Date of Award
Anneliese Amschler Andrews
Smart home systems, Applications, Software
Smart Home Systems (SHS) are some of the most popular Internet of Things (IoT) applications. In 2021, there were 52.22 million smart homes in the United States and they are expected to grow to 77.1 million in 2025 . According to MediaPost , 69 percent of American households have at least one smart home device. The number of smart home systems poses a challenge for software testers to find the right approach to test these systems. This dissertation employs Extended Finite State Machines (EFSMs) [6, 24, 105], Communicating Extended Finite State Machines (EFSMs)  and FSMApp  to generate reusable test-ready models of smart home systems. We present an approach to create reusable test-ready models of smart home systems using EFSMs to model device components (Sensor, Controller and Actuator), EFSMs to model single devices in the SHS and the interaction between the devices. We adopted Al Haddad’s  FSMApp approach to model and test the mobile application that controls the SHS. These reusable test-ready models were used to generate tests. This dissertation also addresses evolution in smart home systems. Evolution is classified into three categories: adding a new device, updating an excising device or removing one. A method for selective black-box model-based regression testing for these changes was proposed.
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Albahli, Afnan Mohammed, "Model-Based Testing of Smart Home Systems Using EFSM, CEFSM, and FSMApp" (2022). Electronic Theses and Dissertations. 2094.
Received from ProQuest
Afnan Mohammed Albahli