It is well-known that Quantum Computing (QC) has the potential to solve complex problems in various domains and bring breakthroughs in science and technology. Nowadays, quantum applications span over algorithms addressing optimization problems such as radiotherapy optimization, machine learning techniques, e.g., for detecting objects from images, as well as modeling and simulations, e.g., for handling uncertainties when predicting the future. The development of QC is also driven by the urgent need to solve ever-complex and large-scale problems, which current (super)computers cannot solve. QC comes right on time to bring revolutionary computation power to handle such complexity. Testing such applications, however, is a big challenge due to their radically different characteristics from their classical counterparts. This includes superposition, entanglement, and probabilistic nature of qubits. The overall ambition is to develop fundamentally new methods for automated and systematic testing of quantum programs, based on a rigorous theoretical foundation with the ultimate goal of supporting future ubiquitous services and data related to QC applications to guarantee their dependability. Also, to allow for testing complex quantum programs with a minimal amount of QC resources, we will develop novel quantum optimization algorithms. The cost-effectiveness of our methods will be demonstrated by testing quantum programs written in quantum high-level programming languages (e.g., Q#).
Research Council of Norway
The University of Malaga, Spain
The University of Maryland, USA
Durham University, UK