Source Code Complexity Assessment with Static Metrics and Maintainability Index

Abstract

Source code complexity assessment helps software teams identify modules that are difficult to understand, test, modify, and maintain. This article presents a static metric-based framework for assessing source code complexity using cyclomatic complexity, Halstead measures, code size indicators, comment density, structural metrics, and Maintainability Index models. The framework classifies modules into maintainability risk groups by combining control-flow difficulty, lexical density, implementation size, documentation support, and index-based maintainability scores. The study shows that complexity is usually concentrated in specific module groups, especially calculation routines, transaction processing logic, and workflow control components. The proposed approach supports targeted refactoring by helping developers distinguish between generally acceptable modules and high-risk modules that require decomposition, branch simplification, documentation improvement, or additional testing.