As the scientific community is increasing the coverage of the quantum computing domain ranging from theoretical physics to financial applications, so does the number of quantum computing applications being developed for quantum computing hardware that is available today. As this hardware evolves towards increased capacity in terms of qubit number and increased fidelity, so does the complexity of quantum computing applications that implement the state-of-the-art of (hybrid) quantum algorithms. With this comes an increased demand for quantum software engineering practices where testing is a crucial part of the development process. Hence, a robust approach that addresses certain challenges and peculiarities related to the quantum computing domain is needed for the testing process. This paper proposes a standard-ready testing pipeline that covers the requirements of testing in a continuous development cycle as part of a modern quantum software engineering lifecycle.
As the scientific community is increasing the coverage of the quantum computing domain ranging from theoretical physics to financial applications, so does the number of quantum computing applications being developed for quantum computing hardware that is available today. As this hardware evolves towards increased capacity in terms of qubit number and increased fidelity, so does the complexity of quantum computing applications that implement the state-of-the-art of (hybrid) quantum algorithms. With this comes an increased demand for quantum software engineering practices where testing is a crucial part of the development process. Hence, a robust approach that addresses certain challenges and peculiarities related to the quantum computing domain is needed for the testing process. This paper proposes a standard-ready testing pipeline that covers the requirements of testing in a continuous development cycle as part of a modern quantum software engineering lifecycle.
As quantum computing transitions from a theoretical domain to a practical technology, many aspects of established practice in software engineering are being faced with new challenges. Quantum Software Engineering has been developed to address the peculiar needs that arise with quantum systems’ dependable, scalable, and fault-tolerant software development. The present paper critically reviews how traditional software engineering methodologies can be reshaped to fit into the quantum field. This also entails providing some critical contributions: frameworks to integrate classical and quantum systems, new error mitigation techniques, and the development of quantum-specific testing and debugging tools. In this respect, best practices have been recommended to ensure that future quantum software can harness the evolving capabilities of quantum hardware with continued performance, reliability, and scalability. The work is supposed to act as a foundational guide for the researcher and developer as quantum computing approaches widespread scientific and industrial adoption.
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.
Quantum computing is an emerging paradigm that enables to solve a variety of problems more efficiently than it is possible on classical computers. As the first quantum computers are available, quantum algorithms can be implemented and executed on real quantum hardware. However, the capabilities of today’s quantum computers are very limited and quantum computations are always disturbed by some error. Thus, further research is needed to develop or improve quantum algorithms, quantum computers, or required software tooling support. Due to the interdisciplinary nature of quantum computing, a common understanding of how to develop and execute a quantum software application is needed. However, there is currently no methodology or lifecycle comprising all relevant phases that can occur during the development and execution process. Hence, in this paper, we introduce the quantum software lifecycle consisting of ten phases a gate-based quantum software application should go through. We analyze the purpose of each phase, the available methods and tools that can be applied, and the open problems or research questions. Therefore, the lifecycle can be used as a baseline for discussions and future research.
The advent of quantum computing has ushered in a new era of technological innovation, promising unprecedented computational power and efficiency. As quantum technology matures, the need for robust, scalable, and efficient software development practices becomes increasingly critical. This paper proposes a novel DevOps framework tailored specifically for quantum software development, addressing unique challenges posed by quantum computing. The proposed architecture incorporates continuous integration and continuous deployment (CI/CD) pipelines, optimized for quantum algorithms, facilitating seamless integration and deployment of quantum applications. Key components include a Quantum Circuit Service for circuit design and optimization, a Quantum CI Service for continuous integration, and a comprehensive testing suite encompassing unit, integration, functional, and probabilistic testing. The framework emphasizes the use of large language models (LLMs) for automated microservice code generation, Kubernetes (K8s) cluster deployment for scalable infrastructure management, and a central quantum artifacts registry for efficient version control and resource management. A significant portion of this paper is dedicated to addressing the unique aspects of quantum computing, including the probabilistic nature of quantum algorithms, the need for specialized testing strategies, and the integration of classical and quantum software components. The proposed framework not only enhances the efficiency and reliability of quantum software development but also provides a structured approach to managing the complexities associated with quantum computing.
The understanding of the Agile development practices and quantum computer are becoming more and more a requirement as the engineering projects of the day are growing extremely complicated and dynamic. Agile methods that are familiar to facilitate an iterative cycle, cooperate and adaptability are inherently appropriate to the experimental and unpredictable world of quantum software development. Quantum computing (QC) that is grounded on the principles of superposition and entanglement is the origin of novel computational paradigms that require new programming and continuous fine-tuning. In addition to satisfying this need for brief development cycles and quick feedback loops, other Agile methods like Scrum, Kanban, and Extreme Programming (XP) also demand rigorous planning. On the other hand, quantum software engineering is faced with specific issues such as the unskilled personnel, testing issues, and hardware limitations. In that case, the Agile methodologies are salvaged and assist in the breaking down of complex and quantum tasks into manageable units and result in a continuous improvement. All in all, standardization of Agile practices and quantum computing does not just assist in the innovation, but also in reduction of the risk of development and speeding up the development of the practical quantum solutions to the current engineering projects.
Quantum computing is getting increasing interest from both academia and industry, and the quantum software landscape has been growing rapidly. The quantum software stack comprises quantum programs, implementing algorithms, and platforms like IBM Qiskit, Google Cirq, and Microsoft Q#, enabling their development. To ensure the reliability and performance of quantum software, various techniques for testing and analyzing it have been proposed, such as test generation, bug pattern detection, and circuit optimization. However, the large amount of work and the fact that work on quantum software is performed by several research communities, make it difficult to get a comprehensive overview of the existing techniques. In this work, we provide an extensive survey of the state of the art in testing and analysis of quantum software. We discuss literature from several research communities, including quantum computing, software engineering, programming languages, and formal methods. Our survey covers a wide range of topics, including expected and unexpected behavior of quantum programs, testing techniques, program analysis approaches, optimizations, and benchmarks for testing and analyzing quantum software. We create novel connections between the discussed topics and present them in an accessible way. Finally, we discuss key challenges and open problems to inspire future research.