Abstract
Assuring the quality of Internet of Things (IoT) systems is of paramount importance, and guaranteeing their reliability and compliance with the requirements is mandatory, but few attempts have been made so far. In previous works, we proposed two approaches for acceptance testing and runtime verification of IoT systems. Both works rely on a UML state machine to specify the system expected behaviour. In the acceptance testing approach, the interesting paths to exercise are identified and translated into executable test scripts. In the runtime verification approach, the relevant events during the system execution are monitored and compared against a formal specification derived from the UML state machine. In this paper, we compare the effectiveness of our two approaches, by applying them to a mobile health IoT system for the management of diabetic patients, employing over 100 mutated versions of the original system and analysing more than 1000 different executions. Results show that both approaches are effective in different ways in detecting bugs. While the acceptance testing approach is more effective to detect the bugs affecting the user interface, the runtime verification approach tracks better the subtle deviations from the system expected behaviour, in particular those concerning network issues.
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