Scriptless Testing for Extended Reality Systems

Extended Reality (XR) systems are complex applications that have emerged in a wide variety of domains, such as computer games and medical practice. Testing XR software is mainly done manually by human testers, which implies a high cost in terms of time and money. Current automated testing approaches for XR systems consist of rudimentary capture and replay of scripts. However, this approach only works for simple test scenarios. Moreover, it is well-known that the scripts break easily each time the XR system is changed. There are research projects aimed at using autonomous agents that will follow scripted instructions to test XR functionalities. Nonetheless, using only scripted testing techniques, it is difficult and expensive to tackle the challenges of testing XR systems. This thesis is focus on the use of automated scriptless testing for XR systems. This way we help to reduce part of the manual testing effort and complement the scripted techniques.