Samira Shirzadehhajimahmood

I. S. W. B. Prasetya, Samira Shirzadehhajimahmood, Saba Gholizadeh Ansari et al.

This short paper presents an architectural overview of an agent-based framework called iv4XR for automated testing that is currently under development by an H2020 project with the same name. The framework's intended main use case of is testing the family of Extended Reality (XR) based systems (e.g. 3D games, VR sytems, AR systems), though the approach can indeed be adapted to target other types of interactive systems. The framework is unique in that it is an agent-based system. Agents are inherently reactive, and therefore are arguably a natural match to deal with interactive systems. Moreover, it is also a natural vessel for mounting and combining different AI capabilities, e.g. reasoning, navigation, and learning.

I. S. W. B. Prasetya, Maurin Voshol, Tom Tanis et al.

To enable automated software testing, the ability to automatically navigate to a state of interest and to explore all, or at least sufficient number of, instances of such a state is fundamental. When testing a computer game the problem has an extra dimension, namely the virtual world where the game is played on. This world often plays a dominant role in constraining which logical states are reachable, and how to reach them. So, any automated testing algorithm for computer games will inevitably need a layer that deals with navigation on a virtual world. Unlike e.g. navigating through the GUI of a typical web-based application, navigating over a virtual world is much more challenging. This paper discusses how concepts from geometry and graph-based path finding can be applied in the context of game testing to solve the problem of automated navigation and exploration. As a proof of concept, the paper also briefly discusses the implementation of the proposed approach.