Like classic software, quantum software must be designed, specified, developed, and, most importantly, tested by developers. Writing tests is a complex, error-prone, and time-consuming task. Due to the particular properties of quantum physics (e.g., superposition), quantum software is inherently more complex to develop and effectively test than classical software. Nevertheless, we already know that some commonly used classical testing practices work for quantum computing to assess and improve the quality of quantum programs.

Several works have been proposed to ease the burden of testing quantum software, we are still in the early stages of testing in the quantum world. Researchers should focus on delivering usable artifacts without much hindrance to the rest of the community, and the development of quantum benchmarks should be a priority to facilitate reproducibility, replicability, and comparison between different testing techniques.

We have proposed mutation operators to assert the quality of quantum test suites and have realized something worth noting. Testing quantum programs is not yet a common practice, and this is due to many different reasons. With the added quantum complexity, the lack of tools and knowledge to design tests, the fact that quantum bug patterns and smells are still being identified, and the lack of real hardware to work on, developers tend to avoid testing. Our next research goal is to develop a method to automatically generate tests for quantum programs for developers to use and test their programs adequately. This is challenging since we must guide our test generation by criteria tailored to the quantum intricacies. The oracle problem is even more complex for quantum since results are non-deterministic.

We are, however, confident that the future holds great things for QP, and with the help of the community, this field will definitely continue to grow.

Prof. Rui Maranhão (publishes as Rui Abreu) holds a Ph.D. in Computer Science - Software Engineering from the Delft University of Technology, The Netherlands, and a M.Sc. in Computer and Systems Engineering from the University of Minho, Portugal. His research revolves around software quality, with emphasis in automating the testing and debugging phases of the software development life-cycle as well as self-adaptation. Dr. Abreu has extensive expertise in both static and dynamic analysis algorithms for improving software quality. He is the recipient of 6 Best Paper Awards, including a Distinguished Paper Award at ESEC/FSE 2019, and his work has attracted considerable attention. Before joining FEUP as a Full Professor, he was an Associate Professor at IST, ULisbon and a member of the Model-Based Reasoning group at PARC’s System and Sciences Laboratory and an Assistant Professor at the University of Porto. He has co-founded DashDash in January 2017, a platform to create web apps using only spreadsheet skills. The company has secured $9M in Series A funding in May 2018. He was a Visting Researcher at Google NYC between 2019 and 2020, working on building systems and tools to increase the security of C/C++ codebases.