Lowest Common Ancestor in Parent Array Representation

Given a binary tree represented as parent array, find Lowest Common Ancestor between two nodes ‘m’ and ‘n’.

In the above diagram, LCA of 10 and 14 is 12 and LCA of 10 and 12 is 12.

(1) Make a parent array and store the parent of ith node in it. Parent of root node should be -1.
(2) Now, access all the nodes from the desired node ‘m’ till root node and mark them visited.
(3) Lastly, access all the nodes from the desired node ‘n’ till first visited node comes.
(4) This node is the lowest common ancestor

C++

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// CPP program to find LCA in a tree represented
// as parent array.
#include <bits/stdc++.h>
using namespace std;
  
// Maximum value in a node
const int MAX = 1000;
  
// Function to find the Lowest common ancestor
int findLCA(int n1, int n2, int parent[])
{
    // Create a visited vector and mark
    // all nodes as not visited.
    vector<bool> visited(MAX, false);
  
    visited[n1] = true;
  
    // Moving from n1 node till root and
    // mark every accessed node as visited
    while (parent[n1] != -1) {
        visited[n1] = true;
  
        // Move to the parent of node n1
        n1 = parent[n1];
    }
  
    visited[n1] = true;
  
    // For second node finding the first
    // node common
    while (!visited[n2])
        n2 = parent[n2];
  
    return n2;
}
  
// Insert function for Binary tree
void insertAdj(int parent[], int i, int j)
{
    parent[i] = j;
}
  
// Driver Functiom
int main()
{
    // Maximum capacity of binary tree
    int parent[MAX];
  
    // Root marked
    parent[20] = -1;
    insertAdj(parent, 8, 20);
    insertAdj(parent, 22, 20);
    insertAdj(parent, 4, 8);
    insertAdj(parent, 12, 8);
    insertAdj(parent, 10, 12);
    insertAdj(parent, 14, 12);
  
    cout << findLCA(10, 14, parent);
  
    return 0;
}

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Java














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// Java program to find LCA in a tree represented 


// as parent array. 


import java.util.*; 


  


class GFG  


{ 


  


// Maximum value in a node 


static int MAX = 1000; 


  


// Function to find the Lowest common ancestor 


static int findLCA(int n1, int n2, int parent[]) 


{ 


    // Create a visited vector and mark 


    // all nodes as not visited. 


    boolean []visited = new boolean[MAX]; 


  


    visited[n1] = true; 


  


    // Moving from n1 node till root and 


    // mark every accessed node as visited 


    while (parent[n1] != -1) 


    { 


        visited[n1] = true; 


  


        // Move to the parent of node n1 


        n1 = parent[n1]; 


    } 


  


    visited[n1] = true; 


  


    // For second node finding the first 


    // node common 


    while (!visited[n2]) 


        n2 = parent[n2]; 


  


    return n2; 


} 


  


// Insert function for Binary tree 


static void insertAdj(int parent[], int i, int j) 


{ 


    parent[i] = j; 


} 


  


// Driver Functiom 


public static void main(String[] args) 


{ 


    // Maximum capacity of binary tree 


    int []parent = new int[MAX]; 


  


    // Root marked 


    parent[20] = -1; 


    insertAdj(parent, 8, 20); 


    insertAdj(parent, 22, 20); 


    insertAdj(parent, 4, 8); 


    insertAdj(parent, 12, 8); 


    insertAdj(parent, 10, 12); 


    insertAdj(parent, 14, 12); 


  


    System.out.println(findLCA(10, 14, parent)); 


} 


} 


  


// This code is contributed by 29AjayKumar 



















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Python3














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# Python 3 program to find LCA in a  


# tree represented as parent array. 


  


# Maximum value in a node 


MAX = 1000


  


# Function to find the Lowest  


# common ancestor 


def findLCA(n1, n2, parent): 


      


    # Create a visited vector and mark 


    # all nodes as not visited. 


    visited = [False for i in range(MAX)] 


  


    visited[n1] = True


  


    # Moving from n1 node till root and 


    # mark every accessed node as visited 


    while (parent[n1] != -1): 


        visited[n1] = True


  


        # Move to the parent of node n1 


        n1 = parent[n1] 


  


    visited[n1] = True


  


    # For second node finding the  


    # first node common 


    while (visited[n2] == False): 


        n2 = parent[n2] 


  


    return n2 


  


# Insert function for Binary tree 


def insertAdj(parent, i, j): 


    parent[i] = j 


  


# Driver Code 


if __name__ =='__main__': 


      


    # Maximum capacity of binary tree 


    parent = [0 for i in range(MAX)] 


  


    # Root marked 


    parent[20] = -1


    insertAdj(parent, 8, 20) 


    insertAdj(parent, 22, 20) 


    insertAdj(parent, 4, 8) 


    insertAdj(parent, 12, 8) 


    insertAdj(parent, 10, 12) 


    insertAdj(parent, 14, 12) 


  


    print(findLCA(10, 14, parent)) 


      


# This code is contributed by 


# Surendra_Gangwar 



















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C#





// C# program to find LCA in a tree represented

// as parent array.

using System;


class GFG

{


// Maximum value in a node

static int MAX = 1000;


// Function to find the Lowest common ancestor

static int findLCA(int n1, int n2, int []parent)

{

	// Create a visited vector and mark

	// all nodes as not visited.

	Boolean []visited = new Boolean[MAX];


	visited[n1] = true;


	// Moving from n1 node till root and

	// mark every accessed node as visited

	while (parent[n1] != -1)

	{

		visited[n1] = true;


		// Move to the parent of node n1

		n1 = parent[n1];

	}


	visited[n1] = true;


	// For second node finding the first

	// node common

	while (!visited[n2])

		n2 = parent[n2];


	return n2;

}


// Insert function for Binary tree

static void insertAdj(int []parent, int i, int j)

{

	parent[i] = j;

}


// Driver Code

public static void Main(String[] args)

{

	// Maximum capacity of binary tree

	int []parent = new int[MAX];


	// Root marked

	parent[20] = -1;

	insertAdj(parent, 8, 20);

	insertAdj(parent, 22, 20);

	insertAdj(parent, 4, 8);

	insertAdj(parent, 12, 8);

	insertAdj(parent, 10, 12);

	insertAdj(parent, 14, 12);


	Console.WriteLine(findLCA(10, 14, parent));

}

}


// This code is contributed by 29AjayKumar





Output:


12





Time Complexity – The time complexity of the above algorithm is O(log n) as it requires O(log n) time in searching.



          
          
          
          

            

    

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    Article Tags : 
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Practice Tags : 
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