Abstract Quantum computing systems harness the power of quantum mechanics to execute computationally demanding tasks more effectively than their classical counterparts. This has led to the emergence of Quantum Software Engineering (QSE), which focuses on unlocking the full potential of quantum computing systems. As QSE gains prominence, it seeks to address the evolving challenges of quantum software development by offering comprehensive concepts, principles, and guidelines. This paper aims to identify, prioritize, and develop a systematic decision-making framework of the challenging factors associated with QSE process execution. We conducted a literature survey to identify the challenging factors associated with QSE process and mapped them into 7 core categories. Additionally, we used a questionnaire survey to collect insights from practitioners regarding these challenges. To examine the relationships between core categories of challenging factors, we applied Interpretive Structure Modeling (ISM). Lastly, we applied fuzzy TOPSIS to rank the identified challenging factors concerning to their criticality for QSE process. We have identified 22 challenging factors of QSE process and mapped them to 7 core categories. The ISM results indicate that the ‘resources’ category has the most decisive influence on the other six core categories of the identified challenging factors. Moreover, the fuzzy TOPSIS indicates that ‘complex programming’, ‘limited software libraries’, ‘maintenance complexity’, ‘lack of training and workshops’, and ‘data encoding issues’ are the highest priority challenging factor for QSE process execution. Organizations using QSE could consider the identified challenging factors and their prioritization to improve their QSE process.
Abstract Quantum computing systems harness the power of quantum mechanics to execute computationally demanding tasks more effectively than their classical counterparts. This has led to the emergence of Quantum Software Engineering (QSE), which focuses on unlocking the full potential of quantum computing systems. As QSE gains prominence, it seeks to address the evolving challenges of quantum software development by offering comprehensive concepts, principles, and guidelines. This paper aims to identify, prioritize, and develop a systematic decision-making framework of the challenging factors associated with QSE process execution. We conducted a literature survey to identify the challenging factors associated with QSE process and mapped them into 7 core categories. Additionally, we used a questionnaire survey to collect insights from practitioners regarding these challenges. To examine the relationships between core categories of challenging factors, we applied Interpretive Structure Modeling (ISM). Lastly, we applied fuzzy TOPSIS to rank the identified challenging factors concerning to their criticality for QSE process. We have identified 22 challenging factors of QSE process and mapped them to 7 core categories. The ISM results indicate that the ‘resources’ category has the most decisive influence on the other six core categories of the identified challenging factors. Moreover, the fuzzy TOPSIS indicates that ‘complex programming’, ‘limited software libraries’, ‘maintenance complexity’, ‘lack of training and workshops’, and ‘data encoding issues’ are the highest priority challenging factor for QSE process execution. Organizations using QSE could consider the identified challenging factors and their prioritization to improve their QSE process.
Context: Quantum Computing (QC) systems exploit the characteristics of quantum mechanics to perform computationally demanding tasks more effectually than their classical counterparts. To utilize the full potential of QC systems, Quantum Software Engineering (QSE) has emerged to manage the challenges of quantum software development. Problem: Due to the lack of awareness of QC problem domains and their associated factors to consider and apply QC in the Software Engineering (SE) process, the development of a QC system becomes complex and less cost effective if without a guidance for software engineers. Objective: The proposed work aims to develop a systematic decision-making framework to help identify the quantum problem domains and prioritize the critical factors to be considered for the application of QC during the software development life cycle (SDLC). Method: The proposed method is implemented in two folds. First, a Systematic Literature Review (SLR) is performed to identify a set of QC problem domains and their associated factors that should be accounted for in the SE process. Second, an online survey is conducted to collect insights on the same aspects from practitioners in their SE processes to form another set of data. Finally, the relationships of the two sets are validated through careful mappings with the assistance of domain experts. Results: Five problem domains and six factors are classified by the proposed methodology, and some of them will benefit from a QC-based solution in the SE process. The results indicate that "Algorithm Development" and "Language Development" are two potential problem domains to apply a QC-based solution. For these two domains, "Current Hardware Limitations", "Standardized Coding Practices" and "Software Specialization/Adaptation" are the critical factors to be considered during the SE process. Conclusion: Organizations and QSE community can take advantage of the identified problem domains and their associated factors to make decisions in the recommendation of QC-based solutions.
The current technology revolution has posed unexpected challenges for the software industry. In recent years, the field of quantum computing (QC) technologies has continued to grow in influence and maturity, and it is now poised to revolutionise software engineering. However, the evaluation and prioritisation of QC challenges in the software industry remain unexplored, relatively under-identified and fragmented. The purpose of this study is to identify, examine and prioritise the most critical challenges in the software industry by implementing a fuzzy analytic hierarchy process (F-AHP). First, to identify the key challenges, we conducted a systematic literature review by drawing data from the four relevant digital libraries and supplementing these efforts with a forward and backward snowballing search. Second, we followed the F-AHP approach to evaluate and rank the identified challenges, or barriers. The results show that the key barriers to QC adoption are the lack of technical expertise, information accuracy and organisational interest in adopting the new process. Another critical barrier is the lack of standards of secure communication techniques for implementing QC. By applying F-AHP, we identified institutional barriers as the highest and organisational barriers as the second highest global weight ranked categories among the main QC challenges facing the software industry. We observed that the highest-ranked local barriers facing the software technology industry are the lack of resources for design and initiative while the lack of organisational interest in adopting the new process is the most significant organisational barrier. Our findings, which entail implications for both academicians and practitioners, reveal the emergent nature of QC research and the increasing need for interdisciplinary research to address the identified challenges.
Context The current technology revolution has posed unexpected challenges for the software industry. In recent years, the field of quantum computing (QC) technologies has continued to grow in influence and maturity, and it is now poised to revolutionise software engineering. However, the evaluation and prioritisation of QC challenges in the software industry remain unexplored, relatively under-identified and fragmented. Objective The purpose of this study is to identify, examine and prioritise the most critical challenges in the software industry by implementing a fuzzy analytic hierarchy process (F-AHP). Method First, to identify the key challenges, we conducted a systematic literature review by drawing data from the four relevant digital libraries and supplementing these efforts with a forward and backward snowballing search. Second, we followed the F-AHP approach to evaluate and rank the identified challenges, or barriers. Results The results show that the key barriers to QC adoption are the lack of technical expertise, information accuracy and organisational interest in adopting the new process. Another critical barrier is the lack of standards of secure communication techniques for implementing QC. Conclusion By applying F-AHP, we identified institutional barriers as the highest and organisational barriers as the second highest global weight ranked categories among the main QC challenges facing the software industry. We observed that the highest-ranked local barriers facing the software technology industry are the lack of resources for design and initiative while the lack of organisational interest in adopting the new process is the most significant organisational barrier. Our findings, which entail implications for both academicians and practitioners, reveal the emergent nature of QC research and the increasing need for interdisciplinary research to address the identified challenges.
Quantum computing is becoming a reality, and quantum software engineering (QSE) is emerging as a new discipline to enable developers to design and develop quantum programs. This paper presents a systematic mapping study of the current state of QSE research, aiming to identify the most investigated topics, the types and number of studies, the main reported results, and the most studied quantum computing tools/frameworks. Additionally, the study aims to explore the research community’s interest in QSE, how it has evolved, and any prior contributions to the discipline before its formal introduction through the Talavera Manifesto. We searched for relevant articles in several databases and applied inclusion and exclusion criteria to select the most relevant studies. After evaluating the quality of the selected resources, we extracted relevant data from the primary studies and analyzed them. We found that QSE research has primarily focused on software testing, with little attention given to other topics, such as software engineering management. The most commonly studied technology for techniques and tools is Qiskit, although, in most studies, either multiple or none specific technologies were employed. The researchers most interested in QSE are interconnected through direct collaborations, and several strong collaboration clusters have been identified. Most articles in QSE have been published in non-thematic venues, with a preference for conferences. The study’s implications are providing a centralized source of information for researchers and practitioners in the field, facilitating knowledge transfer, and contributing to the advancement and growth of QSE.
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.
Context. Quantum computing is becoming a reality, and quantum software engineering (QSE) is emerging as a new discipline to enable developers to design and develop quantum programs. Objective. This paper presents a systematic mapping study of the current state of QSE research, aiming to identify the most investigated topics, the types and number of studies, the main reported results, and the most studied quantum computing tools/frameworks. Additionally, the study aims to explore the research community's interest in QSE, how it has evolved, and any prior contributions to the discipline before its formal introduction through the Talavera Manifesto. Method. We searched for relevant articles in several databases and applied inclusion and exclusion criteria to select the most relevant studies. After evaluating the quality of the selected resources, we extracted relevant data from the primary studies and analyzed them. Results. We found that QSE research has primarily focused on software testing, with little attention given to other topics, such as software engineering management. The most commonly studied technology for techniques and tools is Qiskit, although, in most studies, either multiple or none specific technologies were employed. The researchers most interested in QSE are interconnected through direct collaborations, and several strong collaboration clusters have been identified. Most articles in QSE have been published in non-thematic venues, with a preference for conferences. Conclusions. The study's implications are providing a centralized source of information for researchers and practitioners in the field, facilitating knowledge transfer, and contributing to the advancement and growth of QSE.