What Is Cyclomatic Complexity?
Cyclomatic complexity is a software metric used to measure the complexity of a program. It was developed by Thomas McCabe in 1976 to help measure the difficulty of testing software. Cyclomatic complexity determines the number of independent paths through a program’s source code by analyzing its control flow. The higher the cyclomatic complexity, the more complex the code is and the more difficult it is to understand, test, and maintain. Understanding and managing cyclomatic complexity is important in software development to improve code quality and reduce the risk of bugs and errors.
In software development, cyclomatic complexity is a useful metric for measuring the complexity of a program’s control flow. If a program’s source code has no control flow statements, its cyclomatic complexity is 1, as there is only one possible path.
However, if the program contains an if condition, the cyclomatic complexity increases to 2, as there are now two possible paths – one for when the condition is true, and one for when it is false. To mathematically represent the control flow of a structured program, a directed graph can be used to show the edges that join two basic blocks of the program, indicating how control may pass from one to the other.
How Cyclomatic Complexity is Calculated?
In software development, it is crucial to have a way to measure the complexity of a program. To address this need, Thomas McCabe introduced the concept of cyclomatic number, denoted as V(G), which serves as an indicator of software complexity. The cyclomatic number is determined by counting the number of linearly independent paths through a program in its graph representation. In other words, it represents the number of decision points and control flow statements present in a program. By calculating the cyclomatic number of a program’s control graph G using the appropriate formula, developers can gain insights into its complexity and identify potential issues with testing and maintenance.
Cyclomatic complexity, denoted as V(G), is a software metric that can be defined using the following formula:
V(G) = E – N + 2P
Here,
- E represents the number of edges in the control flow graph of the program
- while N represents the number of nodes in the same graph.
- P represents the number of connected components in the graph.
By using this formula, we can calculate the cyclomatic complexity of a program and gain insights into its complexity and potential challenges in testing and maintaining the code.
The process of calculating cyclomatic complexity and designing test cases involves several important steps, including:
- Constructing a graph with nodes and edges that represents the program’s control flow based on its code.
- Identifying the independent paths through the program to determine the number of decision points and control flow statements.
- Calculating the cyclomatic complexity using the appropriate formula, which takes into account the number of edges, nodes, and connected components in the graph.
- Designing test cases based on the program’s cyclomatic complexity, with a focus on testing all possible independent paths through the code.
By following these steps, software developers can gain a better understanding of the complexity of their programs, improve their testing processes, and reduce the risk of bugs and errors.
Properties of Cyclomatic Complexity in Software Engineering
Cyclomatic complexity possesses several important properties that are essential to understand for software development. These properties include:
- The cyclomatic number, denoted as V(G), represents the maximum number of independent paths through the program’s control flow graph.
- The minimum value of V(G) is 1, which means that every program has at least one independent path and therefore, a minimum complexity.
- When V(G) is equal to 1, the program’s control flow graph will have only one path.
- In software development, it is essential to aim for minimizing the program’s cyclomatic complexity to a value of 10 or less, which can help to reduce the risk of bugs and errors, enhance program maintainability and improve code quality.
Use of Cyclomatic Complexity in Software Development
- Cyclomatic complexity is a valuable tool for both developers and testers.
- It helps determine the number of independent path executions in a program.
- By testing each path at least once, developers can ensure that all paths are covered.
- This approach helps to focus on any uncovered paths that require additional testing.
- By improving code coverage, the risk associated with the program can be more accurately evaluated.
- Using these metrics early in the program can help identify and mitigate potential risks and issues before they become more difficult and costly to resolve.
- Overall, the use of cyclomatic complexity is an effective approach for improving the quality, reliability, and maintainability of software programs.
Advantages of Cyclomatic Complexity
Cyclomatic complexity has several advantages in software development, which include:
- It can be used as a quality metric to provide a relative measure of complexity for different designs, helping developers to identify and evaluate the most efficient and effective design options.
- Cyclomatic complexity is easy to apply, making it accessible to developers and testers at all levels of expertise, and can be used in a variety of programming languages and environments.
- By measuring the minimum effort and areas of concentration needed for testing, cyclomatic complexity can guide the testing process, helping to identify potential risks and issues and ensuring that all critical paths have been tested.
- Compared to Halstead’s metrics, cyclomatic complexity is faster to compute, making it a useful approach for developers who need to quickly assess the complexity of their software programs.
Disadvantages of Cyclomatic Complexity
- It only measures a program’s control complexity and not its data complexity, which means that it may not provide a complete picture of the overall complexity of the program.
- In some cases, such as simple comparisons and decision structures, cyclomatic complexity may provide a misleading figure, potentially leading developers to underestimate or overestimate the actual complexity of the program.
- Nested conditional structures can be more difficult to understand than non-nested structures, which can make it challenging to accurately measure the complexity of programs with complex control flow.
Despite these limitations, cyclomatic complexity remains a useful tool for evaluating software complexity and guiding testing and development efforts.
Had your doubt cleared regarding the Cyclomatic Complexity? and if you find this article worthwhile, we urge you guys to follow our tutorials.freshersnow.com frequently.