To unlock the full potential of quantum computing, the eld must develop a robust software ecosystem grounded in classical software engineering principles—a discipline that itself needs to be adapted to the quantum domain. Currently, however, the advancement of quantum computing is hampered by a growing “software gap,” where a fragmented and non-standardized ecosystem of tools hinders progress. Much of the existing quantum software originates from academic proofs-of-concept that often lack the robustness, maintainability, and scalability required for practical applications. This article argues that bridging this gap requires the systematic application of principles from classical software engineering and design automation. We present the Munich Quantum Toolkit (MQT) as a case study, showcasing a suite of open-source tools built on these principles. By tracing its evolution, we distill key lessons learned in testing, deployment, and community-driven development. We demon-strate that adopting a rigorous software engineering culture is essential for building the reliable and sustainable software infrastructure needed to unlock the full potential of quantum computing.
To unlock the full potential of quantum computing, the eld must develop a robust software ecosystem grounded in classical software engineering principles—a discipline that itself needs to be adapted to the quantum domain. Currently, however, the advancement of quantum computing is hampered by a growing “software gap,” where a fragmented and non-standardized ecosystem of tools hinders progress. Much of the existing quantum software originates from academic proofs-of-concept that often lack the robustness, maintainability, and scalability required for practical applications. This article argues that bridging this gap requires the systematic application of principles from classical software engineering and design automation. We present the Munich Quantum Toolkit (MQT) as a case study, showcasing a suite of open-source tools built on these principles. By tracing its evolution, we distill key lessons learned in testing, deployment, and community-driven development. We demon-strate that adopting a rigorous software engineering culture is essential for building the reliable and sustainable software infrastructure needed to unlock the full potential of quantum computing.
This article provides an overview of the current state and future challenges of quantum software engineering as quantum computing transitions from proof-of-concept to potential industrial adoption. While significant progress has been made in quantum hardware and cloud-based execution platforms, the article argues that innovation will depend critically on advances in software tools, programming abstractions, and engineering methodologies. Focusing on the constraints of the Noisy Intermediate-Scale Quantum (NISQ) era, it examines challenges related to hardware heterogeneity, software portability, hybrid classical–quantum architectures, and the lack of mature development environments. The article also highlights the urgent need for a new generation of quantum software engineers and coherent educational programmes, particularly in Europe, to bridge skills gaps and support the long-term evolution toward fault-tolerant quantum computing.
Quantum computing is quickly becoming a potentially disruptive technology that can tackle the problems inaccessible to classical computers, but the use of quantum computing in real software systems has yet to be fully explored. Present day quantum studies are largely focused on the development of algorithms and hardware, whereas engineering workflows to be used to enable smooth hybrid quantum-classical operations attract limited attention. The paper suggests a concept of quantum-ready software engineering- a systematic approach to applying established principles of software engineering to hybrid systems. In order to meet maintainability, scalability, and reliability objectives in hybrid applications, propose the adoption of a multilayered design, such as abstraction, integration, orchestration, and verification. An example concrete programming template, written in Python in Qiskit, demonstrates how quantum functions being used as modular services can be simulated with classical software. Evaluation measures (maintainability index, latency, and modularity) demonstrate the feasibility of the framework. Results indicate that the hybrid pipelines can be designed in a systematic way using quantum-classical-adapted design patterns. The study introduces a repeatable methodology, program templates, and design pattern engineering principles, which open the door to additional development of quantum DevOps and design pattern formalization. This project, by bridging the gap between classical software engineering and quantum integration, gives a platform upon which to build extraordinarily reliable, scalable systems in the Noisy Intermediate-Scale Quantum and beyond.
Quantum computers are becoming a reality and numerous quantum computing applications with a near-term perspective (e.g., for finance, chemistry, machine learning, and optimization) and with a long-term perspective (e.g., for cryptography or unstructured search) are currently being investigated. However, designing and realizing potential applications for these devices in a scalable fashion requires automated, efficient, and user-friendly software tools that cater to the needs of end users, engineers, and physicists at every level of the entire quantum software stack. Many of the problems to be tackled in that regard are similar to design problems from the classical realm for which sophisticated design automation tools have been developed in the previous decades.The Munich Quantum Toolkit (MQT) is a collection of software tools for quantum computing developed by the Chair for Design Automation at the Technical University of Munich which explicitly utilizes this design automation expertise. Our overarching objective is to provide solutions for design tasks across the entire quantum software stack. This entails high-level support for end users in realizing their applications, efficient methods for the classical simulation, compilation, and verification of quantum circuits, tools for quantum error correction, support for physical design, and more. These methods are supported by corresponding data structures (such as decision diagrams or the ZX-calculus) and core methods (such as SAT encodings/solvers). All of the developed tools are available as open-source implementations and are hosted on github.com/cda-tum.Note: A live version of this document is available at mqt.readthedocs.io.
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.
Quantum computing is rapidly emerging as a transformative force poised to redefine the foundations of software engineering. By leveraging quantum mechanical phenomena such as superposition, entanglement, and interference, quantum computers offer the potential to solve complex problems far beyond the reach of classical systems. This paper explores the multifaceted impact of quantum computing on software engineering, focusing on key areas including quantum algorithms, cryptography, programming paradigms, and application domains. It examines how quantum algorithms like Shor's and Grover's promise significant computational speedups, threatening classical encryption schemes and prompting the rise of post-quantum cryptography. The paper also analyzes the challenges of quantum programming, including steep learning curves, limited hardware access, and the need for new development tools and testing frameworks. These challenges highlight the current limitations of quantum technology, such as hardware instability and scalability issues. As quantum hardware evolves, the integration of hybrid quantum-classical systems is identified as a practical approach for near-term applications in areas such as drug discovery, finance, and optimization. The paper further discusses ethical considerations, such as equitable access to quantum resources and privacy concerns, alongside potential societal impacts to ensure responsible innovation. It underscores the need for future advancements in education, standardization, and hybrid systems to bridge the gap between current limitations and quantum computing’s potential. The paper concludes by emphasizing the importance of educational reform, standardization, and ethical considerations in preparing the software engineering community for a quantum-driven future.
Quantum computing promises transformative computational capabilities; however, the absence of structured and standardized software engineering significantly limits its practical scalability. Quantum Software Engineering (QSE) remains fragmented, tool-centric, and largely experimental. This paper proposes a structured Quantum Software Engineering Lifecycle Framework that systematically integrates requirements engineering, hybrid design, quantum development, verification, deployment, and governance. To validate the proposed lifecycle, a two-stage evaluation was conducted. First, a Delphi-based expert validation involving 15 domain experts assessed clarity, feasibility, scalability, and hybrid applicability. Second, a simulation-based comparative analysis using Qiskit and PennyLane evaluated the lifecycle against ad-hoc development workflows across variational and search-based quantum algorithms. Results demonstrate a 24% reduction in development time, 15–18% improvement in execution fidelity, and significant gains in modularity, reusability, and tool interoperability. These findings confirm that adopting a structured lifecycle enables more reliable, scalable, and sustainable quantum software development, positioning QSE as a mature engineering discipline rather than purely experimental practice.