Modeling Software Quality in Virtual Reality Applications from User Feedback

Abstract

Virtual Reality (VR) applications couple software behavior with head-mounted displays, body movement, spatial interaction, and multimodal feedback. Consequently, familiar software-quality problems can have distinct consequences in VR, yet empirical knowledge of the quality concerns expressed by VR users remains fragmented. We analyze 1,656,968 public reviews of 28,745 VR applications across seven app stores. Our semiautomatic workflow uses five unsupervised methods to generate candidate aspects and multi-round human open and focused coding to construct and refine a hierarchical model of user-perceived VR software quality. The resulting model comprises 12 quality attributes and ten influencing factors. It distinguishes conventional attributes whose consequences change in VR from attributes closely tied to VR, including multisensory perception, user-friendly interaction mechanisms, immersivity, and comfort and safety. The influencing factors connect perceived quality problems to movement, control, tracking, multimedia, physics, configuration, and content decisions. Supplementary analyses examine temporal variation, platform and genre composition, accessibility-related reviews, and developer update logs. These descriptive analyses show that the concerns surfaced by reviews depend on context and identify concrete priorities for VR quality assurance. We release the available datasets, taxonomy materials, and analysis results to support replication and follow-up research: [https://sites.google.com/view/vr-software-quality](https://sites.google.com/view/vr-software-quality).