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International Journal of Innovations in Science and Technology

Design and Validation of a Quantum Software Engineering Lifecycle Framework

Islam Zada, Abid Jameel, Huma Mumtaz, Faisal Hayat, Jalal Ahmad, Sehrish Bibi, Laiba Shehryar

Published Dec 13, 2025• 0 citations
Publisher

Abstract

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.

DOI
10.33411/ijist/1683

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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 one of the research areas progressing rapidly toward practical deployment, yet the engineering of scalable and reliable quantum software remains underdeveloped. Current quantum software engineering (QSE) practices are largely tools‐driven and ad hoc that providing limited support for managing probabilistic execution, hybrid quantum–classical workflows, noise sensitivity, and hardware constraints. This study proposed a structured QSE lifecycle that integrates quantum‐specific characteristics with disciplined software engineering practices and principles. The proposed lifecycle organizes development into six phases, encompassing quantum requirements engineering, formal modeling, architecture and circuit design, hybrid integration, noise‐aware testing, and deployment with monitoring. Each phase is supported by explicit artifacts and quantitative criteria to enable systematic progression and iterative refinement. The QSE is validated through expert assessment and simulation‐based experimentation using representative variational quantum algorithms under the realistic noise conditions. The results show improved fidelity convergence, reduced resource overhead, enhanced development stability (DS), and more reliable validation compared with unstructured workflows, demonstrating the value of lifecycle‐driven engineering for quantum software systems.
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.
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Quantum computing promises exponential advantages over classical paradigms; however, it still lacks standardized software engineering methodologies. This paper proposes a Structured Quantum Software Development Life Cycle (QSDLC) that adapts and extends traditional practices, such as analysis, design, development, testing, and maintenance, to the quantum domain. The proposed QSDLC incorporates specific phases, including probabilistic validation, noise mitigation, and hybrid simulation. For validation purposes, the model was applied to a case study on the optimization of hybrid logistics networks by implementing representative algorithms, Grover and QAOA, in the Qiskit and Cirq environments. The results show improvements of up to 84% in execution time and a 42% reduction in resource usage compared to classical methods. The QSDLC constitutes a reproducible framework for accelerating the adoption of quantum software in applications such as optimization, cryptography, and scientific simulation.
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.