System Test Generation for Virtual Reality Applications using Scenario Models
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arXiv
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| Hauptverfasser: | , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2026
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| _version_ | 1866911662074757120 |
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| author | Longfils, Gerry Cauz, Maxime Blouin, Arnaud Devroey, Xavier |
| author_facet | Longfils, Gerry Cauz, Maxime Blouin, Arnaud Devroey, Xavier |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_07534 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | System Test Generation for Virtual Reality Applications using Scenario Models Longfils, Gerry Cauz, Maxime Blouin, Arnaud Devroey, Xavier Software Engineering 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. |
| title | System Test Generation for Virtual Reality Applications using Scenario Models |
| topic | Software Engineering |
| url | https://arxiv.org/abs/2605.07534 |