Find all Critical Connections in the Graph

Last Updated : 23 Jul, 2025

Given an undirected Connected graph of V vertices and E edges. A critical connection is an edge that, if removed, will make some nodes unable to reach some other nodes, the task is to find all critical connections in the graph.

Note: There are many possible orders for the answer. You are supposed to print the edges in sorted order, and also an edge should be in sorted order too. So if there's an edge between nodes 1 and 2, you should print it like (1,2) and not (2,1).

Examples:

Input:

Output: 0 1 0 2 Explanation: Both the edges in the graph are Crtical connections.

Input:

Output: 2 3 Explanation: The edge between nodes 2 and 3 is the only Critical connection in the given graph.

Approach: To solve the problem follow the below idea:

An edge is a critical connection, if and only if it is not in a cycle.
So, if we know how to find cycles, and discard all edges in the cycles, then the remaining connections are a complete collection of critical connections.

Follow the steps to solve the problem:

Use DFS algorithm to decide whether an edge is in a cycle or not.
Assign a rank or depth to each node while traversing using the dfs. As we keep moving into the depth in the dfs, if some how we jump to node which has lower depth and already visited this means a cycle is found and the edges present in this cycle is not critical connections.
But only the current level of search knows it finds a cycle. How does the upper level of search knows, if you backtrack?
- Let's make use of the return value of DFS: dfs function returns the minimum rank it finds. During a step of search from node u to its neighbor v, if dfs(v) returns something smaller than or equal to rank(u), then u knows its neighbor v helped it to find a cycle back to u or u's ancestor. So u knows it should discard the edge (u, v) which is in a cycle.

Below is the Implementation of the above approach:

C++

// C++ code for the above approach:
#include <bits/stdc++.h>
using namespace std;
int dfs(int i, int p, vector<int>& rank, int k,
        vector<int> adj[], vector<vector<int> >& ans,
        vector<int>& vis)
{

    // Set rank of the ith node to k
    // which is depth
    rank[i] = k;

    // Mark ith node as visited
    vis[i] = 1;

    int minDepth = INT_MAX;

    // Exploring all the neighbour
    // node of node i
    for (auto ch : adj[i]) {

        // This if condition is to make
        // sure we do not call parent
        // from where it is called to
        // avoid child parent loop
        if (ch != p) {

            // If neighbour is already
            // visited then we take
            // minimum with rank of ch,
            // means a cycle is found
            if (vis[ch]) {
                minDepth = min(minDepth, rank[ch]);
            }

            // If neighbour is not
            // visited then we go in
            // depth to check cycle
            // is present or not
            else {
                int minRank = dfs(ch, i, rank, k + 1, adj,
                                  ans, vis);

                // If dfs returns smaller
                // depth value than current
                // depth it means current
                // edge is in a cycle
                // else there is no cycle
                // so we have pushed the
                // edge in our answer
                if (rank[i] < minRank) {
                    ans.push_back({ i, ch });
                }
                minDepth = min(minRank, minDepth);
            }
        }
    }
    return minDepth;
}

// Function to calculate
// the critical edges
vector<vector<int> > criticalConnections(int V,
                                         vector<int> adj[])
{
    vector<vector<int> > ans;
    vector<int> rank(V, -1), vis(V, 0);
    dfs(0, -1, rank, 0, adj, ans, vis);
    for (int i = 0; i < ans.size(); i++) {
        sort(ans[i].begin(), ans[i].end());
    }
    sort(ans.begin(), ans.end());
    return ans;
}

// Drivers code
int main()
{
    int v = 3, e = 2;
    vector<vector<int> > edges = { { 0, 1 }, { 0, 2 } };
    vector<int> adj[v];
    for (int i = 0; i < e; i++) {
        adj[edges[i][0]].push_back(edges[i][1]);
        adj[edges[i][1]].push_back(edges[i][0]);
    }
    vector<vector<int> > ans = criticalConnections(v, adj);
    sort(ans.begin(), ans.end());
    for (int i = 0; i < ans.size(); i++) {
        cout << ans[i][0] << " " << ans[i][1] << endl;
    }
    return 0;
}

