Code complexity refers to how difficult a piece of code is to understand, modify, and test. It’s not just about the number of lines written, but about the structure of the logic—nested conditions, branching paths, dependencies, and how tightly components are coupled. As software grows, unmanaged complexity can quietly become one of the biggest risks to long-term quality.

Highly complex code is harder to reason about, which increases the chances of introducing defects during changes. Even small updates can have unintended side effects because it’s not always clear how different parts of the code interact. This directly impacts testing efforts, as more complex code usually requires more test cases to cover all possible paths and edge cases.

From a testing perspective, code complexity often shows up as poor testability. Functions with too many responsibilities, deep nesting, or heavy dependencies are difficult to isolate and validate. This leads to slower test creation, brittle tests, and reduced confidence in test results. Over time, teams may rely more on manual testing, which further slows down delivery.

Measuring code complexity using metrics like cyclomatic complexity or maintainability index helps teams identify risky areas early. These metrics don’t replace good design practices, but they provide useful signals about where refactoring might be needed. Simplifying logic, improving modularity, and following clean coding principles can significantly reduce complexity without changing functionality.

Keeping code complexity under control is a shared responsibility between developers and testers. When complexity is actively managed, software becomes easier to test, easier to maintain, and far more resilient to change—especially in fast-moving development environments.

Learn more about code complexity here:
https://keploy.io/blog/community/what-is-code-complexity