Quantum software development has largely focused on algorithms, with limited attention to software architecture. As computing moves toward hybrid quantum-classical systems, this gap limits scalability, reusability, and engineering rigor. This study introduces a component-based quantum software architecture framework (QSAF) for hybrid quantum-classical software systems, enabling developers to transition from circuit-level design to system-level reasoning. We identified 34 reusable quantum circuit primitives across seven functional categories and reinterpreted them as architectural components with explicit interfaces and design-relevant constraints. These components are further characterized using non-functional dimensions such as circuit depth, error sensitivity, and information flow, enabling a structured analysis of design trade-offs. The proposed QSAF framework establishes a multi-level abstraction hierarchy linking quantum gates, circuit primitives, algorithmic structures, and hybrid system architectures. Through this approach, common workflows, particularly hybrid quantum-classical workflows such as variational quantum algorithms, can be systematically decomposed, compared, and optimized. By making the architectural structure and trade-offs explicit, this study provides a foundation for quantum software engineering, supporting modular design, reuse, and informed architectural decision-making in quantum application development.
Quantum software development has largely focused on algorithms, with limited attention to software architecture. As computing moves toward hybrid quantum-classical systems, this gap limits scalability, reusability, and engineering rigor. This study introduces a component-based quantum software architecture framework (QSAF) for hybrid quantum-classical software systems, enabling developers to transition from circuit-level design to system-level reasoning. We identified 34 reusable quantum circuit primitives across seven functional categories and reinterpreted them as architectural components with explicit interfaces and design-relevant constraints. These components are further characterized using non-functional dimensions such as circuit depth, error sensitivity, and information flow, enabling a structured analysis of design trade-offs. The proposed QSAF framework establishes a multi-level abstraction hierarchy linking quantum gates, circuit primitives, algorithmic structures, and hybrid system architectures. Through this approach, common workflows, particularly hybrid quantum-classical workflows such as variational quantum algorithms, can be systematically decomposed, compared, and optimized. By making the architectural structure and trade-offs explicit, this study provides a foundation for quantum software engineering, supporting modular design, reuse, and informed architectural decision-making in quantum application development.
Quantum computing promises transformative computational capabilities; however, the absence of structured and standardized software engineering significantly limits its practical scalability. Quantum Software Engineering (QSE) remains fragmented, tool-centric, and largely experimental. This paper proposes a structured Quantum Software Engineering Lifecycle Framework that systematically integrates requirements engineering, hybrid design, quantum development, verification, deployment, and governance. To validate the proposed lifecycle, a two-stage evaluation was conducted. First, a Delphi-based expert validation involving 15 domain experts assessed clarity, feasibility, scalability, and hybrid applicability. Second, a simulation-based comparative analysis using Qiskit and PennyLane evaluated the lifecycle against ad-hoc development workflows across variational and search-based quantum algorithms. Results demonstrate a 24% reduction in development time, 15–18% improvement in execution fidelity, and significant gains in modularity, reusability, and tool interoperability. These findings confirm that adopting a structured lifecycle enables more reliable, scalable, and sustainable quantum software development, positioning QSE as a mature engineering discipline rather than purely experimental practice.
Quantum computing is quickly becoming a potentially disruptive technology that can tackle the problems inaccessible to classical computers, but the use of quantum computing in real software systems has yet to be fully explored. Present day quantum studies are largely focused on the development of algorithms and hardware, whereas engineering workflows to be used to enable smooth hybrid quantum-classical operations attract limited attention. The paper suggests a concept of quantum-ready software engineering- a systematic approach to applying established principles of software engineering to hybrid systems. In order to meet maintainability, scalability, and reliability objectives in hybrid applications, propose the adoption of a multilayered design, such as abstraction, integration, orchestration, and verification. An example concrete programming template, written in Python in Qiskit, demonstrates how quantum functions being used as modular services can be simulated with classical software. Evaluation measures (maintainability index, latency, and modularity) demonstrate the feasibility of the framework. Results indicate that the hybrid pipelines can be designed in a systematic way using quantum-classical-adapted design patterns. The study introduces a repeatable methodology, program templates, and design pattern engineering principles, which open the door to additional development of quantum DevOps and design pattern formalization. This project, by bridging the gap between classical software engineering and quantum integration, gives a platform upon which to build extraordinarily reliable, scalable systems in the Noisy Intermediate-Scale Quantum and beyond.
