QMutBench: A Dataset of Quantum Circuit Mutants
Eñaut Mendiluze Usandizaga, Thomas Laurent, Paolo Arcaini, Shaukat Ali
TLDR
QMutBench is a new dataset of over 700,000 quantum circuit mutants, addressing the lack of faulty program benchmarks for quantum software testing.
Key contributions
- Introduces QMutBench, a dataset of over 700,000 quantum circuit mutants for testing.
- Addresses the critical lack of faulty program benchmarks in quantum software testing.
- Provides an online interface with selection criteria for specific mutant characteristics.
- Enables assessment of quantum test case quality and comparison of testing techniques.
Why it matters
Quantum software testing requires robust benchmarks of faulty programs to evaluate test case effectiveness. QMutBench fills this gap, providing a crucial resource for developers and testers. It will accelerate the development and comparison of quantum testing techniques.
Original Abstract
Quantum software testing has attracted interest in recent years, prompting the development of various techniques to automate the testing of quantum software. These techniques generate test cases that must be assessed for their effectiveness in detecting faults. Such an assessment requires benchmarks of faulty programs. However, there is a lack of benchmarks containing faults. In this data showcase, we propose QMutBench, a dataset that contains over 700,000 quantum circuit mutants representing different faults. The dataset is accessible via an online interface with selection criteria, such as the original quantum circuit(s) from which mutants are generated, the desired survival rate of the selected mutants, and other mutation characteristics (e.g., the type of faulty quantum gate). QMutBench provides quantum software developers and testers with an accessible online dataset to obtain benchmarks of mutants necessary to assess either the quality of the test cases generated by their testing technique or to compare different testing techniques. It also enables the development of new mutation-guided quantum software testing techniques.
📬 Weekly AI Paper Digest
Get the top 10 AI/ML arXiv papers from the week — summarized, scored, and delivered to your inbox every Monday.