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126 changes: 126 additions & 0 deletions Code/C++/Morris_inorder_traversal
Original file line number Diff line number Diff line change
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/*
Morris Inorder Tree Traversal algorithm provides an efficient way to traverse
a binary tree without using extra memory space like stack, and without using
recursion.That means it's space complexity is constant i.e. O(1).

STEPS INVOLVED IN IMPLEMENTATION
1. Find the inorder predecessor of the node before going to it's left sub-tree.
2. Connect that predecessor to the node, so that we have a path to come back to the node. Connect node to the right of the predecessor.
3. To find predecessor, goto the left node of the current node and find the right-most node of it.
4. After traversing the left sub-tree, remove that connection and leave the tree as it was.

EXAMPLE

10
/ \
5 20
/ \ \
-2 6 21
\
3
/
1

In the above given example, the connections in red color are the predecessor's connection.

*/
#include <bits/stdc++.h>
using namespace std;

struct Node {
int data;
Node* left, *right;
Node(int value)
{
data=value;
left=NULL;
right=NULL;
}
};

void MorrisTraversal(struct Node* root)
{
if (root == NULL)
return;

struct Node *current=NULL, *previous=NULL;
current = root;

while (current != NULL) {

if (current->left != NULL)
{
previous = current->left;

while (previous->right != NULL && previous->right != current)
previous = previous->right;

if (previous->right != NULL)
{
cout<<current->data<<" ";
current = current->right;
previous->right = NULL;
}
else
{
previous->right = current;
current = current->left;
}
}
else
{
cout<<current->data<<" ";
current = current->right;
}
}
}

int main()
{
struct Node* root = new Node(1);
root->left = new Node(2);
root->right = new Node(3);
root->left->left = new Node(4);
root->left->right = new Node(5);

MorrisTraversal(root);

return 0;
}

/*
Test Case 1:

6
\
10
\
20
\
30

Output:
6 10 20 30

Test Case 2:

12
/ \
7 20
/ \ \
-2 9 25
\
3
/
2
/
1

Output:
-2 1 2 3 7 9 12 20 25

COMPLEXITIES:
time complexity : O(n) ; n is number of nodes in a tree
space complexity:O(n) ; n is number of nodes in a tree

*/