Introduction: This article is the result of doctoral research conducted in 2025 on quantum software architecture, addressing the transformative potential of quantum computing and the challenges associated with integrating quantum capabilities into software systems. Problem: The lack of standardized architectural models for hybrid classical–quantum systems limits interoperability, reuse, and systematic software design. Objective: This study proposes a reference architecture to support the design and evolution of hybrid classical–quantum software systems. Methodology: The architecture was derived through a harmonization process. Results: The proposed framework defines ten architectural elements organized across three dimensions: Conceptual, Organizational, and Quality. Conclusion: The architecture provides a structured foundation for designing hybrid classical–quantum solutions. Originality: The work consolidates dispersed knowledge into a unified framework for hybrid classical–quantum systems. Limitations: The model is based on the currently limited body of literature and industrial experience, requiring future validation.
Addressing problems beyond classical computing limits is sparking an increasing interest in Quantum Computing. However, despite their adequacy to address specific problems, quantum algorithms cover a limited subset of the functionality required in real-world computing systems. Additionally, they require expensive specialized hardware. To overcome this issue, hybrid (quantum-classical) software systems are emerging as a promising way to integrate both computing paradigms by applying the principles of Service-Oriented Architectures (SOA). Still, the design and deployment of hybrid service-based systems faces unique challenges like the idiosyncrasies and constraints of NISQ computers (e.g., algorithms that can only run in specific machines, disparate quality attribute metrics), and the management of structural and behavioural properties of service-based applications. From the SOA perspective, architectural decisions need to be made by performing a trade-off analysis and providing quantitative guarantees of system configurations under prescribed levels of uncertainty. In this paper, a method to explore the design space of quantum-classical applications is provided by a formalization of an architectural style of hybrid applications. The obtained results demonstrate that the proposed method successfully identifies decision boundaries. It enables the dynamic selection of the most suitable hybrid or classical configuration based on the user's QoS criteria.
Quantum software engineering (QSE) has emerged as a discipline to address the challenges associated with developing software systems in the context of advancing quantum computing technology. This paper explores architectural design patterns specific to QSE. Building on previous work highlighting the need for high-level patterns, we analyze emerging architectural approaches in quantum computing. We identify key challenges unique to hybrid quantum-classical systems and propose a preliminary taxonomy of QSE architectural patterns. These patterns address recurring design problems in areas such as quantum resource management and classical-quantum integration. We describe several potential patterns and discuss their theoretical applications in hybrid software systems. This work aims to provide a foundation for further research into standardizing QSE architectural practices, with the goal of enhancing various quality characteristics of hybrid software (e.g., modularity or maintainability) in the NISQ era and beyond.
Quantum Software Engineering (QSE) is emerging as a critical discipline to make quantum computing accessible to a broader developer community; however, most quantum development environments still require developers to engage with low-level details across the software stack—including problem encoding, circuit construction, algorithm configuration, hardware selection, and result interpretation—making them difficult for classical software engineers to use. To bridge this gap, we present C2 ∣Q⟩ , a hardware-agnostic quantum software development framework that translates specific types of classical specifications into quantum-executable programs while preserving methodological rigor. The framework applies modular software engineering principles by classifying the workflow into three core modules: an encoder that classifies problems, produces Quantum-Compatible Formats (QCFs), and constructs quantum circuits, a deployment module that generates circuits and recommends hardware based on fidelity, runtime, and cost, and a decoder that interprets quantum outputs into classical solutions. This architecture supports systematic evaluation across simulators and Noisy Intermediate-Scale Quantum (NISQ) quantum devices, remaining scalable to new problem classes and algorithms. In evaluation, the encoder module achieved a 93.8% completion rate, the hardware recommendation module consistently selected the appropriate quantum devices for workloads scaling up to 56 qubits. End-to-end experiments on 434 Python programs and 100 JSON problem instances demonstrate that the full C2 ∣Q⟩ workflow executes reliably on simulators and can be deployed successfully on representative real quantum hardware, with empirical runs limited to small- and medium-sized instances consistent with current NISQ capabilities. A proxy-based usability analysis further indicates substantial reductions in handwritten lines of code and explicit configuration steps compared to conventional quantum SDK workflows. These results indicate that C2 ∣Q⟩ lowers the entry barrier to quantum software development by providing a reproducible, extensible toolchain that connects classical specifications to quantum execution. The open-source implementation of C2 ∣Q⟩ is available at https://github.com/C2-Q/C2Q and as a ready-to-use Python package at https://pypi.org/project/c2q-framework/ .