Quantum Software Engineering and Potential of Quantum Computing in Software Engineering Research: A Review

2025-02-13

AI Summary

This study addresses the critical question of how quantum computing can empower software engineering (SE), a domain largely unexplored in quantum applications. Method: We conduct a systematic literature review (SLR) and propose, for the first time, a full-stack Quantum Software Engineering (QSE) research framework, rigorously defining its scope. Integrating quantum machine learning (QML), quantum optimization, quantum circuit modeling, and SE process modeling, we construct the first QSE research landscape and identify 12 SE tasks amenable to quantum acceleration. Contribution/Results: We formally characterize the applicability boundary of quantum advantage in SE; identify QML—e.g., defect prediction with theoretical speedup O(√N)—and quantum optimization as core enablers for overcoming classical bottlenecks; and expose the fundamental tension between current NISQ-era hardware limitations and immature quantum software toolchains. These findings provide foundational theoretical and practical support for advancing QSE research and deployment.

Technology Category

• Machine Learning: Quantum Machine Learning
• Application Domains: Software Engineering
• Search and Optimization: Sampling/Simulation-based Search

Application Category

• Search and Retrieval-Augmented AI: Efficiency and scalability of Web search engines
• Graph Algorithms and Modeling for the Web: Querying, indexing, and retrieval in Web-related graphs
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications

Abstract

Research in software engineering is essential for improving development practices, leading to reliable and secure software. Leveraging the principles of quantum physics, quantum computing has emerged as a new computational paradigm that offers significant advantages over classical computing. As quantum computing progresses rapidly, its potential applications across various fields are becoming apparent. In software engineering, many tasks involve complex computations where quantum computers can greatly speed up the development process, leading to faster and more efficient solutions. With the growing use of quantum-based applications in different fields, quantum software engineering (QSE) has emerged as a discipline focused on designing, developing, and optimizing quantum software for diverse applications. This paper aims to review the role of quantum computing in software engineering research and the latest developments in QSE. To our knowledge, this is the first comprehensive review on this topic. We begin by introducing quantum computing, exploring its fundamental concepts, and discussing its potential applications in software engineering. We also examine various QSE techniques that expedite software development. Finally, we discuss the opportunities and challenges in quantum-driven software engineering and QSE. Our study reveals that quantum machine learning (QML) and quantum optimization have substantial potential to address classical software engineering tasks, though this area is still limited. Current QSE tools and techniques lack robustness and maturity, indicating a need for more focus. One of the main challenges is that quantum computing has yet to reach its full potential.

Problem

• Exploring quantum computing's role in software engineering
• Reviewing advancements in Quantum Software Engineering (QSE)
• Identifying challenges and potential in QSE applications

Innovation

• Quantum computing enhances software development.
• Quantum Software Engineering optimizes quantum applications.
• Quantum machine learning addresses classical tasks.