# Breadth First Traversal or BFS for a Graph

Breadth First Traversal (or Search) for a graph is similar to Breadth First Traversal of a tree (See method 2 of this post). The only catch here is, unlike trees, graphs may contain cycles, so we may come to the same node again. To avoid processing a node more than once, we use a boolean visited array. For simplicity, it is assumed that all vertices are reachable from the starting vertex.
For example, in the following graph, we start traversal from vertex 2. When we come to vertex 0, we look for all adjacent vertices of it. 2 is also an adjacent vertex of 0. If we don’t mark visited vertices, then 2 will be processed again and it will become a non-terminating process. A Breadth First Traversal of the following graph is 2, 0, 3, 1.

## Recommended: Please solve it on “PRACTICE ” first, before moving on to the solution.

Following are C++ and Java implementations of simple Breadth First Traversal from a given source.

The C++ implementation uses adjacency list representation of graphs. STL‘s list container is used to store lists of adjacent nodes and queue of nodes needed for BFS traversal.

## C++

```// Program to print BFS traversal from a given
// source vertex. BFS(int s) traverses vertices
// reachable from s.
#include<iostream>
#include <list>

using namespace std;

// This class represents a directed graph using
class Graph
{
int V;    // No. of vertices

// Pointer to an array containing adjacency
// lists
public:
Graph(int V);  // Constructor

// function to add an edge to graph

// prints BFS traversal from a given source s
void BFS(int s);
};

Graph::Graph(int V)
{
this->V = V;
}

{
}

void Graph::BFS(int s)
{
// Mark all the vertices as not visited
bool *visited = new bool[V];
for(int i = 0; i < V; i++)
visited[i] = false;

// Create a queue for BFS
list<int> queue;

// Mark the current node as visited and enqueue it
visited[s] = true;
queue.push_back(s);

// 'i' will be used to get all adjacent
// vertices of a vertex
list<int>::iterator i;

while(!queue.empty())
{
// Dequeue a vertex from queue and print it
s = queue.front();
cout << s << " ";
queue.pop_front();

// Get all adjacent vertices of the dequeued
// vertex s. If a adjacent has not been visited,
// then mark it visited and enqueue it
{
if (!visited[*i])
{
visited[*i] = true;
queue.push_back(*i);
}
}
}
}

// Driver program to test methods of graph class
int main()
{
// Create a graph given in the above diagram
Graph g(4);

cout << "Following is Breadth First Traversal "
<< "(starting from vertex 2) \n";
g.BFS(2);

return 0;
}
```

## Java

```// Java program to print BFS traversal from a given source vertex.
// BFS(int s) traverses vertices reachable from s.
import java.io.*;
import java.util.*;

// This class represents a directed graph using adjacency list
// representation
class Graph
{
private int V;   // No. of vertices

// Constructor
Graph(int v)
{
V = v;
for (int i=0; i<v; ++i)
}

// Function to add an edge into the graph
{
}

// prints BFS traversal from a given source s
void BFS(int s)
{
// Mark all the vertices as not visited(By default
// set as false)
boolean visited[] = new boolean[V];

// Create a queue for BFS

// Mark the current node as visited and enqueue it
visited[s]=true;

while (queue.size() != 0)
{
// Dequeue a vertex from queue and print it
s = queue.poll();
System.out.print(s+" ");

// Get all adjacent vertices of the dequeued vertex s
// If a adjacent has not been visited, then mark it
// visited and enqueue it
while (i.hasNext())
{
int n = i.next();
if (!visited[n])
{
visited[n] = true;
}
}
}
}

// Driver method to
public static void main(String args[])
{
Graph g = new Graph(4);

System.out.println("Following is Breadth First Traversal "+
"(starting from vertex 2)");

g.BFS(2);
}
}
// This code is contributed by Aakash Hasija
```

## Python

```# Program to print BFS traversal from a given source
# vertex. BFS(int s) traverses vertices reachable
# from s.
from collections import defaultdict

# This class represents a directed graph using adjacency
# list representation
class Graph:

# Constructor
def __init__(self):

# default dictionary to store graph
self.graph = defaultdict(list)

# function to add an edge to graph
self.graph[u].append(v)

# Function to print a BFS of graph
def BFS(self, s):

# Mark all the vertices as not visited
visited = [False]*(len(self.graph))

# Create a queue for BFS
queue = []

# Mark the source node as visited and enqueue it
queue.append(s)
visited[s] = True

while queue:

# Dequeue a vertex from queue and print it
s = queue.pop(0)
print s,

# Get all adjacent vertices of the dequeued
# vertex s. If a adjacent has not been visited,
# then mark it visited and enqueue it
for i in self.graph[s]:
if visited[i] == False:
queue.append(i)
visited[i] = True

# Driver code
# Create a graph given in the above diagram
g = Graph()

print "Following is Breadth First Traversal (starting from vertex 2)"
g.BFS(2)

# This code is contributed by Neelam Yadav
```

Output:

```Following is Breadth First Traversal (starting from vertex 2)
2 0 3 1
```

Illustration :

Note that the above code traverses only the vertices reachable from a given source vertex. All the vertices may not be reachable from a given vertex (example Disconnected graph). To print all the vertices, we can modify the BFS function to do traversal starting from all nodes one by one (Like the DFS modified version) .

Time Complexity: O(V+E) where V is number of vertices in the graph and E is number of edges in the graph.

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