# BFS (Breadth-First Search) in Binary Trees and Graphs

BFS (Breadth-First Search) is one of the simplest algorithms for traversing a graph. Prim’s min-spanning-tree and Djikstra’s algorithm use similar ideas as BFS. BFS is also known as Level-order traversal because the algorithm discover all nodes at distance k from root before discovering any nodes at distance k+1.

### Pseudocode for BFS

Let G be the graph/tree and s be the source node/root. We’ll maintain a vis (visited) array to mark a node as visited ie for node i, vis[i] is 1 if it has been visited already, otherwise vis[i] will be 0. We’ll use Queue – data structure for performing BFS traversal. Let Q be the required queue.

BFS (G, s)
vis[s] = 1
Enqueue (Q, s)
while (!Q.empty()):
u = Q.front()
Q.pop()
if vis[v] === 0:
vis[v] = 1
Enqueue(Q, v)
end
end

Time complexity for Breadth-First Search is O(n) where n is the number of nodes. This is because each node is visited only once.

Note: We advise you to try implementing BFS for a graph yourself before reading the implementation in C++ below:

### Implementation for a Binary Tree

Level Order traversal for above tree is: 1, 20 21, 30 31

### Code

void BFS (Node *root) {
if (root == NULL) {
return;
}
queue<Node*> qu;
qu.push(root);
while (!qu.empty()) {
int size = (int) qu.size();
for (int i=0; i<size; i++) {
Node* curr = qu.front();
cout<<(curr->value)<<" ";
qu.pop();
if (curr->left) {
qu.push(curr->left);
}
if (curr->right) {
qu.push(curr->right);
}
}
}
cout<<endl;
}
}


Here’s a working example:

https://ideone.com/aKazxd

### Implementation for a Graph

BFS traversal for above graph is: 1, 2 3, 4, 5

Code

void BFS (int s, int n, vector<int> graph[]) {
if (s == 0) {
return;
}
int vis[n+1];
queue<int> qu;

for (int i=1; i<=n; i++) {
vis[i] = 0;
}
qu.push(s);
vis[s] = 1;
cout<<s<<endl;
while (!qu.empty()) {
int node = qu.front();
qu.pop();
for (int i=0; i<graph[node].size(); i++) {
int j = graph[node][i];
if (vis[j] == 0) {
vis[j] = 1;
qu.push(j);
cout<<j<<" ";
}
}
cout<<endl;
}
}


Here’s a working example:

https://ideone.com/KobplI

In the next post we’ll learn about DFS (Depth-First Search)