ABSTRACT The recent growth in popularity of wearable medical devices has improved the quality of life of people with medical conditions. Testing such devices may require users to configure these systems using physical trials, putting themselves in potentially dangerous scenarios. Misconfiguration of such devices has caused disease misdiagnoses and incorrect drug prescriptions. Digital twins have been proposed as an opportunity to reduce such risks of testing system configurations in simulated environments, decoupling the user from the system under test. In this paper, we perform an evaluative case study to assess the use of a digital twin for configuration testing of an artificial pancreas system (APS) control algorithm. These systems regulate the blood glucose levels in people with type 1 diabetes mellitus, and so misconfigurations can cause severe hypoglycaemia or hyperglycaemia, which can be life‐threatening. We tested the OpenAPS control algorithm against 156 people's clinical data. We found that our digital twin provided an accurate simulation environment to perform configuration testing and accurately predict blood glucose–insulin behaviour. We evaluated different APS configurations, identifying a potentially unsafe configuration without the risks associated with a physical trial. We identified the challenges associated with modelling clinical data, which could lead to misinterpretations in configuration testing and the reduction of test reliability when modelling stochastic body dynamics.

Cyber–physical systems present a challenge to testers, bringing complexity and scale to safety-critical and collaborative environments. Digital twins enhance these systems through data-driven and simulation based models coupled to physical systems to provide visualisation, predict future states and communication. Due to the coupling between digital and physical worlds, digital twins provide a new perspective into cyber–physical system testing. The objectives of this study are to summarise the existing literature on digital-twin-based testing. We aim to uncover emerging areas of adoptions, the testing techniques used in these areas and identify future research areas. We conducted a systematic literature review which answered the following research questions: What cyber–physical systems are digital twins currently being used to test? How are test oracles defined for cyber–physical systems? What is the distribution of white-box, black-box and grey-box modelling techniques used for digital twins in the context of testing? How are test cases defined and how does this affect test inputs? We uncovered 26 relevant studies from 480 produced by searching with a curated search query. These studies showed an adoption of digital-twin-based testing following the introduction of digital twins in industry as well as the increasing accessibility of the technology. The oracles used in testing are the digital twin themselves and therefore rely on both system specification and data derivation. Cyber–physical systems are tested through passive testing techniques, as opposed to either active testing through test cases or predictive testing using digital twin prediction. This review uncovers the existing areas in which digital twins are used to test cyber–physical systems as well as outlining future research areas in the field. We outline how the infancy of digital twins has affected their wide variety of definitions, emerging specialised testing and modelling techniques as well as the current lack of predictive ability.