AI 中文总结
针对VR应用测试难题，提出基于模型的VRExplorer工具。设计EAT框架，结合路径查找算法和概率有限状态机实现场景探索与交互决策。实验显示其在覆盖率和效率上超现有方法，还成功检测出实际项目中的错误。
AI 中文摘要
随着虚拟现实（VR）市场的激增，VR应用在规模和复杂性上迅速扩展，迫切需要确保VR软件质量。与传统移动应用和计算机软件不同，VR测试因与虚拟对象的多样交互、复杂的3D虚拟环境和复杂的任务序列而面临独特挑战，阻碍了现有测试工具有效系统地测试VR应用。本文提出VRExplorer，一种基于模型的测试工具，能有效与多样虚拟对象交互并探索复杂VR场景。设计了EAT框架以通用方式对多样VR交互建模，在此基础上提出VRExplorer代理，通过精心设计的路径查找算法融入Unity的NavMesh实现有效场景探索，还能在概率有限状态机上系统执行交互决策。对11个代表性VR项目的实验评估表明，VRExplorer在覆盖率和效率上显著优于现有方法VRGuide，消融结果验证了各模块的重要贡献，且成功检测出实际项目中的三个错误。
英文摘要
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.
CommentsPublished in ASE 2025
Journal ref2025 40th IEEE/ACM International Conference on Automated Software Engineering (ASE), pp. 482-494, 2025
DOI：10.1109/ASE63991.2025.00047
