Automatic Diagnosis of Quantum Software Bug-Fix Motifs

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paper196.pdf (265.87 KB)

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https://ksiresearchorg.ipage.com/seke/seke23paper/paper196.pdf

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http://dx.doi.org/10.18293/SEKE2023-196
 http://hdl.handle.net/11603/31732

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UMBC Information Systems Department
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https://orcid.org/0000-0001-9343-3654

Date

2023

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conference papers and proceedings
preprints
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Abstract

Bug-fix pattern detection has been investigated in the past in the context of classical software. However, while quantum software is developing rapidly, the literature is still lacking automated methods and tools to identify, analyze, and detect bug-fix patterns. To the best of our knowledge, our work is the first to leverage classical techniques to detect bug-fix patterns in quantum code. In this paper, we propose an automated framework, called Q-Diff, for detecting bug-fix patterns in IBM Qiskit quantum code. In the framework, we develop a proof-of-concept tool based on Abstract Syntax Trees. To validate our method, we test Q-Diff with a variety of quantum bug-fix patterns using examples. We hope our work will attract the attention of the quantum software engineering community to improve the quality of quantum software.