cyclomatic complexity


Cyclomatic complexity is a vital metric in the field of software engineering. It provides insight into the complexity of a software program by measuring the number of independent paths through the code. This article aims to explain what it is, why it is important, how to calculate it, and ways to reduce it. By understanding this metric, software engineers can design and maintain more efficient and maintainable code. 


What is Cyclomatic Complexity? 

Cyclomatic complexity is a software metric that measures the complexity of a program by counting the number of decision points and paths within the code. Thomas J. McCabe developed it in 1976 as a way to quantify the complexity of a program’s control flow. Consequently, a higher cyclomatic complexity considers the program to be more complex.

How to Find Cyclomatic Complexity 

There are several ways to find the cyclomatic complexity of a program. One common method is to use a control flow graph, which visually represents the program’s control flow. Each node in the graph represents a decision point, and each edge represents a possible path through the code. By counting the number of nodes and edges in the graph, the cyclomatic complexity can be determined.

On the other hand, another way to find it is by using a cyclomatic complexity calculator or a static code analysis tool. These tools analyze the code and automatically calculates it. Additionally, development environments can integrate them and offer real-time feedback on the complexity of the code.

Why is It Important in Software Engineering? 

Cyclomatic complexity is important in software engineering for several reasons. Firstly, it provides a quantitative measure of the complexity of a program. This information is valuable for understanding the maintainability and readability of the code. A higher one indicates that the code may be harder to understand, test, and maintain. 

Secondly, cyclomatic complexity can help identify potential areas of the code that are prone to errors. Research has shown that there is a correlation between this metric and the number of defects in a program. By managing and reducing it, software engineers can improve the quality and reliability of their code. 

Lastly, this metric can assist in estimating the effort required to test a program. Programs with high cyclomatic complexity are more likely to have a larger number of test cases and require more extensive testing. Understanding it can help allocate appropriate testing resources and ensure thorough coverage. 

Understanding the Basics of Cyclomatic Complexity 

To understand cyclomatic complexity, it is essential to grasp the concept of control flow. Control flow refers to the sequence in which statements or instructions are executed within a program. Decision points, such as if statements or loops, introduce branches in the control flow. 

It measures the number of independent paths through a program’s control flow. It can be calculated by counting the number of decision points and adding one. This calculation is based on the assumption that each decision point has at least two possible outcomes. 

How to Calculate Cyclomatic Complexity 

You can calculate cyclomatic complexity using the formula CC = E – N + 2P, where E represents the number of edges, N represents the number of nodes, and P represents the number of connected components. This formula incorporates the count of decision points and paths in the control flow graph. Alternatively, you can calculate this metric as the number of predicate nodes plus one.

Interpreting Cyclomatic Complexity Values 

Interpreting cyclomatic complexity values can help software engineers assess the complexity of their code. Generally, a higher one indicates a more complex program. However, there is no universal threshold for what is considered a “good” or “bad” one. It depends on the specific context and requirements of the software project. 

As a guideline, software developers generally consider cyclomatic complexity values below 10 to be acceptable. Values between 10 and 20 indicate moderately complex code that may benefit from simplification. However, values above 20 suggest highly complex code that requires careful review and refactoring.

cyclomatic complexity

What is Good Cyclomatic Complexity? 

While there is no definitive answer to what constitutes good cyclomatic complexity, maintaining a balance between complexity and simplicity is crucial. Software engineers should aim to reduce this metric to improve code readability, maintainability, and testability

A good approach is to use techniques such as modularization, encapsulation, and abstraction to break down complex code into smaller, more manageable components. This not only reduces cyclomatic complexity but also improves code organization and reusability. 

Benefits of Managing It 

Managing cyclomatic complexity offers several benefits for software engineering projects. By reducing complexity, developers can improve the readability of the code, making it easier to understand and maintain. This, in turn, leads to fewer bugs and easier debugging. 

Additionally, managing it can enhance code testability. Programs with lower complexity are typically easier to test and require fewer test cases to achieve comprehensive coverage. This can save time and effort during the testing phase of a project. 

