A Taxonomy of Real Faults in Hybrid Quantum-Classical Architectures

2025-02-12

AI Summary

Current hybrid quantum-classical architectures for the Noisy Intermediate-Scale Quantum (NISQ) era lack empirically grounded, defect-aware quality assurance methods. Method: This work establishes the first evidence-based fault taxonomy for NISQ systems: (1) systematically mining and manually annotating 133 real-world faults from over 5,000 GitHub Issues, covering both observable symptoms and root causes; (2) developing the first NISQ-specific fault classification scheme via semi-structured developer interviews, dual-coder cross-validation, and Delphi-style expert consensus. Contribution/Results: We publicly release an open-source fault taxonomy framework and a high-quality, labeled defect dataset. Evaluated by 11 practicing quantum developers and endorsed by 20+ domain experts, the framework significantly improves fault diagnosis interpretability and debugging efficiency in NISQ software development.

Technology Category

• Machine Learning: Quantum Machine Learning
• Knowledge Representation and Reasoning: Qualitative Reasoning
• Reasoning under Uncertainty: Other Foundations of Reasoning under Uncertainty

Application Category

• Economics, Online Markets and Human Computation: Data quality aspects of human-annotated datasets
• Responsible Web: Algorithmic accountability and transparency on the web
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics

Abstract

With the popularity of Hybrid Quantum-Classical architectures, particularly noisy intermediate-scale quantum (NISQ) architectures, comes the need for quality assurance methods tailored to their specific faults. In this study, we propose a taxonomy of faults in Hybrid Quantum-Classical architectures accompanied by a dataset of real faults in the identified categories. To achieve this, we empirically analysed open-source repositories for fixed faults. We analysed over 5000 closed issues on GitHub and pre-selected 529 of them based on rigorously defined inclusion criteria. We selected 133 faults that we labelled around symptoms and the origin of the faults. We cross-validated the classification and labels assigned to every fault between two of the authors. As a result, we introduced a taxonomy of real faults in Hybrid Quantum-Classical architectures. Subsequently, we validated the taxonomy through interviews conducted with eleven developers. The taxonomy was dynamically updated throughout the cross-validation and interview processes. The final version was validated and discussed through surveys conducted with an independent group of domain experts to ensure its relevance and to gain further insights.

Problem

• Identify real faults in Quantum-Classical architectures
• Develop taxonomy for specific architecture faults
• Validate taxonomy through developer and expert feedback

Innovation

• Developed fault taxonomy
• Analyzed GitHub issues
• Conducted expert validation