When Shared Worlds Break: Demystifying Defects in Multi-User Extended Reality Software Systems

2025-10-01

AI Summary

Multi-user extended reality (XR) systems exhibit unique software defects that severely degrade shared immersive experiences, yet their root causes and impacts remain poorly understood. To address this gap, we conduct a large-scale empirical study of 2,649 real-world bug reports—aggregated from GitHub repositories, developer forums, and app store reviews—and apply iterative open coding to construct the first three-dimensional defect taxonomy for multi-user XR, structured along symptom–root cause–impact dimensions. Our analysis reveals synchronization inconsistency and avatar anomalies as the most prevalent symptoms, with network synchronization logic flaws and session management vulnerabilities identified as primary root causes; over 34% of defects result in shared world crashes, persistent disconnections, or interaction failures. Based on these findings, we propose actionable quality assurance strategies spanning development practices, platform design, and future research directions—providing an evidence-based foundation and methodological framework to enhance the reliability of multi-user XR systems.

Technology Category

• Multiagent Systems: Other Foundations of Multi Agent Systems
• Knowledge Representation and Reasoning: Qualitative Reasoning
• Intelligent Robots: Multi-Robot Systems

Application Category

• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

Multi-user Extended Reality (XR) systems enable transformative shared experiences but introduce unique software defects that compromise user experience. Understanding software defects in multi-user XR systems is crucial for enhancing system reliability, yet remains underexplored. To fill the gap, this paper presents the first large-scale empirical study of multi-user XR defects, analyzing 2,649 real-world bug reports from diverse sources, including developer forums, GitHub repositories, and app reviews on mainstream XR app stores. Through rigorous qualitative analysis using iterative open coding, we develop a comprehensive taxonomy that classifies multi-user XR bugs along three dimensions: Symptom Manifestation, Root Cause Origin, and Consequence Severity. Our findings reveal that synchronization inconsistencies and avatar-related anomalies are the most prevalent symptoms, while network/synchronization logic defects and session management flaws emerge as dominant root causes. Critically, over 34% of analyzed bugs lead to severe consequences that fundamentally break the shared experience, including system crashes, persistent disconnections, and complete interaction breakdowns, etc. We also identify concerning privacy and health implications unique to multi-user XR contexts. Based on our findings of defect analysis, we provide actionable recommendations for developers, platform vendors, and researchers. Our results demonstrate that multi-user XR systems face distinct challenges at the intersection of distributed systems, real-time 3D interaction, and immersive experiences, necessitating specialized approaches to testing, debugging, and quality assurance.

Problem

• Analyzing software defects in multi-user XR systems
• Identifying prevalent symptoms like synchronization inconsistencies
• Addressing severe consequences breaking shared experiences

Innovation

• Large-scale empirical study of multi-user XR defects
• Comprehensive taxonomy classifying bugs along three dimensions
• Actionable recommendations for testing and quality assurance