Software Testing in the Quantum World

TL;DR

This work addresses the critical challenge of testing large-scale quantum software on real hardware where classical simulation is impractical. It advocates a shift from simulator-centric methods to end-to-end, statistically grounded QA within a hybrid quantum–classical workflow, leveraging abstraction, metamorphic and relation-based testing, and adaptive sampling. The paper discusses the potential for quantum computing to assist testing tasks (e.g., test-input search, optimization, fault localization) in near-term hybrid setups, while outlining benchmarks, tooling, and standardization needs. Collectively, these proposals aim to enable reliable, scalable quantum software that can achieve practical quantum advantage while maintaining dependability as hardware evolves.

Abstract

Quantum computing offers significant speedups for simulating physical, chemical, and biological systems, and for optimization and machine learning. As quantum software grows in complexity, the classical simulation of quantum computers, which has long been essential for quality assurance, becomes infeasible. This shift requires new quality-assurance methods that operate directly on real quantum computers. This paper presents the key challenges in testing large-scale quantum software and offers software engineering perspectives for addressing them.