Cyclomatic Complexity Calculator
Calculate McCabe's cyclomatic complexity metric for software code analysis
Calculate Cyclomatic Complexity
Nodes represent program statements or decision points
Edges represent control flow connections between nodes
Usually 1 for single programs (default)
Cyclomatic Complexity Analysis
McCabe's Formula
Calculation: M = 0 - 0 + 2×1 = 2
Where: M = Cyclomatic Complexity, E = Edges, N = Nodes, C = Components
Example: Collatz Conjecture Program
Program Description
A program that computes the Collatz conjecture sequence with input validation and additional loops.
Control Flow Analysis:
- Input validation loop
- Main Collatz sequence loop
- Final repetition loop
- Multiple conditional statements
Complexity Calculation
Nodes: 14 (decision points and statements)
Edges: 18 (control flow connections)
Components: 1 (single connected program)
Cyclomatic Complexity: M = 18 - 14 + 2×1 = 6
Complexity Scale
McCabe originally recommended splitting modules when complexity reaches 10.
Control Flow Elements
Nodes (N)
Program statements, conditions, function calls
Edges (E)
Control flow paths between nodes
Components (C)
Connected subgraphs (usually 1)
Common Patterns
- • If statement: +1
- • Loop: +1
- • Switch case: +1 per case
- • Try-catch: +1
Understanding Cyclomatic Complexity
What is Cyclomatic Complexity?
Cyclomatic complexity is a software metric developed by Thomas McCabe in 1976 that measures the complexity of a program by quantifying the number of linearly independent paths through the program's source code.
Why Does It Matter?
- •Code Quality: Higher complexity indicates harder-to-maintain code
- •Testing: More paths require more test cases
- •Bug Risk: Complex code is more prone to errors
- •Refactoring: Identifies code that needs simplification
McCabe's Formula
Control Flow Graph
Represents program structure as nodes (statements) connected by edges (control flow)
Independent Paths
Each path through the program that introduces new edges not covered by previous paths
Practical Usage
Set complexity limits in code reviews and automated quality checks