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

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.

💡 Research Summary

This paper presents an experience report on the design, delivery, and evaluation of a university‑level elective that frames quantum computing as a software‑engineering (SE) discipline. Recognizing that most existing quantum curricula focus on theory and algorithms while neglecting SE concerns such as testing, abstraction, tooling, and lifecycle management, the author created a cross‑listed undergraduate‑graduate course titled “Introduction to Quantum Software Engineering.” The course was offered in the Winter 2025 term to a mixed cohort of students with backgrounds in linear algebra, probability, computer organization, and introductory SE, but with no prior quantum experience.

The instructional design consists of twelve three‑hour lectures, each divided into three 50‑minute segments. The first half of the semester (Lectures 1‑5) introduces quantum information, circuit model, and canonical algorithms (Deutsch‑Jozsa, Grover, Shor) through executable code in open‑source frameworks (Qiskit, Pennylane, Cirq). By emphasizing “white‑box” code inspection and statistical result interpretation, students develop an operational intuition that later supports SE reasoning. The second half (Lectures 7‑10) shifts to quantum software‑engineering topics: test‑case design under nondeterminism, quality‑assurance strategies for noisy hardware, abstraction boundaries, service‑oriented quantum computing, and programming‑paradigm choices. Real‑world constraints—probabilistic outcomes, hardware noise, and backend variability—are repeatedly contrasted with classical SE assumptions, illustrating why traditional debugging and deterministic testing are insufficient.

Assessment is modular and tiered. Assignments (30 % of the grade) require students to implement, run, and analyze quantum programs, documenting tooling choices and empirical findings. Undergraduate students complete a final written exam (20 %); graduate students deliver a research‑paper presentation on a recent QSE study (20 %). A capstone project (45 %) is team‑based, involving deployment of a quantum application on both simulators and actual quantum hardware, followed by a comparative analysis of performance, noise impact, and maintainability. In‑class participation (5 %) captures engagement in discussions, quizzes, and peer reviews. This assessment model accommodates differing expertise levels while reinforcing the same learning outcomes.

Data collected from instructor observations, student surveys, and artifact analysis indicate that students initially struggled with abstract quantum concepts but quickly gained confidence once hands‑on labs and a flipped‑classroom approach (pre‑lecture videos plus automatic quizzes) were introduced. The course succeeded in fostering critical tool‑chain literacy; students could articulate trade‑offs between simulators, cloud‑based APIs, and device‑specific constraints. The project phase revealed that students could apply statistical testing methods (e.g., hypothesis testing on measurement distributions) to evaluate correctness, thereby internalizing a quantum‑specific quality‑assurance mindset.

The author acknowledges several threats to validity: the three‑hour lecture blocks may cause cognitive fatigue; heterogeneous prior knowledge creates uneven pacing; and rapid evolution of quantum software stacks can render teaching materials obsolete. Nevertheless, the modular lecture packets, publicly released slides, code repositories, and detailed activity guides (provided in the appendix) enable other institutions to replicate or adapt the course with minimal overhead.

Key insights distilled from the experience are: (1) embedding SE perspectives early in quantum education equips students to treat quantum programs as evolving software systems rather than isolated mathematical artifacts; (2) an “experiment‑repeat‑validate” cycle built around executable code and statistical analysis maximizes learning gains; (3) a mixed undergraduate‑graduate format efficiently utilizes teaching resources while delivering level‑appropriate outcomes; and (4) treating tooling variability and hardware noise as pedagogical variables prepares students for real‑world quantum development challenges.

The paper concludes by outlining future work: incorporating quantitative learning‑outcome metrics, expanding collaborations with industry partners to co‑design curriculum modules, and integrating emerging topics such as quantum error mitigation, compiler optimization, and formal verification into the SE‑focused framework. By sharing this modular design and assessment blueprint, the author aims to accelerate the emergence of a workforce capable of engineering reliable, maintainable quantum software.