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Innovative VR Testing Tools: Adevelopment and QA Perspective

Author(s) Komal Jasani
Country United States
Abstract Exploring the field of Virtual Reality (VR), one can state that it brings socially responsible and transformative changes across the entertainment, medicine, education platforms, and training services. However, the quality, performance, and reliability of VR applications are crucial aspects not easily tackled by regular software testing techniques. These are systematic approaches that have been developed as testing tools and techniques to help develop QA VR applications. It outlines the distinctions between VR and software testing as a distinct testing practice thatcenters on real-time appliance and user experience. The study also outlines several issues that may affect VR QA, including hardware constraints, the onset of motion sickness, compliance issues, and high resource utilization. However, to solve such problems, it is possible to distinguish the following types of testing tools for VR – automated testing, performance analysis, usability, compatibility, and regression debugging. The paper investigates various advanced testing tools and methods in VR, which are VRTest is a testing framework for scene automation, testing agents in AI user emulation, SIM2VR aimed at predicting the user’s actions, CAVE-AR for multi-user testing, and VisionaryVR for optical and vision testing. Others, such as the SteamVR Performance Tool for testing system compatibility and various accessibilities testing frames, are also discussed.
Through these testing solutions, developers can improve the quality of the VR application, users’ experience, and accessibility. This research stresses the need for constant enhancement of VR testing techniques to rapidly cater to the market's increasing demand for more quality and immersive VR solutions.
Keywords -
Field Engineering
Published In Volume 4, Issue 5, May 2023
Published On 2023-05-03
Cite This Innovative VR Testing Tools: Adevelopment and QA Perspective - Komal Jasani - IJLRP Volume 4, Issue 5, May 2023. DOI 10.5281/zenodo.14982536
DOI https://doi.org/10.5281/zenodo.14982536
Short DOI https://doi.org/g8688m
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