System Complexity Metrics

System complexity metrics are quantitative measures used to assess how intricate and difficult a codebase is to understand, test, and maintain. High complexity often correlates with a higher probability of bugs and security vulnerabilities.

Metrics such as cyclomatic complexity, which counts the number of linearly independent paths through a program's source code, help developers identify overly complex functions that should be simplified. In the context of financial derivatives, where logic is often highly sophisticated, monitoring these metrics is essential for ensuring that the code remains manageable and auditable.

By keeping complexity within acceptable limits, teams can ensure that their protocols are more resilient to errors and easier to secure over the long term.