A Course on the Introduction to Quantum Software Engineering: Experience Report

2026-02-07

AI Summary

This work addresses a critical gap in current quantum computing education, which predominantly emphasizes algorithms and framework usage while neglecting core software engineering challenges such as testing, abstraction, toolchain integration, and lifecycle management. To bridge this gap, the authors designed and implemented an interdisciplinary course for undergraduate and graduate students that approaches quantum computing from a software engineering perspective, integrating foundational quantum information concepts, algorithm implementation, and hands-on engineering practice. The curriculum emphasizes executable artifacts, empirical reasoning, and engineering trade-offs in noisy environments. Structured modularly and supported by a scalable assessment model, the course effectively accommodates students with diverse academic backgrounds. Empirical results demonstrate that even learners without prior quantum computing experience can grasp key concepts and engage meaningfully in engineering tasks, thereby validating the feasibility and transferability of this pedagogical approach.

Technology Category

• Machine Learning: Quantum Machine Learning
• Application Domains: Software Engineering
• Knowledge Representation and Reasoning: Qualitative Reasoning

Application Category

• Graph Algorithms and Modeling for the Web: Algorithms and analysis for incomplete, noisy, or partially observed Web-related graphs
• Economics, Online Markets and Human Computation: Economic aspects and information design of Web, GenAI, and cloud computing
• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments

Abstract

Quantum computing is increasingly practiced through programming, yet most educational offerings emphasize algorithmic or framework-level use rather than software engineering concerns such as testing, abstraction, tooling, and lifecycle management. This paper reports on the design and first offering of a cross-listed undergraduate--graduate course that frames quantum computing through a software engineering lens, focusing on early-stage competence relevant to software engineering practice. The course integrates foundational quantum concepts with software engineering perspectives, emphasizing executable artifacts, empirical reasoning, and trade-offs arising from probabilistic behaviour, noise, and evolving toolchains. Evidence is drawn from instructor observations, student feedback, surveys, and analysis of student work. Despite minimal prior exposure to quantum computing, students were able to engage productively with quantum software engineering topics once a foundational understanding of quantum information and quantum algorithms, expressed through executable artifacts, was established. This experience report contributes a modular course design, a scalable assessment model for mixed academic levels, and transferable lessons for software engineering educators developing quantum computing curricula.

Problem

• quantum computing
• software engineering education
• quantum software engineering
• curriculum design
• executable artifacts

Innovation

• quantum software engineering
• software engineering education
• executable artifacts
• modular course design
• scalable assessment