A comparison of code quality metrics and best practices in non-IoT and IoT systems

IoT systems are a network of connected devices powered by software, requiring the study of software quality for maintenance. Despite extensive studies on non-IoT systems’ software quality, research on IoT systems’ software quality is lacking. It is uncertain whether non-IoT and IoT systems’ software are comparable, limiting the application of results and best practices from non-IoT to IoT systems. Therefore, we compare the code quality of two equivalent sets of non-IoT and IoT systems to determine whether there are similarities and differences between the two kinds of software systems. We design and apply a systematic method to select two sets of 94 non-IoT and IoT system software from GitHub with comparable characteristics. We compute quality metrics on the systems in these two sets and then analyse and compare the metric values. We conduct an in-depth analysis and provide specific examples of the IoT systems’ complexity and how it manifests in their source code. We conclude that software for IoT systems is more complex, coupled, larger, less maintainable, and cohesive than non-IoT systems. Several factors, such as integrating multiple hardware and software components and managing data communication between them, contribute to these differences. After the comparison, we systematically select and present a list of best practices to address the observed differences between non-IoT and IoT code. We present a list of revisited best practices with approaches, tools, or techniques for developing IoT systems. For example, applying modularity and refactoring are best practices for lowering complexity. Based on our work, researchers can now make informed decisions using existing studies on the quality of non-IoT systems for IoT systems. Developers can use the list of best practices to minimise disparities in complexity, size, and cohesion and enhance maintainability and code readability.