Introduction to Cyclomatic Complexity
Cyclomatic complexity is a measurement to calculate the code complexity and the errors present in the code using the graph methodology in which nodes of the graph represent source code and the arcs present in the graph represent the control flow in the program. The graph notation is used to find a number of ways for the given program and find the complexity of the program. The topological intricacy of the graph can be compared with computer program complexity.
What is Cyclomatic Complexity?
The measurement of efficiency of computer programs using the graphical representation method is known as Cyclomatic complexity. It is the software metric for finding complexity and errors present in the program. The complexity of source code can be easily measured. It was given by McCabe for finding the efficiency of a computer program. It uses the graphical representation in which the independent paths represent the number of ways in which the computer program can execute. This method uses the graph methodology to finding computer program complexity which can be easily applied for source files of the program, individual functions, and modules of the program. The flow of the graph is from top to bottom and the bottom node is used for representing the program end. The maximum value is given as ten. The use of Cyclomatic complexity can be done for software testing, finding the defects and the correlation among them and limiting the complexity of source code.
It can be calculated by the given formula:
V(G) = E- N + 2*P
- P = Total connected components present in graph.
- E = Total edge count in a graph.
- N = Total nodes count in a graph.
For calculating the Cyclomatic complexity, the first graph is made from the assembly code. The assembly code is first to disassemble and then from that code graph is created in the following steps:
- One node is created for one instruction.
- The nodes are internally connected to each other when the next instruction is related to previous instruction.
- The recursive call is considered as one functional call otherwise it will create a loop situation that will create a problem to calculate the Cyclomatic complexity for source program.
It is inversely proportional to code readability and easy to understand code. It means when the Cyclomatic complexity is greater the code is not easy to understand and difficult to read and when the complexity is less the code is easy to read and easy to understand.
Cyclomatic complexity uses a simple algorithm to calculate the program complexity. The Cyclomatic complexity has the formula V(G) = ‘E-N+2*P’ which is used for calculating the complexity of a computer program. For this methodology, it has certain properties that exist to calculate the Cyclomatic complexity. Some of them are mentioned below:
- E represents no. of edges present in the graph, M is McCabe’s complexity and N is nodes count.
- V(G) is an expression used for defining the number of independent paths of the graph.
- The V(G) should be greater than 1.
- If the value of V(G) is equal to 1 then there is only one path in the graph which means there is only one solution to the computer program.
- The complexity should be less than 10.
- It is completely independent of source lines count in the computer program. The complexity does not depend on how many lines of code are there or how many branches are present in the graph.
- If the code is reformatted it does not affect the Cyclomatic complexity.
- The metric count gets linearly growth if the complexity of the function is increased. It means if the code contains a number of if-else statement it will directly increase the number of metric and the Cyclomatic complexity.
- This calculation is quite easy for a single function but when the number of function increases in the source program it increases the complexity calculation. The main reason for the increase in complexity is because of the function call which is not shown in the flow diagram.
- It is used for calculating the complexity of source code and not the complexity of data structures used in the source code.
- Greater the Cyclomatic complexity less efficient is the source code.
Advantages of Cyclomatic Complexity
It is used for calculating the code complexity and the errors present in the source code if any. Apart from these, there are several advantages, that need to be overlooked while using it for calculating the code complexity. Some of them are described below:
- As the Cyclomatic complexity calculates the independent paths for the source program, it gives the idea of a number of test cases for testing the source code. So when the number of independent path count is present it helps to test the code in that number of times. And by this, the whole code is covered for testing and solve the bugs if present.
- By finding the code complexity the potential defect risk is also decreased which means the relative cost is reduced for finding the defects in source code. By the Cyclomatic complexity calculation, the program maintenance cost is also reduced.
- Based on the Cyclomatic complexity the project released can be shipped and the product can be on board in the organization.
- It uses the graphical representation for representing the number of solutions for executing the same source code. And to calculate the Cyclomatic Complexity at that time became easier.
Cyclomatic complexity uses the graphical representation to calculate the complexity of the source program. The graph uses the linear independent path which represents the individual solution for the execution of source code. It is widely used for testing different software and finding defects in the source program.
This is a guide to the What is Cyclomatic Complexity?. Here we discuss the Introduction and the different Properties along with advantages. You can also go through our suggested articles to learn more –
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