Date of Award

2022

Document Type

Dissertation

Degree Name

Ph.D.

Organizational Unit

Daniel Felix Ritchie School of Engineering and Computer Science, Computer Science

First Advisor

Anneliese Amschler Andrews

Second Advisor

Chip Reichardt

Third Advisor

Scott Leutenegger

Fourth Advisor

Chris GauthierDickey

Keywords

Smart home systems, Applications, Software

Abstract

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 [71]. According to MediaPost [74], 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) [68] and FSMApp [10] 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 [10] 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.

Publication Statement

Copyright is held by the author. User is responsible for all copyright compliance.

Rights Holder

Afnan Mohammed Albahli

Provenance

Received from ProQuest

File Format

application/pdf

Language

en

File Size

179 pgs

Discipline

Computer science

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