Cyclomatic Complexity
Cyclomatic Complexity may be defined as
 It is a software metric that measures the logical complexity of the program code.
 It counts the number of decisions in the given program code.
 It measures the number of linearly independent paths through the program code.
Cyclomatic complexity indicates several information about the program code
Cyclomatic Complexity  Meaning 
1 – 10 

10 – 20 

20 – 40 

> 40 

Importance of Cyclomatic Complexity
 It helps in determining the software quality.
 It is an important indicator of program code’s readability, maintainability and portability.
 It helps the developers and testers to determine independent path executions.
 It helps to focus more on the uncovered paths.
 It evaluates the risk associated with the application or program.
 It provides assurance to the developers that all the paths have been tested at least once.
Properties of Cyclomatic Complexity
 It is the maximum number of independent paths through the program code.
 It depends only on the number of decisions in the program code.
 Insertion or deletion of functional statements from the code does not affect its cyclomatic complexity.
 It is always greater than or equal to 1.
Calculating Cyclomatic Complexity
Cyclomatic complexity is calculated using the control flow representation of the program code.
In control flow representation of the program code,
 Nodes represent parts of the code having no branches.
 Edges represent possible control flow transfers during program execution
There are 3 commonly used methods for calculating the cyclomatic complexity
Method01:
Cyclomatic Complexity = Total number of closed regions in the control flow graph + 1
Method02:
Cyclomatic Complexity = E – N + 2
Here
 E = Total number of edges in the control flow graph
 N = Total number of nodes in the control flow graph
Method03:
Cyclomatic Complexity = P + 1
Here,
P = Total number of predicate nodes contained in the control flow graph
Note
 Predicate nodes are the conditional nodes.
 They give rise to two branches in the control flow graph.
PRACTICE PROBLEMS BASED ON CYCLOMATIC COMPLEXITY
Problem01:
Calculate cyclomatic complexity for the given code
IF A = 354 THEN IF B > C THEN A = B ELSE A = C END IF END IF PRINT A
Solution
We draw the following control flow graph for the given code
Using the above control flow graph, the cyclomatic complexity may be calculated as
Method01:
Cyclomatic Complexity
= Total number of closed regions in the control flow graph + 1
= 2 + 1
= 3
Method02:
Cyclomatic Complexity
= E – N + 2
= 8 – 7 + 2
= 3
Method03:
Cyclomatic Complexity
= P + 1
= 2 + 1
= 3
Problem02:
Calculate cyclomatic complexity for the given code
{ int i, j, k; for (i=0 ; i<=N ; i++) p[i] = 1; for (i=2 ; i<=N ; i++) { k = p[i]; j=1; while (a[p[j1]] > a[k] { p[j] = p[j1]; j; } p[j]=k; }
Solution
We draw the following control flow graph for the given code
Using the above control flow graph, the cyclomatic complexity may be calculated as
Method01:
Cyclomatic Complexity
= Total number of closed regions in the control flow graph + 1
= 3 + 1
= 4
Method02:
Cyclomatic Complexity
= E – N + 2
= 16 – 14 + 2
= 4
Method03:
Cyclomatic Complexity
= P + 1
= 3 + 1
= 4
Problem03:
Calculate cyclomatic complexity for the given code
begin int x, y, power; float z; input(x, y); if(y<0) power = y; else power = y; z=1; while(power!=0) { z=z*x; power=power1; } if(y<0) z=1/z; output(z); end
Solution
We draw the following control flow graph for the given code
Using the above control flow graph, the cyclomatic complexity may be calculated as
Method01:
Cyclomatic Complexity
= Total number of closed regions in the control flow graph + 1
= 3 + 1
= 4
Method02:
Cyclomatic Complexity
= E – N + 2
= 16 – 14 + 2
= 4
Method03:
Cyclomatic Complexity
= P + 1
= 3 + 1
= 4
To gain better understanding about Cyclomatic Complexity,
Next Article Cause Effect Graph Technique
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