Computer 3D games are complex software environments that require novel testing processes to ensure high-quality standards. The Intelligent Verification/Validation for Extended Reality Based Systems ( iv4XR ) framework addresses this need by enabling the implementation of autonomous agents to automate game testing scenarios. This framework facilitates the automation of regression test cases for complex 3D games like Space Engineers. Nevertheless, the technical expertise required to define test scripts using iv4XR can constrain seamless collaboration between developers and testers. This paper reports how integrating a Behavior-Driven Development (BDD) approach with the iv4XR framework allows the industrial company behind Space Engineers to automate regression testing. The success of this industrial collaboration has inspired the iv4XR team to integrate the BDD approach to improve the automation of play-testing for the experimental 3D game LabRecruits. Furthermore, the iv4XR framework has been extended with tactical programming to enable the automation of long-play test scenarios in Space Engineers. These results underscore the versatility of the iv4XR framework in supporting diverse testing approaches while showcasing how BDD empowers users to create, manage, and execute automated game tests using comprehensive and human-readable statements.

Computer games have reached unprecedented importance, exceeding two billion users in the early 2020s. Human game testers bring invaluable expertise to evaluate complex games like 3D sandbox games. However, the sheer scale and diversity of game content constrain their ability to explore all scenarios manually. Recognizing the significance and inherent complexity of game testing, our research aims to investigate new automated testing approaches. To achieve this goal, we have integrated scriptless testing into the industrial game Space Engineers, enabling an automated approach to explore and test sandbox game scenarios. Our approach involves the development of a Space Engineers-plugin, leveraging the Intelligent Verification and Validation for Extended Reality-Based Systems (IV4XR) framework and extending the capabilities of the open-source scriptless testing tool TESTAR. Through this research, we unveil the potential of a scriptless agent to explore 3D sandbox game scenarios autonomously. Results demonstrate the effectiveness of an autonomous scriptless agent in achieving spatial coverage when exploring and (dis)covering elements within the 3D sandbox game.

We introduce a dynamic benchmarking system for conversational agents that evaluates their performance through a single, simulated, and lengthy user$\leftrightarrow$agent interaction. The interaction is a conversation between the user and agent, where multiple tasks are introduced and then undertaken concurrently. We context switch regularly to interleave the tasks, which constructs a realistic testing scenario in which we assess the Long-Term Memory, Continual Learning, and Information Integration capabilities of the agents. Results from both proprietary and open-source Large-Language Models show that LLMs in general perform well on single-task interactions, but they struggle on the same tasks when they are interleaved. Notably, short-context LLMs supplemented with an LTM system perform as well as or better than those with larger contexts. Our benchmark suggests that there are other challenges for LLMs responding to more natural interactions that contemporary benchmarks have heretofore not been able to capture.

Testing for quality assurance (QA) is a crucial step in the development of Extended Reality (XR) systems that typically follow iterative design and development cycles. Bringing automation to these testing procedures will increase the productivity of XR developers. However, given the complexity of the XR environments and the User Experience (UX) demands, achieving this is highly challenging. We propose to address this issue through the creation of autonomous cognitive test agents that will have the ability to cope with the complexity of the interaction space by intelligently explore the most prominent interactions given a test goal and support the assessment of affective properties of the UX by playing the role of users.

This paper describes the history, functions, and usage of the program that was used to analyze the plans for direct broadcast satellite service developed in the course of the 1983 Regional Administrative Radio Conference for ITU Region 2. Given the requirements for direct broadcast service by the administrations, the conference delegates 1) developed the appropriate technical parameters; 2) made tentative assignments to the orbit locations, frequencies, and polarizations of space stations; 3) calculated the interferences and margins of such assignments through the use of the Spectrum Orbit Utilization Program (SOUP); and 4) iterated this procedure until an acceptable plan was found.