Java

import java.util.*;

public class Main {
    // Function to find critical connections in a graph
    static List<List<Integer>> criticalConnections(int V, List<Integer>[] adj) {
        List<List<Integer>> ans = new ArrayList<>();
        int[] rank = new int[V];
        Arrays.fill(rank, -1);
        int[] vis = new int[V];
        dfs(0, -1, rank, 0, adj, ans, vis);

        // Sort each edge in ascending order of nodes
        for (List<Integer> edge : ans) {
            Collections.sort(edge);
        }

        // Sort the list of edges
        ans.sort((a, b) -> {
            if (a.get(0).equals(b.get(0))) {
                return a.get(1) - b.get(1);
            }
            return a.get(0) - b.get(0);
        });

        return ans;
    }

    // Depth-first search to find critical connections
    static int dfs(int i, int p, 
                   int[] rank, 
                   int k, 
                   List<Integer>[] adj, 
                   List<List<Integer>> ans, 
                   int[] vis) {
        rank[i] = k;
        vis[i] = 1;
        int minDepth = Integer.MAX_VALUE;

        for (int ch : adj[i]) {
            if (ch != p) {
                if (vis[ch] == 1) {
                    minDepth = Math.min(minDepth, rank[ch]);
                } else {
                    int minRank = dfs(ch, i, rank, k + 1, adj, ans, vis);

                    if (rank[i] < minRank) {
                        List<Integer> edge = new ArrayList<>();
                        edge.add(i);
                        edge.add(ch);
                        ans.add(edge);
                    }

                    minDepth = Math.min(minRank, minDepth);
                }
            }
        }
        return minDepth;
    }

    public static void main(String[] args) {
        int V = 3;
        List<Integer>[] adj = new ArrayList[V];
        for (int i = 0; i < V; i++) {
            adj[i] = new ArrayList<>();
        }

        List<List<Integer>> edges = new ArrayList<>();
        edges.add(Arrays.asList(0, 1));
        edges.add(Arrays.asList(0, 2));

        for (List<Integer> edge : edges) {
            adj[edge.get(0)].add(edge.get(1));
            adj[edge.get(1)].add(edge.get(0));
        }

        List<List<Integer>> ans = criticalConnections(V, adj);

        // Print the critical connections
        for (List<Integer> edge : ans) {
            System.out.println(edge.get(0) + " " + edge.get(1));
        }
    }
}

Python3

# Python code for the above approach:
def dfs(i, p, rank, k, adj, ans, vis):

    # Set rank of the ith node to k
    # which is depth
    rank[i] = k

    # Mark ith node as visited
    vis[i] = 1

    minDepth = float('inf')

    # Exploring all the neighbour
    # node of node i
    for ch in adj[i]:

        # This if condition is to make
        # sure we do not call parent
        # from where it is called to
        # avoid child parent loop
        if ch != p:

            # If neighbour is already
            # visited then we take
            # minimum with rank of ch,
            # means a cycle is found
            if vis[ch]:
                minDepth = min(minDepth, rank[ch])

            # If neighbour is not
            # visited then we go in
            # depth to check cycle
            # is present or not
            else:
                minRank = dfs(ch, i, rank, k + 1, adj,
                              ans, vis)

                # If dfs returns smaller
                # depth value than current
                # depth it means current
                # edge is in a cycle
                # else there is no cycle
                # so we have pushed the
                # edge in our answer
                if rank[i] < minRank:
                    ans.append([i, ch])
                minDepth = min(minRank, minDepth)
    return minDepth

# Function to calculate
# the critical edges


def criticalConnections(V, adj):
    ans = []
    rank = [-1] * V
    vis = [0] * V
    dfs(0, -1, rank, 0, adj, ans, vis)
    for i in range(len(ans)):
        ans[i].sort()
    ans.sort()
    return ans


# Drivers code
v = 3
e = 2
edges = [[0, 1], [0, 2]]
adj = [[] for _ in range(v)]
for i in range(e):
    adj[edges[i][0]].append(edges[i][1])
    adj[edges[i][1]].append(edges[i][0])
ans = criticalConnections(v, adj)
ans.sort()
for i in range(len(ans)):
    print(ans[i][0], ans[i][1])

# This code is contributed by Tapesh(tapeshdua420)

using System;
using System.Collections.Generic;

class MainClass {
    // Function to find critical connections in a graph
    static List<List<int>> CriticalConnections(int V, List<int>[] adj) {
        List<List<int>> ans = new List<List<int>>();
        int[] rank = new int[V];
        for (int i = 0; i < V; i++) {
            rank[i] = -1;
        }
        int[] vis = new int[V];
        DFS(0, -1, rank, 0, adj, ans, vis);

        // Sort each edge in ascending order of nodes
        foreach (var edge in ans) {
            edge.Sort();
        }

        // Sort the list of edges
        ans.Sort((a, b) => {
            if (a[0] == b[0]) {
                return a[1] - b[1];
            }
            return a[0] - b[0];
        });

        return ans;
    }

    // Depth-first search to find critical connections
    static int DFS(int i, int p, int[] rank, int k, List<int>[] adj, List<List<int>> ans, int[] vis) {
        rank[i] = k;
        vis[i] = 1;
        int minDepth = int.MaxValue;

        foreach (var ch in adj[i]) {
            if (ch != p) {
                if (vis[ch] == 1) {
                    minDepth = Math.Min(minDepth, rank[ch]);
                } else {
                    int minRank = DFS(ch, i, rank, k + 1, adj, ans, vis);

                    if (rank[i] < minRank) {
                        List<int> edge = new List<int> { i, ch };
                        ans.Add(edge);
                    }

                    minDepth = Math.Min(minRank, minDepth);
                }
            }
        }
        return minDepth;
    }

    public static void Main(string[] args) {
        int V = 3;
        List<int>[] adj = new List<int>[V];
        for (int i = 0; i < V; i++) {
            adj[i] = new List<int>();
        }

        List<List<int>> edges = new List<List<int>> {
            new List<int> {

JavaScript

function criticalConnections(V, adj) {
    const ans = [];
    const rank = new Array(V).fill(-1);
    const vis = new Array(V).fill(0);

    // Depth-first search to find critical connections
    function dfs(i, p, k) {
        rank[i] = k;
        vis[i] = 1;
        let minDepth = Infinity;

        for (const ch of adj[i]) {
            if (ch !== p) {
                if (vis[ch] === 1) {
                    minDepth = Math.min(minDepth, rank[ch]);
                } else {
                    const minRank = dfs(ch, i, k + 1);

                    if (rank[i] < minRank) {
                        ans.push([i, ch]);
                    }

                    minDepth = Math.min(minRank, minDepth);
                }
            }
        }
        return minDepth;
    }

    dfs(0, -1, 0);

    // Sort each edge in ascending order of nodes
    ans.forEach(edge => {
        edge.sort((a, b) => a - b);
    });

    // Sort the list of edges
    ans.sort((a, b) => {
        if (a[0] === b[0]) {
            return a[1] - b[1];
        }
        return a[0] - b[0];
    });

    return ans;
}

const V = 3;
const adj = new Array(V).fill().map(() => []);

const edges = [[0, 1], [0, 2]];

edges.forEach(edge => {
    adj[edge[0]].push(edge[1]);
    adj[edge[1]].push(edge[0]);
});

const ans = criticalConnections(V, adj);

// Print the critical connections
ans.forEach(edge => {
    console.log(edge[0], edge[1]);
});

Output

0 1
0 2

Time Complexity: O(V) + ElogE
Auxiliary Space : O(V)

Analysis of Algorithms

hem_kishan_gfg

Improve

Article Tags :

Practice Tags :

Find all Critical Connections in the Graph

Similar Reads

Basics & Prerequisites

Data Structures

Algorithms

Advanced

Interview Preparation

Practice Problem

Thank You!

What kind of Experience do you want to share?