testing, and being unable to deal with multistep tasks. This paper presents an alternate selection approach based on the use of a grammar to design the ASR and an Evolutionary Algorithm (EA) with Novelty Search (NS) to direct the evolution process. Preliminary testing shows that the ASRS do evolve in the standard EA process. Further research is needed to show the benefits of the additional NS for the testing process.