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Advancing Quantum Software Engineering: A Vision of Hybrid Full-Stack Iterative Model
Arif Ali Khan, Davide Taibi, Muhammad Azeem Akbar
TL;DR
Quantum software development faces challenges in integrating quantum and classical components, while large-scale quantum software remains limited. The paper proposes a hybrid, iterative lifecycle grounded in DevOps, with quantum-agnostic development and operational phases for hybrid workloads. Its proposed roadmap aims to make development accessible to people without extensive quantum-computing expertise.
Problem
Method
The paper proposes a hybrid, iterative lifecycle that starts with quantum-agnostic coding and integrates cloud services, orchestration, translation, execution, and interpretation.
Source: §2 · p. 2, §3 · pp. 2–3Results
The proposed model outlines a lifecycle for hybrid quantum and classical software development, rather than reporting an empirical evaluation.
Source: §5 · p. 4Takeaways & Limitations
The roadmap aims to make quantum software development accessible to developers without extensive quantum-computing expertise.
Source: §5 · p. 4
Abstract
from arXiv · showhide
This paper introduces a vision for Quantum Software Development lifecycle, proposing a hybrid full-stack iterative model that integrates quantum and classical computing. Addressing the current challenges in Quantum Computing (QC) such as the need for integrating diverse programming languages and managing the complexities of quantum-classical systems, this model is rooted in the principles of DevOps and continuous software engineering. It presents a comprehensive lifecycle for quantum software development, encompassing quantum-agnostic coding, testing, deployment, cloud computing services, orchestration, translation, execution, and interpretation phases. Each phase is designed to accommodate the unique demands of QC, enabling traditional software developers to engage with QC environments without needing in-depth QC expertise. The paper presents a detailed implementation roadmap, utilizing a range of existing tools and frameworks, thereby making quantum software development more accessible and efficient. The proposed model not only addresses current challenges in quantum software development but also makes a substantial contribution to the field of Quantum Software Engineering (QSE). By proposing a structured and accessible model, it sets the stage for further advancements and research in QSE, enhancing its practicality and relevance in a wide range of applications.
1 INTRODUCTION
Quantum software development remains difficult to scale, despite growing interest in quantum computing and its potential applications. The paper proposes a hybrid, iterative lifecycle that brings classical software-engineering practices into quantum software development.
1 INTRODUCTION
- Quantum software is essential to realizing quantum computing’s industrial potential, but large-scale development remains far from widespread.The introduction notes growing interest and investment while emphasizing the slow progress of cost-effective, reliable quantum software.Source: §1 · p. 1
- Quantum software engineering applies classical software-engineering practices to quantum programming, especially to the development of hybrid quantum/classical systems.The paper identifies integrating classical and quantum systems as a key challenge in operationalizing these practices.Source: §1 · p. 1
- The paper envisions a full-stack lifecycle inspired by iterative DevOps, with quantum computations integrated iteratively.The approach adapts traditional DevOps to the intricate integration of classical and high-performance computing resources.Source: §1 · pp. 1–2
2 BACKGROUND AND MOTIVATION
Quantum software engineering needs development methods that accommodate quantum-specific complexity and hybrid systems. Building on prior work, the paper proposes an iterative lifecycle that progressively integrates classical, HPC, and quantum computing.
2 BACKGROUND AND MOTIVATION
- Quantum mechanics’ characteristics motivate new techniques, tools, processes, and methods, while QSE is expected to evolve toward adaptable, iterative development [15].The cited SEI agenda identifies integrating classical and quantum systems into a unified lifecycle as a future research challenge.Source: §2 · p. 2
- Prior studies identify multidisciplinary expertise and lifecycle integration as needs for hybrid quantum applications, alongside limited adoption and technical and socio-technical challenges.Other cited work proposes an organizational readiness model [1] and continuous deployment for quantum services.Source: §2 · p. 2
- The paper proposes a hybrid quantum, classical, and HPC lifecycle in which developers start with quantum-agnostic code and add complexity iteratively.The proposed cloud-managed process includes orchestration, translation, execution, and interpretation, aiming to support developers without extensive QC expertise.Source: §2 · p. 2
3 HYBRID FULL-STACK ITERATIVE QUANTUM SOFTWARE DEVELOPMENT MODEL
The proposed lifecycle combines quantum-agnostic development with operational phases that route, translate, execute, and interpret hybrid workloads. Iteration is incorporated across development and the quantum-specific processing stages.
3 HYBRID FULL-STACK ITERATIVE QUANTUM SOFTWARE DEVELOPMENT MODEL
- Quantum-agnostic code enters a CI/CD pipeline for repeated integration, automated testing, and deployment after tests pass.Developers refine code using feedback and test outcomes before and during the pipeline.Source: §3 · p. 3
- Cloud services provide a platform for deploying tested code, while orchestration routes classical code to classical/HPC systems and quantum code to translation.The orchestration stage classifies code by computational requirements.Source: §3 · p. 3
- Translation converts quantum-agnostic code into executable quantum code and circuits for hardware or simulators, with iterative refinement for accuracy and compatibility.The translation process must be fine-tuned across quantum systems.Source: §3 · p. 3
- Classical code runs on HPC systems and quantum code on quantum hardware; interpretation converts quantum outputs into classical data for comparison with HPC results.Interpretation can use statistical analysis and classical simulations of quantum code.Source: §3 · p. 3
4 EXECUTION ROADMAP
The execution roadmap pairs existing development, deployment, orchestration, and analysis tools with distinct classical and quantum execution environments. It outlines tools and frameworks for operationalizing the proposed lifecycle.
4 EXECUTION ROADMAP
- The roadmap suggests Qiskit, Cirq, or Microsoft Quantum Development Kit for coding, GitLab for version control, Jenkins and PyTest for CI/CD and testing, and IBM Cloud for deployment.These are proposed options for the roadmap, not reported as an evaluated implementation.Source: §4 · p. 3
- Kubernetes is proposed for orchestration, Qiskit Aer for simulator testing, HPC systems for classical code, and Rigetti Quantum Cloud Services for quantum execution.The roadmap also proposes SciPy and Tableau for interpreting and presenting integrated results, with Agile methods and cross-disciplinary training.Source: §4 · pp. 3–4
5 CONCLUSIONS
The paper proposes a Hybrid Full-Stack Iterative Quantum Software Development lifecycle grounded in DevOps and continuous software engineering. Its roadmap aims to make quantum software development more accessible and efficient, including for developers without extensive quantum expertise.
5 CONCLUSIONS
- The proposed lifecycle bridges quantum and classical computing while addressing diverse programming paradigms and quantum-classical interaction.It is grounded in DevOps and continuous software engineering.Source: §5 · p. 4
- The lifecycle spans quantum-agnostic coding, orchestrated deployment, and specialized translation through execution and interpretation.Source: §5 · p. 4
- A roadmap using modern tools and frameworks aims to make quantum software development accessible and efficient, even without extensive quantum computing expertise.The approach is presented as facilitating practical realization of quantum software engineering and laying a foundation for future advances.Source: §5 · p. 4