A quantum computer (QC) can solve many computational problems more efficiently than a classic one. The field of QCs is growing: companies (such as D-Wave, IBM, Google, and Microsoft) are building QC offerings. We position that software engineers should look into defining a set of software engineering practices that apply to QC's software. To start this process, we give examples of challenges associated with testing such software and sketch potential solutions to some of these challenges.
A quantum computer (QC) can solve many computational problems more efficiently than a classic one. The field of QCs is growing: companies (such as D-Wave, IBM, Google, and Microsoft) are building QC offerings. We position that software engineers should look into defining a set of software engineering practices that apply to QC's software. To start this process, we give examples of challenges associated with testing such software and sketch potential solutions to some of these challenges.
Quantum computing is getting increasing interest from both academia and industry, and the quantum software landscape has been growing rapidly. The quantum software stack comprises quantum programs, implementing algorithms, and platforms like IBM Qiskit, Google Cirq, and Microsoft Q#, enabling their development. To ensure the reliability and performance of quantum software, various techniques for testing and analyzing it have been proposed, such as test generation, bug pattern detection, and circuit optimization. However, the large amount of work and the fact that work on quantum software is performed by several research communities, make it difficult to get a comprehensive overview of the existing techniques. In this work, we provide an extensive survey of the state of the art in testing and analysis of quantum software. We discuss literature from several research communities, including quantum computing, software engineering, programming languages, and formal methods. Our survey covers a wide range of topics, including expected and unexpected behavior of quantum programs, testing techniques, program analysis approaches, optimizations, and benchmarks for testing and analyzing quantum software. We create novel connections between the discussed topics and present them in an accessible way. Finally, we discuss key challenges and open problems to inspire future research.
Quantum computing is a fundamentally different way of performing computation than classical computing. Many problems that are considered hard for classical computers may have efficient solutions using quantum computers. Recently, technology companies including IBM, Microsoft, and Google have invested in developing both quantum computing hardware and software to explore the potential of quantum computing. Because of the radical shift in computing paradigms that quantum represents, we see an opportunity to study the unique needs people have when interacting with quantum systems, what we call Quantum HCI (QHCI). Based on interviews with experts in quantum computing, we identify four areas in which HCI researchers can contribute to the field of quantum computing. These areas include understanding current and future quantum users, tools for programming and debugging quantum algorithms, visualizations of quantum states, and educational materials to train the first generation of "quantum native" programmers.
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.
Quantum software testing concentrates on testing quantum programs to discover quantum faults in the programs cost-effectively. Given the foundations in quantum mechanics, the way quantum computations are performed is significantly different than classical computing. Therefore, quantum software testing also differs from classical software testing. There has been quite an interest in building quantum software testing techniques since 2019 in the software engineering (SE) community. Thus, we aim to introduce quantum software testing to the SE community. In particular, we will present the basic foundations of quantum computing and quantum programming as circuits, followed by the current state of the art on quantum software testing. Next, we will present some basic quantum software testing techniques and finally give the research directions that deserve attention from the SE community.
Despite the increasing interest in quantum computing, the aspect of development to achieve cost-effective and reliable quantum software applications has been slow. One barrier is the software engineering of quantum programs, which can be approached from two directions. On the one hand, many software engineering practices, debugging in particular, are bound to classical computing. On the other hand, quantum programming is closely associated with the phenomena of quantum physics, and consequently, the way we express programs resembles the early days of programming. Moreover, much of the software engineering research today focuses on agile development, where computing cycles are cheap and new software can be rapidly deployed and tested, whereas in the quantum context, executions may consume lots of energy, and test runs may require lots of work to interpret. In this paper, we aim at bridging this gap by starting with the quantum computing workflow and by mapping existing software engineering research to this workflow. Based on the mapping, we then identify directions for software engineering research for quantum computing.