Gu, R., Rojas, J.M. and Shin, D. orcid.org/0000-0002-0840-6449 (Accepted: 2025) XRintTest: An automated framework for user interaction testing in extended reality applications. In: Proceedings of the 40th IEEE/ACM International Conference on Automated Software Engineering. 40th IEEE/ACM International Conference on Automated Software Engineering, 16-20 Nov 2025, Seoul, South Korea. Institute of Electrical and Electronics Engineers (IEEE). (In Press)
Abstract
Extended Reality (XR) technologies offer immersive user experiences across diverse application domains, presenting unique testing challenges due to their spatial interaction paradigms. While existing works test XR applications through scene navigation and interaction triggering, they fail to synthesise realistic spatial input via specialised XR devices, such as 6 degrees of freedom controller gestures, that are essential for modern XR user experiences. To address this gap, we present XRINTTEST, an automated testing framework for Unity-based XR applications. XRINTTEST starts by constructing an XR User Interaction Graph that models interaction targets and required events. Leveraging this graph, it then automatically explores the XR scene under test and generates user interactions. We evaluated XRINTTEST on XRBENCH3D, a novel benchmark comprising seven XR scenes containing 367 distinct 3D user interactions. XRINTTEST shows great effectiveness, achieving 97% coverage of trigger and grab interactions across all scenes, 9x more effective and 5x more efficient than random exploration, while detecting runtime exceptions and functional defects. We opensourced our tool and dataset at https://github.com/ruizhengu/ XRintTest and https://github.com/ruizhengu/XRBench3D, respectively. A video demo is available on YouTube at https://youtu.be/K0Q6waE47Us.
Metadata
| Item Type: | Proceedings Paper |
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| Authors/Creators: |
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| Copyright, Publisher and Additional Information: | © 2025 The Author(s). |
| Keywords: | Extended Reality; Software Testing; 3D Interaction; Model-based Testing |
| Dates: |
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| Institution: | The University of Sheffield |
| Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
| Date Deposited: | 05 Nov 2025 15:34 |
| Last Modified: | 05 Nov 2025 15:34 |
| Status: | In Press |
| Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
| Refereed: | Yes |
| Related URLs: | |
| Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:233951 |
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