Furthermore, reducing cyclomatic complexity can improve the overall performance of a software system. Simplifying complex code can lead to faster execution times and improved resource utilization, resulting in a more efficient and responsive application.

Which are the 3 Ways to Compute Cyclomatic Complexity? 

There are three commonly used methods to compute it: 

  • Control Flow Graph (CFG): This method involves creating a graphical representation of the program’s control flow. The graph consists of nodes representing decision points and edges representing possible paths. The cyclomatic complexity is then calculated using the number of nodes and edges in the graph. 
  • Cyclomatic Complexity Calculator: This method involves using specialized software tools that analyze the source code and automatically calculate this metric. These tools provide developers with real-time feedback and can be integrated into development environments for seamless analysis. 
  • Static Code Analysis: This method involves using static code analysis tools that analyze the source code without executing it. These tools can identify potential issues, including high cyclomatic complexity, and provide suggestions for code improvement. Static code analysis can be performed as part of the development process or during code reviews. 

How to Reduce Cyclomatic Complexity 

Reducing cyclomatic complexity is an important aspect of software development. Therefore, here are some strategies to help reduce it:

  1. Refactor Complex Code: Firstly, identify complex sections of code and refactor them into smaller, more manageable functions or modules. This improves code organization and makes it easier to understand and maintain.
  2. Use Control Structures Wisely: Secondly, minimize the use of nested loops and conditionals. Consider using switch statements or polymorphism to simplify complex branching logic.
  3. Limit the Number of Decision Points: Thirdly, try to reduce the number of decision points in a program. This can be achieved by breaking down complex conditions into smaller, more manageable parts.
  4. Encourage Code Reusability: Fourthly, promote the reuse of code through the use of functions, libraries, and frameworks. Reusable code reduces the overall complexity of a program.
  5. Write Clear and Concise Code: Lastly, use meaningful variable and function names, and avoid complex logic or unnecessary complexity. Clear and concise code is easier to understand and maintain.

Can Cyclomatic Complexity be 0? 

Cyclomatic complexity cannot be zero in most cases. The minimum value for a program is one, indicating that there is at least one decision point or path in the code. Even the simplest program with sequential execution will have a value of one. 

However, it is possible to have a cyclomatic complexity of zero in certain scenarios. For example, a program with no decision points or branching logic will have a value of zero. This can occur in very simple programs that only consist of a single statement or function. 

cto vs vp engineering

Cyclomatic Complexity: Number of Decisions 

The cyclomatic complexity of a program is directly related to the number of decision points or branches in the code. Each decision point introduces additional paths through the program’s control flow, increasing the cyclomatic complexity. 

By understanding the number of decisions in a program, software engineers can gain insight into the potential complexity of the code. They can then take appropriate measures to manage and reduce the cyclomatic complexity to improve code quality and maintainability. 

Tools for Measuring It

Several tools are available for measuring cyclomatic complexity in software projects. These tools analyze the source code and provide developers with detailed reports on the complexity of their code. Some popular tools include: 

1. SonarQube: SonarQube is an open-source platform that performs continuous code quality analysis.

2. PMD: PMD is a static code analysis tool that can be used to find common programming flaws and code quality issues. It includes a cyclomatic complexity rule that helps identify complex code. 

3. Visual Studio Code: Visual Studio Code is a popular integrated development environment (IDE) that offers extensions for analyzing code complexity. These extensions provide this metrics and other useful insights. 

Conclusion and Key Takeaways

Cyclomatic complexity is a crucial metric in software engineering that measures the complexity of a program’s control flow. Understanding and managing it is essential for developing maintainable, readable, and reliable code. 

By calculating cyclomatic complexity, software engineers can assess the complexity of their code and identify potential areas for improvement. Reducing it through techniques such as refactoring, simplifying control structures, and promoting code reusability can lead to more efficient and maintainable software systems. 

Remember, in software engineering, we use cyclomatic complexity as just one of many metrics. You should use it alongside other methodologies and best practices to ensure the overall quality and performance of the codebase. Implement these strategies and improve your software development process!


Start optimizing your code by measuringand implementing strategies to reduce it. You can read our article about Engineering Analytics Systems and increase readability, maintainability, and quality for your software projects.

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