System Test Generation for Virtual Reality Applications using Scenario Models
Gerry Longfils, Maxime Cauz, Arnaud Blouin, Xavier Devroey
TLDR
UltraInstinctVR automates system test generation for VR applications using scenario models, outperforming existing tools in bug detection.
Key contributions
- Introduces UltraInstinctVR, a novel automated system testing approach for VR applications.
- Generates and executes VR system tests based on predefined VR scenario models.
- Empirically evaluated on 10 open-source VR apps, outperforming state-of-the-art tools.
- Effectively detects unique failures and identifies real-world bugs in VR applications.
Why it matters
VR applications lack effective testing methods, hindering adoption. UltraInstinctVR provides a systematic, automated solution. This improves VR software quality, making applications more reliable and maintainable for broader integration.
Original Abstract
Virtual Reality (VR) applications are increasingly being integrated across a wide range of domains, including surgical training and industrial marketing. However, the long-term adoption and maintenance of VR applications remain limited, particularly due to the lack of effective, systematic, and reproducible software testing approaches tailored to their unique characteristics. To address this issue, we introduce UltraInstinctVR, a novel testing approach for VR applications. Relying on predefined VR models (scenarios), it automates the generation and execution of concrete VR system tests. In our empirical evaluation, we compare UltraInstinctVR with state-of-the-art automated VR testing approaches in terms of coverage and failure detection on 10 open-source VR applications. The results show that UltraInstinctVR outperforms existing automated tools for detecting unique failures and provides valuable insights for identifying real-world bugs in VR applications.
📬 Weekly AI Paper Digest
Get the top 10 AI/ML arXiv papers from the week — summarized, scored, and delivered to your inbox every Monday.