Analyzing Software Code — Cyclomatic Complexity

3 min readFeb 5, 2024

Analyzing Software Code — Cyclomatic Complexity

Cyclomatic Complexity serves as a pivotal metric in assessing the structural intricacy of code. This metric is derived by evaluating the multitude of distinct code paths within the program’s flow. Essentially, it quantifies the number of independent routes that the program can take during its execution. The rationale behind evaluating Cyclomatic Complexity lies in its ability to offer valuable insights into the program’s comprehensibility, testability, and maintainability.

In essence, the concept revolves around the understanding that a program with a convoluted control flow necessitates a more extensive set of tests to attain optimal code coverage. The term “control flow” pertains to the sequence in which the program’s instructions are executed, and the complexity of this flow is directly proportional to the number of decision points, loops, and branches within the code.

Cyclomatic Complexity is a numerical representation of the software’s structural complexity, and it aids developers in gauging the potential challenges associated with comprehending, testing, and maintaining the codebase. The metric’s significance becomes particularly pronounced when considering the relationship between complexity and code quality.

The underlying principle is straightforward: a higher Cyclomatic Complexity score indicates a more intricate program structure, which, in turn, implies a greater number of code paths and decision points. While this complexity can be inherent in certain algorithms or functionalities, it also raises concerns about the software’s robustness and maintainability.

One notable implication of elevated Cyclomatic Complexity is the increased testing burden. The more intricate the code, the more extensive and thorough the testing needs to be to achieve satisfactory code coverage. Code coverage refers to the percentage of the codebase that is executed during testing. Adequate coverage is crucial for identifying and rectifying potential issues, ensuring the software behaves as intended across various scenarios.

Furthermore, the metric’s influence extends to the maintainability of the software. A highly complex codebase is inherently more challenging to maintain. When developers need to introduce modifications, fix bugs, or add new features, the understanding and navigation of intricate code become arduous tasks. This, in turn, heightens the likelihood of introducing errors during the maintenance process.

In practice, Cyclomatic Complexity is often used as a guideline for code reviews and quality assessments. Development teams may establish threshold values for acceptable complexity levels, and code exceeding these thresholds may undergo additional scrutiny. By incorporating such metrics into the development process, teams can proactively address complexity issues and enhance the overall quality of the software.

It’s important to note that while Cyclomatic Complexity provides valuable insights, it is not a standalone indicator of code quality. Other metrics and considerations, such as code duplication, adherence to coding standards, and proper documentation, also contribute to the overall quality of a software system.

How to measure Cyclomatic Complexity

To measure the complexity of a program by counting the number of independent paths through the source code. It is calculated based on the control flow of the program, considering decision points such as loops, conditionals, and branches.

The formula for Cyclomatic Complexity is given by:

E — N + 2P

Where:

E is the number of edges in the control flow graph.
N is the number of nodes in the control flow graph.
P is the number of connected components (for a single program, P is 1).

Let’s consider a simple example in C#:

class Example
{
    public void SimpleMethod(int x)
    {
        if (x > 0) // E
        {
            Console.WriteLine("Positive"); // P and N
        }
        else
        {
            Console.WriteLine("Non-positive"); // P and N
        }
    }
}

In this example, the control flow graph has three nodes (one for the condition, and two for the branches) and three edges. Applying the formula:

E = 2, N = 2, P = 1

Cyclomatic Complexity = E −N + 2P became 2 − 2 + 2(1) = 2

So, the Cyclomatic Complexity for the SimpleMethod is 2, indicating that there are two independent paths through the code. Lower cyclomatic complexity values are generally desirable, as they suggest simpler and more maintainable code.