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.
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.
The 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. This article is published in IE Perspectives, Issue 1 (January 2026). Full issue available at: https://doi.org/10.5281/zenodo.18376222
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 holds the potential to change our world. Following the quantum wave, software engineers have recognised the opportunity to establish a new discipline of Quantum Software Engineering. Despite the significant progress achieved, Quantum Computing's widespread adoption still faces critical hurdles. In this paper, we outline two of these challenges. (1) Quantum programming continues to be a complex art mastered by a select few experts. We suggest that the primary culprit can be pinpointed in the absence of high-level quantum software abstractions which forces developers to work with low-level quantum concepts and reason in terms of matrix multiplications. (2) The scarce collaboration among quantum software engineers resulted in a lack of platform and software interoperability. While a diversity of research proposals fuels scientific progress, it can hinder the development and adoption of innovative technologies, potentially fragmenting the collective efforts and confining them within isolated research groups. We believe that overcoming these issues is crucial for fostering innovation, advancing Quantum Software Engineering, and Quantum Computing as a whole.
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.
Quantum Computing (QC) has evolved into a computational model that can potentially solve problems of classes that cannot be solved by classical systems. This review gives a discussion on the innovation of software frameworks, experimental platforms and quantum computing tools used to compute quantum algorithm development, simulation and implementation. It concentrates on widely used programming environments, which compile abstract quantum models into practical workflows, including Cirq, TensorFlow Quantum, ProjectQ and Qiskit. The paper, besides describing the long-lasting problems related to scalability, error correction, and hardware reliability, also considers the architecture of the modern quantum computing platforms. Finally, new advances are outlined, such as quantum cloud service and the integration of artificial intelligence and quantum computing, and their role in the development of QC to viable and lucrative deployments. All in all, the discussion suggests that even now quantum computing still needs to be taken to the next level in terms of hardware infrastructure and software development that would allow progressing to the next stage of quantum technology testing and implementation.
Quantum computing has transitioned from a theoretical curiosity to an emerging technological paradigm with demonstrable computational advantages in specific problem domains. This paper presents a comprehensive review of current advances in quantum computing hardware, software, and near-term applications within the Noisy Intermediate-Scale Quantum (NISQ) era. We examine the architectural evolution of leading quantum platforms, including superconducting, trapped-ion, and photonic systems, analyzing their qubit counts, gate fidelities, and coherence times. The paper evaluates key quantum algorithms Shor's factoring algorithm [1], Grover's search algorithm [2], the Variational Quantum Eigensolver (VQE) [3], and the Quantum Approximate Optimization Algorithm (QAOA) [4] in the context of their practical applicability to real-world problems. We further discuss the milestone of quantum computational advantage demonstrated by Google's Sycamore processor [5] and IBM's ambitious hardware roadmap toward fault-tolerant quantum computing [6]. Our analysis reveals that while universal fault-tolerant quantum computing remains a long-term objective, NISQ-era devices are already yielding valuable results in quantum chemistry simulation, combinatorial optimization, and quantum machine learning. We conclude by identifying the critical challenges—error correction, scalability, and algorithm design that must be addressed to realize the full potential of quantum computing.