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.
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.
As quantum computing continues to advance, the development of reliable and scalable quantum software systems becomes increasingly crucial. However, designing and implementing hybrid (quantum-classical) software systems poses unique challenges that require novel approaches and best practices. This position paper argues for the importance of developing architectural and design patterns specific to Quantum Software Engineering (QSE). We provide an overview of existing quantum software design patterns (more focused on low-level, programming details) and highlight the lack of patterns addressing hybrid software systems and architectural patterns. We discuss the key challenges that architectural patterns should address, including quantum-classical integration, maintainability, efficiency, and security. We also discuss the implications for practitioners, providing guidance on how to think high-level about hybrid software development process. Finally, we outline future research directions and emphasize the need for collaboration between the quantum computing and software engineering communities to establish a comprehensive high-level patterns framework for QSE.
Abstract Quantum computing is an emerging field in which theoretical principles are being transformed into practical applications, largely due to the efforts of the developer community. In order to ensure that quantum software engineering continues to advance, it is vital to understand the experiences, challenges, and aspirations of developers. This chapter is a continuation of our previous work, which provided a comprehensive survey exploring the adoption patterns and common challenges in quantum software engineering. In addition to the survey, we conducted in-depth, semi-structured interviews with practitioners in the field to gain a deeper and more detailed understanding of their perspectives. Through the interviews and survey findings, we have gained nuanced insights into the motivations, hurdles, and outlook of developers toward the rapidly evolving quantum computing landscape. We describe the research methodology in detail, including the tools and techniques used, in order to provide a comprehensive understanding of the research process. Furthermore, we present critical insights from both the survey and interviews, enriching the narrative with fresh perspectives obtained from the post-publication interviews. This chapter is a blend of academic investigation and real-world practitioner insights, aiming to provide a comprehensive understanding of the current state of quantum software engineering. By illuminating the path for future research and development in this dynamic field, we hope to guide the way toward continued progress and innovation.
With recent breakthroughs in quantum computing, it has become a coming reality instead of a promising future. Quantum computing applications offer revolutionary potential across multiple domains including artificial intelligence (AI), optimization, healthcare, energy, and space, known as quantum advantage. The power of quantum computing relies on novel quantum algorithms, quantum software, and hardware. Unlike classical software, quantum software has unique features because of quantum mechanics such as superposition and noncloning. This opens a new research field - quantum software engineering (QSE). While the software engineering (SE) research community became aware of this need in 2019, we noticed the lack of a comprehensive investigation of state-of-the-art technologies and tools to improve quantum software quality. Testing and debugging are the two most efficient approaches to assure software quality in classical SE. In QSE, testing and debugging quantum programs become challenging due to quantum mechanics. While we can leverage some best practices from the classical world, new techniques and tools are needed to address the concerns in QSE. In this chapter, we first conduct a survey study of the state-of-the-art technologies and tools for testing and debugging quantum software. This study includes but is not limited to quantum bug pattern analysis and detection, quantum software testing techniques and classification, and quantum debugging techniques. In the second place, we provide our visions and insights of testing and debugging quantum software in terms of challenges and opportunities for improving quantum software quality. This survey has the potential to foster a research community committed to developing novel methods and tools for QSE.
Quantum computing is poised to revolutionize computational paradigms by leveraging quantum mechanics principles such as superposition and entanglement.However, the full-scale deployment of quantum applications remains constrained by hardware limitations, including high error rates and quantum decoherence.Quantum Software Engineering (QSE) emerges as a critical field addressing these challenges by optimizing algorithm design, error mitigation, and compiler strategies to enhance fault tolerance.Algorithm design in QSE focuses on developing quantum algorithms that efficiently exploit quantum parallelism while minimizing resource overhead.Key advancements include quantum variational algorithms, hybrid quantum-classical frameworks, and novel quantum heuristics tailored for optimization and cryptographic problems.Error mitigation techniques play a pivotal role in extending quantum circuit reliability without requiring full quantum error correction.Methods such as zero-noise extrapolation, probabilistic error cancellation, and quantum embedding techniques help reduce computational inaccuracies.Additionally, compiler optimization ensures efficient quantum program execution by minimizing gate depth, optimizing qubit mapping, and leveraging noise-adaptive scheduling to enhance quantum hardware performance.This paper explores the synergy between these three pillars of QSE, analyzing their impact on improving the feasibility of fault-tolerant quantum computing.It also examines emerging trends, including AI-driven quantum compilers, adaptive error mitigation techniques, and hardware-aware quantum software development.By bridging the gap between theoretical advancements and practical implementations, QSE provides a structured approach to accelerating quantum computing adoption across domains such as cryptography, materials science, and artificial intelligence.The findings underscore the necessity of interdisciplinary collaboration in developing robust quantum software solutions that maximize computational efficiency while mitigating inherent quantum hardware limitations.
Quantum computing is rapidly transitioning from a scientific curiosity to an industrial reality, offering the potential to overcome classical computation limitations. This shift has given rise to the field of quantum software engineering (QSE), focused on developing novel approaches for engineering large-scale quantum applications. Traditional software engineering methods fall short in addressing the unique characteristics of quantum computing, necessitating innovative QSE methodologies and tools. While progress has been made in testing and debugging quantum programs, very little work has been done on analyzing if and how existing requirements engineering techniques can address the challenges that designing quantum software raises. This paper discusses some of the challenges for requirements engineers while eliciting requirements for quantum software, modeling the collected requirements, and analyzing them, and introduces some initial solutions for eliciting, modeling, and analyzing quantum requirements.
Context: Quantum software development is a complex and intricate process that diverges significantly from traditional software development. Quantum computing and quantum software are deeply entangled with quantum mechanics, which introduces a different level of abstraction and a deep dependence on quantum physical properties. The classical requirements engineering methods must be adapted to encompass the essential quantum features in this new paradigm. Aim: This study aims to systematically identify and analyze challenges, opportunities, developments, and new lines of research in requirements engineering for quantum computing. Method: We conducted a systematic literature review, including three research questions. This study included 105 papers published from 2017 to 2024. Results: The main results include the identification of problems associated with defining specific requirements for quantum software and hybrid system requirements. In addition, we identified challenges related to the absence of standards for quantum requirements engineering. Finally, we can see the advances in developing programming languages and simulation tools for developing software in hybrid systems. Conclusions: This study presents the challenges and opportunities in quantum computing requirements engineering, emphasizing the need for new methodologies and tools. It proposes a roadmap for future research to develop a standardized framework, contributing to theoretical foundations and practical applications.