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Unveiling Code Clones in Quantum Programming: An Empirical Study with Qiskit

Kenta Manoku, Jianjun Zhao

TL;DR

This study addresses the lack of understanding of code clones in quantum programming by empirically analyzing Qiskit-based software. It combines AST-based extraction of functions/classes with a SequenceMatcher-based similarity metric, defined as $Similarity = \frac{2 \times \text{Matching Characters}}{\text{Length of String 1} + \text{Length of String 2}}$, to detect Type-1 through Type-3 clones. The key finding is a notable density of Type-2 and Type-3 clones, with Type-1 clones also present, indicating maintenance challenges in quantum software. These results motivate the development of quantum-specific clone-detection and refactoring tools to improve maintainability and scalability of quantum applications.

Abstract

Code clones, referring to identical or similar code fragments, have long posed challenges in classical programming, impacting software quality, maintainability, and scalability. However, their presence and characteristics in quantum programming remain unexplored. This paper presents an empirical study of code clones in quantum programs, specifically focusing on software developed using the Qiskit framework. We examine the existence, distribution, density, and size of code clones in quantum software, revealing a high density of Type-2 and Type-3 clones involving minor modifications. Our findings suggest that these clones are more frequent in quantum software, likely due to the complexity of quantum algorithms and their integration with classical logic. This highlights the need for advanced clone detection and refactoring tools specifically designed for the quantum domain to improve software maintainability and scalability.

Unveiling Code Clones in Quantum Programming: An Empirical Study with Qiskit

TL;DR

This study addresses the lack of understanding of code clones in quantum programming by empirically analyzing Qiskit-based software. It combines AST-based extraction of functions/classes with a SequenceMatcher-based similarity metric, defined as , to detect Type-1 through Type-3 clones. The key finding is a notable density of Type-2 and Type-3 clones, with Type-1 clones also present, indicating maintenance challenges in quantum software. These results motivate the development of quantum-specific clone-detection and refactoring tools to improve maintainability and scalability of quantum applications.

Abstract

Code clones, referring to identical or similar code fragments, have long posed challenges in classical programming, impacting software quality, maintainability, and scalability. However, their presence and characteristics in quantum programming remain unexplored. This paper presents an empirical study of code clones in quantum programs, specifically focusing on software developed using the Qiskit framework. We examine the existence, distribution, density, and size of code clones in quantum software, revealing a high density of Type-2 and Type-3 clones involving minor modifications. Our findings suggest that these clones are more frequent in quantum software, likely due to the complexity of quantum algorithms and their integration with classical logic. This highlights the need for advanced clone detection and refactoring tools specifically designed for the quantum domain to improve software maintainability and scalability.
Paper Structure (18 sections, 4 figures, 2 tables)

This paper contains 18 sections, 4 figures, 2 tables.

Table of Contents

  1. Introduction
  2. Methodology
  3. Repository Selection Criteria
  4. Qiskit Project Collection
  5. Selection of Target Programs
  6. Code Clone Detection
  7. Experimental Results
  8. Experimental Setting
  9. Existence of Code Clones
  10. Distribution and Density of Code Clones
  11. Type-1 Code Clones
  12. Type-2 and Type-3 Code Clones
  13. Size of Code Clones
  14. Discussion
  15. Implications for Maintenance
  16. ...and 3 more sections

Figures (4)

  • Figure 1: An example of a Type-1 code clone is shown. The code on the left is from https://github.com/tiagomsleao/ShorAlgQiskit/blob/master/Shor_Normal_QFT.py, while the code on the right is from https://github.com/tiagomsleao/ShorAlgQiskit/blob/master/Shor_Sequential_QFT.py.
  • Figure 2: Repository size and percentage of files containing code clones
  • Figure 3: An example of a Type-3 code clone is shown. The code on the left is from https://github.com/vm6502q/qiskit-qrack-provider/blob/master/test/terra/reference/ref_non_clifford.py, while the code on the right is from https://github.com/vm6502q/qiskit-qrack-provider/blob/master/test/terra/reference/ref_1q_clifford.py.
  • Figure 4: Repository size and size of code clones