[Paper Review] Quantum Software Engineering: Roadmap and Challenges Ahead

Juan M. Murillo, José Garcí­a-Alonso+14 more|arXiv (Cornell University)|Apr 10, 2024

Quantum Computing Algorithms and Architecture7 citations

TL;DR

This paper surveys the field of Quantum Software Engineering (QSE), outlines active research areas, challenges, and anticipated directions for the next decade. It articulates how classical software engineering can inform QSE and where new paradigms are needed.

ABSTRACT

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 as a distinct field within the broader software engineering landscape. In this work, a group of active researchers analyse in depth the current state of quantum software engineering research. From this analysis, the key areas of quantum software engineering 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 Quantum Software Engineering.

Motivation & Objective

• Motivate the development of QSE as a discipline by highlighting its importance as quantum hardware evolves.
• Summarize current research in key QSE areas and identify gaps hindering industry adoption.
• Discuss how classical software engineering concepts (e.g., SOC, MDE, testing) apply or need adaptation to quantum contexts.
• Propose future research directions to enable repeatable, efficient, maintainable, and cost-effective quantum software.

Proposed method

• Review and synthesize recent QSE literature across multiple domains (SOC, MDE, testing, programming paradigms).
• Highlight major challenges and proposed solutions from active research groups.
• Identify interoperability, platform independence, and training needs as recurring themes.
• Discuss modeling languages, DSMLs, and QIR as mechanisms to raise abstraction in quantum software.
• Outline open research questions and potential decade-spanning roadmaps for QSE.

Figure 1. Papers on QSE over time

Experimental results

Research questions

• RQ1 What are the most active research areas in Quantum Software Engineering and why are they central to the field?
• RQ2 What challenges must be overcome to achieve repeatable, maintainable, and cost-effective quantum software?
• RQ3 How can classical software engineering practices (SOC, MDE, testing) be adapted or extended for quantum contexts?
• RQ4 What future directions and breakthroughs are needed to advance QSE over the next decade?

Key findings

• QSE has emerged as a distinct discipline with increasing publication activity since 2020, culminating in over 200 publications in 2023.
• Active areas include Service-Oriented Computing, Model-Driven Engineering, testing and debugging, and programming paradigms for quantum software.
• Significant challenges center on interoperability, platform independence, demand/capacity management, and workforce training.
• Future research directions emphasize high-level design methodologies for hybrid quantum-classical systems, scalable maintenance/evolution, intelligent code generation and orchestration, and improved testing techniques.