Internet of Things (IoT) systems are becoming ubiquitous and assuring their quality is of paramount importance, especially in safety-critical contexts. Unfortunately, few quality assurance proposals are present in the literature. In this paper, we propose an approach for semi-automated model-based generation of executable test cases, oriented to system-level acceptance testing of IoT systems. Our approach is supported by a prototype tool taking in input a UML model of the system under test and some additional artifacts, and produces in output a test suite that checks if the behavior of the system is compliant with such a model. The empirical evaluation of the approach executed on a mobile health IoT system for diabetic patients – involving sensors, actuators, a smartphone, and a remote cloud system – shows that the test suite generated with our tool has been able to kill between 87% and 98% of the mutants (i.e., artificial bugged versions of the system under test).
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