VRExplorer: A Model-based Approach for Semi-Automated Testing of Virtual Reality Scenes
2026-07-11 • Software Engineering
Software EngineeringHuman-Computer Interaction
AI summaryⓘ
The authors introduce VRExplorer, a new tool designed to test Virtual Reality (VR) software more effectively. VRExplorer uses a special framework called Entity, Action, and Task (EAT) to model how users interact with VR environments. It explores VR scenes using smart navigation methods and systematically tests interactions using a Probabilistic Finite State Machine. When tested on 11 VR projects, VRExplorer performed better than existing tools by covering more code and finding bugs successfully. The authors also showed that each part of their system is important for its overall performance.
Virtual Reality (VR)Software TestingModel-based TestingEntity Action Task (EAT) FrameworkNavigation Mesh (NavMesh)Probabilistic Finite State Machine (PFSM)Code CoverageFunctional BugsNon-functional Bugs
Authors
Zhengyang Zhu, Hong-Ning Dai, Hanyang Guo, Zeqin Liao, Zibin Zheng
Abstract
With the proliferation of Virtual Reality (VR) markets, VR applications are rapidly expanding in scale and complexity, thereby driving an urgent need for assuring VR software quality. Different from traditional mobile applications and computer software, VR testing faces unique challenges due to diverse interactions with virtual objects, complex 3D virtual environments, and intricate sequences to complete tasks. All of these emerging challenges hinder existing VR testing tools from effectively and systematically testing VR applications. In this paper, we present VRExplorer, a novel model-based testing tool to effectively interact with diverse virtual objects and explore complex VR scenes. Particularly, we design the Entity, Action, and Task (EAT) framework for modeling diverse VR interactions in a generic way. Built upon the EAT framework, we then present the VRExplorer agent, which can achieve effective scene exploration by incorporating meticulously designed path-finding algorithms into Unity's NavMesh. Moreover, the VRExplorer agent can also systematically execute interaction decisions on top of the Probabilistic Finite State Machine (PFSM). Experimental evaluation on 11 representative VR projects shows that VRExplorer consistently outperforms the state-of-the-art (SOTA) approach VRGuide by achieving significantly higher coverage and better efficiency. Specifically, VRExplorer yields up to 122.8% and 52.8% improvements over VRGuide in terms of executable lines of code (ELOC) coverage and method (function) coverage, respectively. Furthermore, ablation results also verify the essential contributions of each designed module. More importantly, our VRExplorer has successfully detected two functional bugs and one non-functional bug from real-world projects.