Is Measurement Enough? Rethinking Output Validation in Quantum Program Testing

Fuente: arXiv
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Main Authors: Ye, Jiaming, Wu, Xiongfei, Xia, Shangzhou, Zhang, Fuyuan, Zhao, Jianjun
Format: Preprint
Published: 2025
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author Ye, Jiaming
Wu, Xiongfei
Xia, Shangzhou
Zhang, Fuyuan
Zhao, Jianjun
author_facet Ye, Jiaming
Wu, Xiongfei
Xia, Shangzhou
Zhang, Fuyuan
Zhao, Jianjun
contents As quantum computing continues to emerge, ensuring the quality of quantum programs has become increasingly critical. Quantum program testing has emerged as a prominent research area within the scope of quantum software engineering. While numerous approaches have been proposed to address quantum program quality assurance, our analysis reveals that most existing methods rely on measurement-based validation in practice. However, due to the inherently probabilistic nature of quantum programs, measurement-based validation methods face significant limitations. To investigate these limitations, we conducted an empirical study of recent research on quantum program testing, analyzing measurement-based validation methods in the literature. Our analysis categorizes existing measurement-based validation methods into two groups: distribution-level validation and output-value-level validation. We then compare measurement-based validation with statevector-based validation methods to evaluate their pros and cons. Our findings demonstrate that measurement-based validation is suitable for straightforward assessments, such as verifying the existence of specific output values, while statevector-based validation proves more effective for complicated tasks such as assessing the program behaviors.
format Preprint
id arxiv_https___arxiv_org_abs_2509_16595
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Is Measurement Enough? Rethinking Output Validation in Quantum Program Testing
Ye, Jiaming
Wu, Xiongfei
Xia, Shangzhou
Zhang, Fuyuan
Zhao, Jianjun
Software Engineering
As quantum computing continues to emerge, ensuring the quality of quantum programs has become increasingly critical. Quantum program testing has emerged as a prominent research area within the scope of quantum software engineering. While numerous approaches have been proposed to address quantum program quality assurance, our analysis reveals that most existing methods rely on measurement-based validation in practice. However, due to the inherently probabilistic nature of quantum programs, measurement-based validation methods face significant limitations. To investigate these limitations, we conducted an empirical study of recent research on quantum program testing, analyzing measurement-based validation methods in the literature. Our analysis categorizes existing measurement-based validation methods into two groups: distribution-level validation and output-value-level validation. We then compare measurement-based validation with statevector-based validation methods to evaluate their pros and cons. Our findings demonstrate that measurement-based validation is suitable for straightforward assessments, such as verifying the existence of specific output values, while statevector-based validation proves more effective for complicated tasks such as assessing the program behaviors.
title Is Measurement Enough? Rethinking Output Validation in Quantum Program Testing
topic Software Engineering
url https://arxiv.org/abs/2509.16595