Software Quality Evaluation Using McCabe Cyclomatic Complexity

Abstract

Software quality evaluation using McCabe cyclomatic complexity is important because control-flow complexity directly affects code understandability, testing effort, defect risk, and maintainability. Software modules with many decision points, nested conditions, loops, and branching paths become harder to test completely and more difficult to modify safely. Traditional quality evaluation based only on code size or defect counts may not clearly show the logical complexity inside a program. This article focuses on McCabe cyclomatic complexity as a structured metric for measuring independent execution paths in software modules. The study discusses how complexity values can be calculated from control-flow graphs and used to classify modules into low, moderate, high, and very high risk categories. The article concludes that cyclomatic complexity measurement can help identify risky modules, guide unit test design, support refactoring decisions, reduce defect leakage, and improve long-term software maintainability.