Utilizing the output of Azure IoT hub to comprehend the software functionalities

It is essential to understand the software functionalities in the physical devices in the Internet of Things (IoT) before implementing any update or maintenance. It is usually implemented by monitoring the IoT data. The monitoring at runtime illustrates the behavior of connected devices and their functionalities at a high-level concept. However, locating the software functionalities on the running machines in the IoT environment is challenging and time-consuming due to the large data volume and live monitoring complexity. Current work aims to monitor the connectivity of the devices in the IoT. It remains the critical limitation towards allocating the devices' existing software functionalities and mapping them to the possible related source of code. This paper proposes a novel approach to utilize the output of monitoring devices in the IoT environment and use the collected data to locate the current software functionalities running on the IoT system. The collected data are processed and filtered to minimize the size of the noise in the collected data. The developers use the filtered data to locate the software functionality based on the invoked source code. The performance is evaluated using one case study that generates one monitoring file (execution trace). The collected execution trace indicates the source code for the running software functionality. The proposed methodology achieves up to 51% in the F-measure score, and the results show the possibility of increasing the accuracy when the monitoring solution is optimized.