A Metrics Suite for Measuring Indirect Coupling Complexity

Abstract

Software development can be a time-consuming and costly process that requires a significant amount of effort. Developers are often tasked with completing programming tasks or making modifications to existing code without increasing overall complexity. It is essential for them to understand the dependencies between the program components before implementing any changes. However, as code evolves, it becomes increasingly challenging for project managers to detect indirect coupling links between components. These hidden links can complicate the system, cause inaccurate effort estimates, and compromise the quality of the code. To address these challenges, this study aims to provide a set of measures that leverage measurement theory and hidden links between software components to expand the scope, effectiveness, and utility of accepted software metrics. The research focuses on two primary topics: (1) how indirect coupling measurements can aid developers with maintenance tasks and (2) how indirect coupling metrics can quantify software complexity and size, leveraging weighted differences across techniques. The study presents a comprehensive set of measures designed to assist developers and project managers with project management and maintenance activities. Using the power of indirect coupling measurements, these measures can enhance the quality and efficiency of software development and maintenance processes.