What is cyclomatic complexity in Java?
If you’ve been a programmer for a while, chances are that you’ve come across code that looks like a mess. Or, simply put, a spaghetti codebase. And you’d probably know that the more complex the code looks, the more likely it has bugs.
In a nutshell, that’s exactly what cyclic complexity is.
So, how do we quantify and manage this complexity?
Here’s where cyclomatic complexity comes in. Simply put, cyclic complexity is the total number of independent execution paths in a given code solution. Now, cyclomatic complexity reflects the ease at which a program can be comprehended, meaning that if it is high, it is complex and, therefore, is likely to have bugs.
Do you know how high cyclomatic complexity leads to more bugs?
Yes, since it measures the number of possible execution routes, it is an indirect measure of the number of test cases you will need to include in your code design. More test cases will be run over, and an edge case may be missing.
In simple words, we can say that cyclomatic complexity is a proposition to complexity.
How is cyclomatic complexity calculated?
To determine the cyclomatic complexity of the program, we have to build a control flow graph.
A control flow graph is the graphical representation of the control sequences that are used in place of the execution of the program.
The control flow graph easily reveals the nodes, edges, and connected components. Then, we can use the cyclomatic complexity formula to compute the complexity.
The formula for Cyclomatic Complexity(C) is:
C = N – E + 2P
N: Number of nodes
E: Number of edges
P: Number of connected components
This calculation returns the number of linearly independent paths in the code, indicating the minimum number of paths you must test so that each decision point is processed at least once.
Cyclomatic Complexity in Java Code
Let’s understand how cyclomatic complexity works in practice by examining the following Java code. Here, you will be able to get an idea of how the control structure contributes to cyclomatic complexity.
For example, consider this class “ShippingCostCalculator”, which has a method “calculateShippingCost” that calculates the shipping cost based on customer location and total bill amount.
public class ShippingCostCalculator { public static double calculateShippingCost(String location, double orderAmount){ double shippingCost; if (location.equalsIgnoreCase("international")) { shippingCost = 20.0; } else if (orderAmount > 100) { shippingCost = 0.0; } else { shippingCost = 5.0; } return shippingCost; } public static void main(String[] args) { String location = "international"; double orderAmount = 120.0; double shippingAmount = calculateShippingCost(location, orderAmount); System.out.println("Shipping Cost = $" + shippingAmount); } }
We can represent the method calculateShippingCost with the following control flow graph.
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From this control flow graph, we can derive the number of nodes(N) and the number of edges(E).
E = 8
N = 7
P = 1 (single connected component)
So, let’s apply the formula to get the Cyclomatic Complexity(C)
C = E – N + 2P
= 8 – 7 + 2(1)
= 3
The cyclomatic complexity score of three implies that the code follows three unique routes. Each approach must be checked to ensure all possibilities are considered.
How Can We Reduce Cyclomatic Complexity?
Cyclomatic complexity is a highly significant software development statistic. It significantly impacts the total code complexity of a piece of code. As previously noted, putting cyclomatic complexity in the bottom layer will help the code be more intelligible.
It is critical to understand how to minimize the cyclomatic complexity. Let’s look at some effective ways to lower cyclomatic complexity while improving code quality and understandability.
- Writing smaller functions: Breaking down large chunks of code into small units has numerous benefits. It reduces code complexity and makes it more readable. Small functions are also easier to test and help developers keep their codebase clean and resilient.
- Avoid flag parameters: Flag parameters frequently result in confusing logic. Replacing flag parameters with different, purpose-specific functions will reduce the number of decision routes and make the code easier to maintain and test.
- Design patterns: The design patterns create a uniform vocabulary of conventional solutions that others can easily understand. For example, a strategy pattern can help you limit the use of if statements. The template pattern can assist you in eliminating code duplication.
- Simplifying conditional statements: Simplifying decision statements reduces cyclomatic complexity by minimizing the number of independent paths through the code. Complex, nested conditions increase the number of decision points, making the code harder to understand and maintain.
// method without simplified conditional logic public String getStatus(int age, boolean isStudent) { if (age > 18) { if (isStudent) { return "Adult Student"; } else { return "Adult"; } } else { if (isStudent) { return "Minor Student"; } else { return "Minor"; } } }
Let’s simplify the conditional statements with the help of a ternary operator.
// method with simplified conditional logic public String getStatus(int age, boolean isStudent) { if (age <= 18) { return isStudent ? "Minor Student" : "Minor"; } return isStudent ? "Adult Student" : "Adult"; }
Now, we can see the reduction in the cyclomatic complexity value, leading the developer or tester to easily maintain the codebase.
By focusing on these tactics, developers can reduce cyclomatic complexity metrics while also improving the quality of their code. This will make it enjoyable for anybody who comes across it to work with it.
Wrapping up
Controlling cyclomatic complexity is essential to keeping code clear and error-free. Using best practices guarantees a more reliable software solution and a more seamless development process.
Additionally, Developers can decrease testing efforts and improve code readability by knowing how to quantify and reduce complexity.
Thank you for reading.