What are some applications of Depth First Search?

Depth First Traversal (or Search) for a graph is similar to Depth First Traversal of a tree. The only catch here is, that, unlike trees, graphs may contain cycles (a node may be visited twice). To avoid processing a node more than once, use a boolean visited array. A graph can have more than one DFS traversal.

Follow the below steps to solve the problem:

  • Create a recursive function that takes the index of the node and a visited array.
  • Mark the current node as visited and print the node.
  • Traverse all the adjacent and unmarked nodes and call the recursive function with the index of the adjacent node.
    Below is the implementation of the above approach:
#include <bits/stdc++.h>
using namespace std;
 
// Graph class represents a directed graph
// using adjacency list representation
class Graph {
public:
    map<int, bool> visited;
    map<int, list<int> > adj;
 
    // function to add an edge to graph
    void addEdge(int v, int w);
 
    // DFS traversal of the vertices
    // reachable from v
    void DFS(int v);
};
 
void Graph::addEdge(int v, int w)
{
    adj[v].push_back(w); // Add w to v’s list.
}
 
void Graph::DFS(int v)
{
    // Mark the current node as visited and
    // print it
    visited[v] = true;
    cout << v << " ";
 
    // Recur for all the vertices adjacent
    // to this vertex
    list<int>::iterator i;
    for (i = adj[v].begin(); i != adj[v].end(); ++i)
        if (!visited[*i])
            DFS(*i);
}
 
// Driver's code
int main()
{
    // Create a graph given in the above diagram
    Graph g;
    g.addEdge(0, 1);
    g.addEdge(0, 2);
    g.addEdge(1, 2);
    g.addEdge(2, 0);
    g.addEdge(2, 3);
    g.addEdge(3, 3);
 
    cout << "Following is Depth First Traversal"
            " (starting from vertex 2) \n";
 
    // Function call
    g.DFS(2);
 
    return 0;
}

Output

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

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

Auxiliary Space: O(V), since an extra visited array of size V is required.