Testing Embedded Software for an IoT-Enabled Acoustic Imaging Camera

Abstract

This thesis enumerates the verification and validation of an embedded software application for an IoT-enabled acoustic imaging camera. The device is used to detect abnormal events, partial discharge, and air leaks of low-frequency sound. A testing framework was developed that combined manual and automated test script methodologies, and the methods were evaluated based on four known criteria, namely performance, scalability, reliability, and cost. The result indicated that automated testing improves the testing efficiency of embedded software applications, reduces time, and feedback time. Offering scalable testing practice for future IoT-based devices.

Keywords: Appium, Python Client, Test-Double, Testing, Automated Test Script, Manual Test Environment, Partial Discharge, and Air Leak.