Identifying Bug Patterns in Quantum Programs

Zhao, Pengzhan; Zhao, Jianjun; Ма, Лей

doi:10.48550/arxiv.2103.09069

Cited by 6 publications

(6 citation statements)

References 19 publications

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“…Finally, some other studies in the field of quantum software engineering have tackled a specific challenge, and proposed preliminary solutions. For instance, some have faced the challenge of artifact modeling [22,37,38,23], and others have discussed quality issues, ranging from the definition of specific metrics, to debugging [39,40,41].…”

Section: Related Workmentioning

confidence: 99%

Software Engineering for Quantum Programming: How Far Are We?

Stefano¹,

Pecorelli²,

Nucci³

et al. 2022

Preprint

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Quantum computing is no longer only a scientific interest but is rapidly becoming an industrially available technology that can potentially overcome the limits of classical computation. Over the last years, all major companies have provided frameworks and programming languages that allow developers to create their quantum applications. This shift has led to the definition of a new discipline called quantum software engineering, which is demanded to define novel methods for engineering large-scale quantum applications. While the research community is successfully embracing this call, we notice a lack of systematic investigations into the state of the practice of quantum programming. Understanding the challenges that quantum developers face is vital to precisely define the aims of quantum software engineering. Hence, in this paper, we first mine all the GitHub repositories that make use of the most used quantum programming frameworks currently on the market and then conduct coding analysis sessions to produce a taxonomy of the purposes for which quantum technologies are used. In the second place, we conduct a survey study that involves the contributors of the considered repositories, which aims to elicit the developers' opinions on the current adoption and challenges of quantum programming. On the one hand, the results highlight that the current adoption of quantum programming is still limited. On the other hand, there are many challenges that the software engineering community should carefully consider: these do not strictly pertain to technical concerns but also socio-technical matters.

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Section: Related Workmentioning

confidence: 99%

Software Engineering for Quantum Programming: How Far Are We?

Stefano¹,

Pecorelli²,

Nucci³

et al. 2022

Preprint

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“…Our implementation of MorphQ targets the Qiskit platform, which is highly popular and has been studied also by previous work [12,21,38,39], however we believe our approach could be easily extended to other quantum computing platforms. The generator supports a total of 45 gates, i.e., all but three gates expressible in Qiskit, excluded due to deprecation, presence of non-float parameters, or absence in the documentation.…”

Section: Program Generationmentioning

confidence: 99%

MorphQ: Metamorphic Testing of the Qiskit Quantum Computing Platform

Paltenghi¹,

Pradel²

2022

Preprint

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As quantum computing is becoming increasingly popular, the underlying quantum computing platforms are growing both in ability and complexity. This growth may cause bugs in the platforms, which hinders the adoption of quantum computing. Unfortunately, testing quantum computing platforms is challenging due to the relatively small number of existing quantum programs and because of the oracle problem, i.e., a lack of specifications of the expected behavior of programs. This paper presents MorphQ, the first metamorphic testing approach for quantum computing platforms. Our two key contributions are (i) a program generator that creates a large and diverse set of valid (i.e., non-crashing) quantum programs, and (ii) set of program transformations that exploit quantum-specific metamorphic relationships to alleviate the oracle problem. Evaluating the approach by testing the popular Qiskit platform shows that the approach creates over 50k program pairs within two days, many of which expose crashes. Inspecting the crashes, we find twelve bugs, eight of which have already been confirmed. MorphQ widens the slim portfolio of testing techniques of quantum computing platforms, helping to create a reliable software stack for this increasingly important field.

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“…Weder et al [23] introduced a ten-phases software life cycle for gate-based quantum software. Zhao et al [24] identified the bug patterns in Qiskit and discussed how bug patterns could be eliminated. Zhao [25] proposed metrics for measuring the size and structure of quantum software.…”

Section: Prior Workmentioning

confidence: 99%

Development of a Tool for Finding Equivalent Mutants in Quantum Program: A Perspective to Measure the Quality of Quantum Software

Kumar

Kwatra

Garhwal

2022

Preprint

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Software testing is an important activity to ensure the software's quality. Mutation testing is a fault-based technique for checking the effectiveness of test cases for the verification and validation of software. Testing quantum programs is challenging due to the involvement of quantum mechanics concepts (such as superposition and entanglement ) and the probabilistic nature of the outcome. In this paper, We will propose the modified mutation testing approach for quantum program. The proposed approach will help to reduce the cost, time, and effort of performing the mutation testing. Moreover, we also propose a method for determining the equivalent mutant and developing a tool to check whether the mutated and original quantum program behave semantically equivalent or differently.

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Identifying Bug Patterns in Quantum Programs

Cited by 6 publications

References 19 publications

Software Engineering for Quantum Programming: How Far Are We?

Software Engineering for Quantum Programming: How Far Are We?

MorphQ: Metamorphic Testing of the Qiskit Quantum Computing Platform

Development of a Tool for Finding Equivalent Mutants in Quantum Program: A Perspective to Measure the Quality of Quantum Software

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