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.

Player experience (PX) evaluation has become a field of interest in the game industry. Several manual PX techniques have been introduced to assist developers to understand and evaluate the experience of players in computer games. However, automated testing of player experience still needs to be addressed. An automated player experience testing framework would allow designers to evaluate the PX requirements in the early development stages without the necessity of participating human players. In this paper, we propose an automated player experience testing approach by suggesting a formal model of event-based emotions. In particular, we discuss an event-based transition system to formalize relevant emotions using Ortony, Clore, & Collins (OCC) theory of emotions. A working prototype of the model is integrated on top of Aplib, a tactical agent programming library, to create intelligent PX test agents, capable of appraising emotions in a 3D game case study. The results are graphically shown e.g. as heat maps. Visualization of the test agent's emotions would ultimately help game designers to produce contents that evoke a certain experience in players.

Designers of extended reality systems need to predict users feedback about designed elements to evaluate their systems. Manual user experience testing can not cover all preferences of users and user-system interactions. To improve and accelerate this process, automated user experience testing is a field of growing interest. Since users' emotions affect their experience, the automated testing framework should represent users with different emotional states. In this study, we propose an approach to deploy an automated user experience testing framework using BDI test agents which work with a computational model of emotion to regulate their testing behavior.

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.Index Terms-AI for automated testing, automated testing XR systems, agent based testing, AI for testing games

No abstract