# Quantum Software Engineering: Roadmap and Challenges Ahead

arXiv: https://arxiv.org/abs/2404.06825 · HTML: https://mlsanity.com/paper/2404.06825/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 Apr 2024.

## Built on by (most cited first, 6 of 6)

- [Exploring LLM-Driven Explanations for Quantum Algorithms](https://mlsanity.com/paper/2409.19028/) (2024)
- [Taxonomy of migration scenarios for Qiskit refactoring using LLMs](https://mlsanity.com/paper/2506.07135/) (2025)
- [QSpark: Towards Reliable Qiskit Code Generation](https://mlsanity.com/paper/2507.12642/) (2025)
- [Search-Based Software Engineering and AI Foundation Models: Current Landscape and Future Roadmap](https://mlsanity.com/paper/2505.19625/) (2025)
- [Formal Verification of Noisy Quantum Reinforcement Learning Policies](https://mlsanity.com/paper/2512.01502/) (2025)
- [Leveraging LLM-Based Agentic Systems to Generate Quantum Applications for Test Optimization](https://mlsanity.com/paper/2607.00939/) (2026)

## Abstract (arXiv)

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.