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ACM/IEEE International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)

Mutation testing of quantum programs written in QISKit

Daniel Fortunato, José Campos, Rui Abreu

Published May 21, 2022• 28 citations
Publisher

Abstract

There is an inherent lack of knowledge and technology to test a quantum program properly. In this paper, building on the definition of syntactically equivalent quantum operations, we investigated a novel set of mutation operators to generate mutants based on qubit measurements and quantum gates. To ease the adoption of quantum mutation testing, we further discuss QMutPy, an extension of the well-known and fully automated open-source mutation tool MutPy. To evaluate QMutPy's performance we conducted a case study on 11 real quantum programs written in the IBM's QISKit library. QMutPy has proven to be an effective quantum mutation tool, providing insight on the current state of quantum tests.

DOI
10.1145/3510454.3528649

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Mutation Testing of Quantum Programs Written in QISKit

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There is an inherent lack of knowledge and technology to test a quantum program properly. In this paper, building on the definition of syntactically equivalent quantum operations, we investigated a novel set of mutation operators to generate mutants based on qubit measurements and quantum gates. To ease the adoption of quantum mutation testing, we further discuss QMutPy, an extension of the well-known and fully automated open-source mutation tool MutPy. To evaluate QMutPy’s performance we conducted a case study on 11 real quantum programs written in the IBM’s QISKit library. QMutPy has proven to be an effective quantum mutation tool, providing insight on the current state of quantum tests.

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•Dec 9, 2022•2 citations
There is an inherent lack of knowledge and technology to test a quantum program properly. In this paper, building on the definition of syntactically equivalent quantum operations, we investigated a novel set of mutation operators to generate mutants based on qubit measurements and quantum gates. To ease the adoption of quantum mutation testing, we further discuss QMutPy, an extension of the well-known and fully automated open-source mutation tool MutPy. To evaluate QMutPy's performance we conducted a case study on 11 real quantum programs written in the IBM's QISKit library. QMutPy has proven to be an effective quantum mutation tool, providing insight on the current state of quantum tests.
There is an inherent lack of knowledge and technology to test a quantum program properly. In this paper, building on the definition of syntactically equivalent quantum operations, we investigated a novel set of mutation operators to generate mutants based on qubit measurements and quantum gates. To ease the adoption of quantum mutation testing, we further discuss QMutPy, an extension of the well-known and fully automated open-source mutation tool MutPy. To evaluate QMutPy’s performance we conducted a case study on 11 real quantum programs written in the IBM’s QISKit library. QMutPy has proven to be an effective quantum mutation tool, providing insight on the current state of quantum tests.
As quantum computing is still in its infancy, there is an inherent lack of knowledge and technology to test a quantum program properly. In the classical realm, mutation testing has been successfully used to evaluate how well a program's test suite detects seeded faults (i.e., mutants). In this paper, building on the definition of syntactically equivalent quantum operations, we propose a novel set of mutation operators to generate mutants based on qubit measurements and quantum gates. To ease the adoption of quantum mutation testing, we further propose QMUTPY, an extension of the well-known and fully automated open-source mutation tool MUTPY. To evaluate QMUTPY's performance, we conducted a case study on 24 real quantum programs written in IBM's QISKIT library. Furthermore, we show how better test suite coverage and improvements to test assertions can increase the test suites' mutation score and quality. QMUTPY has proven to be an effective quantum mutation tool, providing insight into the current state of quantum tests and how to improve them.
There is an inherent lack of knowledge and technology to test a quantum program properly. In this paper, building on the definition of syntactically equivalent quantum gates, we describe our efforts in developing a tool, coined QMutPy, leveraging the well-known open-source mutation tool MutPy. We further discuss the design and implementation of QMutPy, and the usage of a novel set of mutation operators that generate mutants for qubit measurements and gates. To evaluate QMutPy’s performance, we conducted a preliminary study on 11 real quantum programs written in the IBM’s Qiskit library. QMutPy has proven to be an effective quantum mutation tool, providing insight into the current state of quantum tests. QMutPy is publicly available at https://github.com/danielfobooss/mutpy. Tool demo: https://youtu.be/fC4tOY5trqc.
Given that quantum software testing is a new area of research, there is a lack of benchmark programs and bugs repositories to assess the effectiveness of testing techniques. To this end, quantum mutation analysis focuses on systematically generating faulty versions of Quantum Programs (QPs), called mutants, using mutation operators. Such mutants can be used as benchmarks to assess the quality of test cases in a test suite. Thus, we present Muskit - a quantum mutation analysis tool for QPs coded in IBM's Qiskit language. Muskit defines mutation operators on gates of QPs and selection criteria to reduce the number of mutants to generate. Moreover, it allows for the execution of test cases on mutants and generation of results for test analyses. Muskit is provided as command line interface, GUI, and web application. We validated Muskit by using it to generate and execute mutants for four QPs. Muskit code: https://github.com/Simula-COMPLEX/muskitWeb app: https://qiskitmutantcreatorsrl.pythonanywhere.com/YouTube Video: EbPHJOK_AEA Artifact Available: https://doi.org/10.5281/zenodo.5288917
Quantum mutation analysis is emerging as an essential technique for evaluating test suites due to the limited availability of real faulty quantum programs. However, existing quantum mutation analysis tools use fixed gate-based mutations, resulting in easy-to-detect mutants, which reduces their effectiveness in assessing the quality of test suites. We propose QUMUG, a search-based approach for generating challenging mutants by utilising parameterisable quantum gates. QUMUG employs search algorithms to optimise mutation parameters and find non-equivalent mutants passing a given test suite. In our evaluation over 30 quantum programs, QUMUG produced mutants that are three times more challenging than the mutants generated by existing tools. Among the four evaluated search algorithms, the genetic algorithm was the most effective, generating an average of 494 undetected mutants per program with a 99.67% success rate and 94.3% non-equivalent ratio. The generated mutants demonstrated their effectiveness by requiring the addition of five times more test cases to the test suite than the mutants generated by existing tools. We also analysed the behaviour of higher order mutants in quantum circuits, and showed that while first order mutations are more effective for enhancing the test suite, higher order mutants highlight the need for new unique test cases.
Abstract 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.