Determining software quality using code analysis metrics

This paper addresses the evaluation of software quality through the use of code analysis metrics. Software quality is critical to ensuring functionality, reliability, and maintainability, with complexity serving as a fundamental factor affecting these aspects. The study identifies common “code smells” structural issues within code that indicate potential weaknesses and categorizes them into dispensable elements, bloaters, coupling issues, and more. Object-oriented metrics such as Lines of Code (LOC), Cyclomatic Complexity (CC), and Number of Methods per Class (NOM) are explored for their roles in measuring and managing code complexity. Furthermore, the study proposes new metrics, including Relative Complexity Index (RCI) and Interaction Complexity (IC), designed to enhance the detection of code smells and improve maintainability. Implementation results using a Maven plugin for Spring Boot projects demonstrate the practicality of these metrics in generating detailed reports for software developers.