Bug-Locating Method Based on Statistical Testing for Quantum Programs

When a bug is detected by testing a quantum program on a quantum computer, we want to determine its location to fix it. To locate the bug, the quantum program is divided into several segments, and each segment is tested. However, to prepare a quantum state that is input to a segment, it is necessary to execute all the segments ahead of that segment in a quantum computer. This means that the cost of testing each segment depends on its location. We can also locate a buggy segment only if it is confirmed that there are no bugs in all segments ahead of that buggy segment. Since a quantum program is tested statistically on the basis of measurement results, there is a tradeoff between testing accuracy and cost. These characteristics are unique to quantum programs and complicate locating bugs. We propose an efficient bug-locating method consisting of four approaches, i.e., cost-based binary search, early determination, finalization, and looking back, which take these characteristics into account. We present experimental results indicating that the proposed method can reduce bug-locating cost, represented as the number of executed quantum gates, compared with naive methods that do not use the four approaches. The limitations and usefulness of the proposed method are also discussed on the basis of the experimental results.

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Publication Details

Journal
IEEE Transactions on Software Engineering
Published
2025-08-08
DOI
https://doi.org/10.1109/tse.2025.3597316
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
Field-Weighted Citation Impact
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article

Bug-Locating Method Based on Statistical Testing for Quantum Programs

Ryota Katsube, Naoto Sato
IEEE Transactions on Software Engineering
Quantum Computing Algorithms and Architecture
article

Bug-Locating Method Based on Statistical Testing for Quantum Programs

Ryota Katsube, Naoto Sato
article en

Abstract

When a bug is detected by testing a quantum program on a quantum computer, we want to determine its location to fix it. To locate the bug, the quantum program is divided into several segments, and each segment is tested. However, to prepare a quantum state that is input to a segment, it is necessary to execute all the segments ahead of that segment in a quantum computer. This means that the cost of testing each segment depends on its location. We can also locate a buggy segment only if it is confirmed that there are no bugs in all segments ahead of that buggy segment. Since a quantum program is tested statistically on the basis of measurement results, there is a tradeoff between testing accuracy and cost. These characteristics are unique to quantum programs and complicate locating bugs. We propose an efficient bug-locating method consisting of four approaches, i.e., cost-based binary search, early determination, finalization, and looking back, which take these characteristics into account. We present experimental results indicating that the proposed method can reduce bug-locating cost, represented as the number of executed quantum gates, compared with naive methods that do not use the four approaches. The limitations and usefulness of the proposed method are also discussed on the basis of the experimental results.

IEEE Transactions on Software EngineeringVol. 51(10)
Hitachi (Japan) (JP)
Openalex Percentile: Top 90%
Quantum Computing Algorithms and Architecture
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