Challenges for Quantum Software Engineering: An Industrial Application Scenario Perspective
Cecilia Carbonelli, Michael Felderer, Matthias Jung, Elisabeth Lobe, Malte Lochau, Sebastian Markus Luber, Wolfgang Mauerer, Rudolf Ramler, Ina Schaefer, Christoph Schroth
Abstract Quantum software is becoming a key enabler for applying quantum computing to industrial use cases. This poses challenges to quantum software engineering in providing efficient and effective means to develop such software. Eventually, this must be reliably achieved in time, on budget, and in quality, using sound and well-principled engineering approaches. Given that quantum computers are based on fundamentally different principles than classical machines, this raises the question if, how, and to what extent established techniques for systematically engineering software need to be adapted. In this chapter, we analyze three paradigmatic application scenarios for quantum software engineering from an industrial perspective. The respective use cases center around (1) optimization and quantum cloud services, (2) quantum simulation, and (3) embedded quantum computing. Our aim is to provide a concise overview of the current and future applications of quantum computing in diverse industrial settings. We derive presumed challenges for quantum software engineering and thus provide research directions for this emerging field.
Abstract Quantum software is becoming a key enabler for applying quantum computing to industrial use cases. This poses challenges to quantum software engineering in providing efficient and effective means to develop such software. Eventually, this must be reliably achieved in time, on budget, and in quality, using sound and well-principled engineering approaches. Given that quantum computers are based on fundamentally different principles than classical machines, this raises the question if, how, and to what extent established techniques for systematically engineering software need to be adapted. In this chapter, we analyze three paradigmatic application scenarios for quantum software engineering from an industrial perspective. The respective use cases center around (1) optimization and quantum cloud services, (2) quantum simulation, and (3) embedded quantum computing. Our aim is to provide a concise overview of the current and future applications of quantum computing in diverse industrial settings. We derive presumed challenges for quantum software engineering and thus provide research directions for this emerging field.
As quantum computers advance, the complexity of the software they can execute increases as well. To ensure this software is efficient, maintainable, reusable, and cost-effective—key qualities of any industry-grade software—mature software engineering practices must be applied throughout its design, development, and operation. However, the significant differences between classical and quantum software make it challenging to directly apply classical software engineering methods to quantum systems. This challenge has led to the emergence of Quantum Software Engineering (QSE) as a distinct field within the broader software engineering landscape. In this work, a group of active researchers analyze in depth the current state of QSE research. From this analysis, the key areas of QSE are identified and explored in order to determine the most relevant open challenges that should be addressed in the next years. These challenges help identify necessary breakthroughs and future research directions for advancing 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.
Quantum computing is rapidly emerging as a new computing paradigm with the potential to improve decision-making, optimization, and simulation across industries. For industrial engineering (IE) and operations research (OR), this shift introduces both unprecedented opportunities and substantial challenges. The learning curve is high, and to help researchers navigate the emerging field of quantum operations research, we provide a road map of the current field of quantum operations research. We introduce the foundational principles of quantum computing, outline the current hardware and software landscape, and survey major algorithmic advances relevant to IE/OR, including quantum approaches to linear algebra, optimization, machine learning, and stochastic simulation. We then highlight applied research directions, including the importance of problem domains for driving long-term value of quantum computers and how existing classical OR models can be reformulated for quantum hardware. Recognizing the steep learning curve, we propose pathways for IE/OR researchers to develop technical fluency and engage in this interdisciplinary domain. By bridging theory with application, and emphasizing the interplay between hardware and research development, we argue that industrial engineers are uniquely positioned to shape the trajectory of quantum computing for practical problem-solving. Ultimately, we aim to lower the barrier to entry into quantum computing, motivate new collaborations, and chart future directions where quantum technologies may deliver tangible impact for industry and academia.
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.
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.
Abstract Quantum computing (QC) hinged upon the bedrock principles of quantum theory and holds promise for reforming a large number of industries. The researcher in this area aims to deliver a comprehensive understanding of the current state of the art and future trajectories of QC. The authors have discovered that most academic studies have concentrated upon dissecting specific aspects of QC. This discernment underscores the exigency of identifying challenges that might impede the seamless integration of QC within the software industry. Moreover, it becomes crucial to ascertain the panoply of solutions/practices required to overcome these barriers. A comprehensive multi‐vocal literature review was performed and culled a total of 49 academic papers for data extraction. A total of 13 challenges encountered by organisations were identified during the adoption of QC. Subsequently, these challenges were examined deeply and determined that five of them are the most critical, these are ‘Lack of quantum specific algorithms, dev and testing methodologies’, ‘Difficult compilation and debugging’, ‘Lack of development tools and technology’, ‘Lack of development guidelines & Quality Assurance Standards’ and ‘Lack of professional expert’, together founding over 30% of occurrences. These challenges from various perspectives were evaluated, including time frame, methodology, geographical region and publication platform. To address these barriers and implement the QC in software industry effectively, a total of 53 practices/solutions. This research aims to share valuable knowledge to simplify and amplify quantum application development.