Inorder Successor In BST
In this page, we will solve the problem of determining the inorder successor of given element in BST.
Problem Description​
Given a BST, and a reference to a Node x in the BST. Find the Inorder Successor of the given node in the BST.
Examples​
Example 1:
Input:
2
/ \
1 3
K(data of x) = 2
Output: 3
Explanation:
Inorder traversal : 1 2 3
Hence, inorder successor of 2 is 3.
Example 2:
Input:
20
/ \
8 22
/ \
4 12
/ \
10 14
K(data of x) = 8
Output: 10
Explanation:
Inorder traversal: 4 8 10 12 14 20 22
Hence, successor of 8 is 10.
Constraints​
- , where is number of nodes
Solution​
Intuition and Approach​
This problem can be solved by a simple approach of Inorder Traversal
- Inorder Traversal
Approach: Inorder Traversal​
- Initialize an empty list 'traversal' to store the nodes of the tree in inorder traversal.
- Then we define a helper function inorder_traversal to perform an inorder traversal of the tree and populate the traversal list. This function takes root as an argument. If root is None, it simply returns, indicating the base case of the recursion.
- Within the helper function inorder_traversal, we first recursively call inorder_traversal on the left child of the current node.
- We then append the current node to the traversal list.
- Next, we recursively call inorder_traversal function on the right child of the current node.
- After populating the traversal list, we iterate through the list to find the node whose value matches x.data. We do this using a for loop that iterate through the traversal list and find the successor of the element x by checking if the data of the current node (traversal[i].data) is equal to the data of the node x (x.data).
- If the condition is met, it means we have found the node x. The inorder successor of x is the next node in the ans list (traversal[i + 1]). We return this node as the result.
Code in Python​
class Solution:
# returns the inorder successor of the Node x in BST (rooted at 'root')
def inorderSuccessor(self, root, x):
# Code here
traversal_list=[]
def inorder_traversal(root):
if root is None:return
inorder_traversal(root.left)
traversal_list.append(root)
inorder_traversal(root.right)
inorder_traversal(root)
for i in range(len(traversal_list)-1):
if traversal_list[i].data==x.data:
return traversal_list[i+1]
return None
Complexity Analysis​
- Time Complexity:
- Space Complexity: