Is Graph Bipartite (Leetcode 785) Solution - Coding Interview Question

Mani
Mani
Educating everyone with the beauty of programming!!

There is an undirected graph with n nodes, where each node is numbered between 0 and n - 1. You are given a 2D array graph, where graph[u] is an array of nodes that node u is adjacent to. More formally, for each v in graph[u], there is an undirected edge between node u and node v. The graph has the following properties:

  • There are no self-edges (graph[u] does not contain u).
  • There are no parallel edges (graph[u] does not contain duplicate values).
  • If v is in graph[u], then u is in graph[v] (the graph is undirected).
  • The graph may not be connected, meaning there may be two nodes u and v such that there is no path between them.

A graph is bipartite if the nodes can be partitioned into two independent sets A and B such that every edge in the graph connects a node in set A and a node in set B.

Return true if and only if it is bipartite.

 

Example 1:

Input: graph = [[1,2,3],[0,2],[0,1,3],[0,2]]
Output: false
Explanation: There is no way to partition the nodes into two independent sets such that every edge connects a node in one and a node in the other.

Example 2:

Input: graph = [[1,3],[0,2],[1,3],[0,2]]
Output: true
Explanation: We can partition the nodes into two sets: {0, 2} and {1, 3}.

 

Constraints:

  • graph.length == n
  • 1 <= n <= 100
  • 0 <= graph[u].length < n
  • 0 <= graph[u][i] <= n - 1
  • graph[u] does not contain u.
  • All the values of graph[u] are unique.
  • If graph[u] contains v, then graph[v] contains u.

Solution:

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
/**
 * Intuition: Each node is seperated into two different parties (0, 1). We do a dfs to distinguish the parties.
 * If at any moment, we find the party of two adjacent nodes is same, it means we can't divide the graph
 * into two different parties. Since there could be interdepency.
 * <p>
 * So we do a DFS + Party Map.
 * Time Complexity: O(N+E) : N is the number of nodes in graph, E is the number of edges
 * Space Complexity: O(N)
 **/
class Solution {
    public boolean isBipartite(int[][] graph) {
        Set<Integer> visited = new HashSet<>();
        for (int i = 0; i < graph.length; i++) {
            dfs(graph, i, visited, new HashMap<>());
            if (!res) {
                return res;
            }
        }
        return true;
    }

    boolean res = true;

    void dfs(int[][] graph, int i, Set<Integer> visited, Map<Integer, Integer> party) {
        if (visited.contains(i)) {
            return;
        }

        visited.add(i);

        for (int j = 0; j < graph[i].length; j++) {
            int x = i;
            int y = graph[i][j];

            Integer a = party.get(x);
            Integer b = party.get(y);
            if (a == null && b == null) {
                party.put(x, 0);
                party.put(y, 1);
            } else if (a == null && b != null) {
                party.put(x, (b + 1) % 2);
            } else if (a != null && b == null) {
                party.put(y, (a + 1) % 2);
            } else if (a != null && b != null) {
                if (a.equals(b)) {
                    res = false;
                    return;
                }
            }

            dfs(graph, y, visited, party);
        }
    }

}
Drop your comments below for any questions or comments. For full list of must learn top interview questions Click Here: Must Learn Top Interview Questions

Rating: