Given a directed graph containing **N** vertices and **M** edges, the task is to find all the dependencies of each vertex in the graph and the vertex with the minimum dependency.

A directed graph (or digraph) is a set of nodes connected by edges, where the edges have a direction associated with them.

For example, an arc (x, y) is considered to be directed from x to y, and the arc (y, x) is the inverted link. Y is a direct successor of x, and x is a direct predecessor of y.

The dependency is the number of connections to different vertices which are dependent on the current vertex.

**Examples:**

Output:

Vertex 1 dependencies -> 2-> 3

Vertex 2 dependencies -> 3-> 1

Vertex 3 dependencies -> 1-> 2

Node 1 has the minimum number of dependency of 2.Explanation:

Vertex 1 is dependent on 2 and 3.

Similarly, vertex 2 and 3 on (3, 1) and (1, 2) respectively.

Therefore, the minimum number of dependency among all vertices is 2.

Output:

Vertex 1 dependency -> 2-> 3-> 4-> 5-> 6

Vertex 2 dependency -> 6

Vertex 3 dependency -> 4-> 5-> 6

Vertex 4 dependency -> 5-> 6

Vertex 5 dependency -> 6

Vertex 6 is not dependent on any vertex.

Node 6 has the minimum dependency of 0Explanation:

Vertex 1 is dependent on (3, 4, 5, 6, 7). Similarly, vertex 2 on (6), vertex 3 on (4, 5, 6), vertex 4 on (5, 6), vertex 5 on (6) and vertex 6 is not dependent on any.

Therefore, the minimum number of dependency among all vertices is 0.

**Approach:** The idea is to use depth-first search(DFS) to solve this problem.

- Get the directed graph as the input.
- Perform the DFS on the graph and explore all the nodes of the graph.
- While exploring the neighbours of the node, add 1 to count and finally return the count which signifies the number of dependencies.
- Finally, find the node with the minimum number of dependencies.

Below is the implementation of the above approach:

`// C++ program to find the ` `// dependency of each node ` ` ` `#include <bits/stdc++.h> ` `using` `namespace` `std; `
` ` `// Defining the graph ` `class` `Graph { `
` ` ` ` `// Variable to store the `
` ` `// number of vertices `
` ` `int` `V; `
` ` ` ` `// Adjacency list `
` ` `list<` `int` `>* adjList; `
` ` ` ` `// Initializing the graph `
`public` `: `
` ` `Graph(` `int` `v) `
` ` `{ `
` ` `V = v; `
` ` `adjList = ` `new` `list<` `int` `>[V]; `
` ` `} `
` ` ` ` `// Adding edges `
` ` `void` `addEdge(` `int` `u, ` `int` `v, `
` ` `bool` `bidir = ` `true` `) `
` ` `{ `
` ` `adjList[u].push_back(v); `
` ` `if` `(bidir) { `
` ` `adjList[u].push_back(v); `
` ` `} `
` ` `} `
` ` ` ` `// Performing DFS on each node `
` ` `int` `dfs(` `int` `src) `
` ` `{ `
` ` `// Map is used to mark `
` ` `// the current node as visited `
` ` `map<` `int` `, ` `bool` `> visited; `
` ` `vector<` `int` `> dependent; `
` ` `int` `count = 0; `
` ` ` ` `stack<` `int` `> s; `
` ` ` ` `// Push the current vertex `
` ` `// to the stack which `
` ` `// stores the result `
` ` `s.push(src); `
` ` ` ` `visited[src] = ` `true` `; `
` ` ` ` `// Traverse through the vertices `
` ` `// until the stack is empty `
` ` `while` `(!s.empty()) { `
` ` `int` `n = s.top(); `
` ` `s.pop(); `
` ` ` ` `// Recur for all the vertices `
` ` `// adjacent to this vertex `
` ` `for` `(` `auto` `i : adjList[n]) { `
` ` ` ` `// If the vertices are `
` ` `// not visited `
` ` `if` `(!visited[i]) { `
` ` `dependent.push_back(i + 1); `
` ` `count++; `
` ` ` ` `// Mark the vertex as `
` ` `// visited `
` ` `visited[i] = ` `true` `; `
` ` ` ` `// Push the current vertex to `
` ` `// the stack which stores `
` ` `// the result `
` ` `s.push(i); `
` ` `} `
` ` `} `
` ` `} `
` ` ` ` `// If the vertex has 0 dependency `
` ` `if` `(!count) { `
` ` `cout << ` `"Vertex "` `<< src + 1 `
` ` `<< ` `" is not dependent on any vertex.\n"` `; `
` ` `return` `count; `
` ` `} `
` ` ` ` `cout << ` `"Vertex "` `<< src + 1 << ` `" dependency "` `; `
` ` `for` `(` `auto` `i : dependent) { `
` ` `cout << ` `"-> "` `<< i; `
` ` `} `
` ` `cout << ` `"\n"` `; `
` ` `return` `count; `
` ` `} `
`}; ` ` ` `// Function to find the ` `// dependency of each node ` `void` `operations(` `int` `arr[][2], `
` ` `int` `n, ` `int` `m) `
`{ ` ` ` `// Creating a new graph `
` ` `Graph g(n); `
` ` ` ` `for` `(` `int` `i = 0; i < m; i++) { `
` ` `g.addEdge(arr[i][0], `
` ` `arr[i][1], ` `false` `); `
` ` `} `
` ` ` ` `int` `ans = INT_MAX; `
` ` `int` `node = 0; `
` ` ` ` `// Iterating through the graph `
` ` `for` `(` `int` `i = 0; i < n; i++) { `
` ` `int` `c = g.dfs(i); `
` ` ` ` `// Finding the node with `
` ` `// minimum number of `
` ` `// dependency `
` ` `if` `(c < ans) { `
` ` `ans = c; `
` ` `node = i + 1; `
` ` `} `
` ` `} `
` ` `cout << ` `"Node "` `<< node `
` ` `<< ` `"has minimum dependency of "`
` ` `<< ans; `
`} ` ` ` `// Driver code ` `int` `main() `
`{ ` ` ` `int` `n, m; `
` ` ` ` `n = 6, m = 6; `
` ` ` ` `// Defining the edges of the `
` ` `// graph `
` ` `int` `arr[][2] = { { 0, 1 }, `
` ` `{ 0, 2 }, `
` ` `{ 2, 3 }, `
` ` `{ 4, 5 }, `
` ` `{ 3, 4 }, `
` ` `{ 1, 5 } }; `
` ` ` ` `operations(arr, n, m); `
` ` ` ` `return` `0; `
`} ` |

*chevron_right*

*filter_none*

**Output:**

Vertex 1 dependency -> 2-> 3-> 4-> 5-> 6 Vertex 2 dependency -> 6 Vertex 3 dependency -> 4-> 5-> 6 Vertex 4 dependency -> 5-> 6 Vertex 5 dependency -> 6 Vertex 6 is not dependent on any vertex. Node 6has minimum dependency of 0

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