Given a Binary Tree, convert it to a Binary Search Tree. The conversion must be done in such a way that keeps the original structure of Binary Tree.
This solution will use Sets of C++ STL instead of array based solution.
Example 1 Input: 10 / 2 7 / 8 4 Output: 8 / 4 10 / 2 7 Example 2 Input: 10 / 30 15 / 20 5 Output: 15 / 10 20 / 5 30
- Copy the items of binary tree in a set while doing inorder traversal. This takes O(n log n) time. Note that set in C++ STL is implemented using a Self Balancing Binary Search Tree like Red Black Tree, AVL Tree, etc
- There is no need to sort the set as sets in C++ are implemented using Self-balancing binary search trees due to which each operation such as insertion, searching, deletion etc takes O(log n) time.
- Now simply copy the items of set one by one from beginning to the tree while doing inorder traversal of tree. Care should be taken as when copying each item of set from its beginning, we first copy it to the tree while doing inorder traversal, then remove it from the set as well.
Now the above solution is simpler and easier to implement than the array based conversion of Binary tree to Binary search tree explained here- Conversion of Binary Tree to Binary Search tree (Set-1), where we had to separately make a function to sort the items of the array after copying the items from tree to it.
Program to convert a binary tree to binary search tree using set.
# Python3 program to convert a Binary tree
# to BST using sets as containers.
# Binary Tree Node
“”” A utility function to create a
new BST node “””
# Construct to create a newNode
def __init__(self, data):
self.data = data
self.left = None
self.right = None
# function to store the nodes in set
# while doing inorder traversal.
def storeinorderInSet(root, s):
if (not root) :
# visit the left subtree first
# insertion takes order of O(logn)
# for sets
# visit the right subtree
# Time complexity = O(nlogn)
# function to copy items of set one by one
# to the tree while doing inorder traversal
def setToBST(s, root) :
# base condition
if (not root):
# first move to the left subtree and
# update items
# iterator initially pointing to
# the beginning of set
it = next(iter(s))
# copying the item at beginning of
# set(sorted) to the tree.
root.data = it
# now erasing the beginning item from set.
# now move to right subtree
# and update items
# T(n) = O(nlogn) time
# Converts Binary tree to BST.
s = set()
# populating the set with the tree’s
# inorder traversal data
# now sets are by default sorted as
# they are implemented using self-
# balancing BST
# copying items from set to the tree
# while inorder traversal which makes a BST
# Time complexity = O(nlogn),
# Auxiliary Space = O(n) for set.
# function to do inorder traversal
def inorder(root) :
if (not root) :
print(root.data, end = ” “)
# Driver Code
if __name__ == ‘__main__’:
root = newNode(5)
root.left = newNode(7)
root.right = newNode(9)
root.right.left = newNode(10)
root.left.left = newNode(1)
root.left.right = newNode(6)
root.right.right = newNode(11)
“”” Constructing tree given in
the above figure
1 6 10 11 “””
# converting the above Binary tree to BST
print(“Inorder traversal of BST is: “)
# This code is contributed by
# Shubham Singh(SHUBHAMSINGH10)
Inorder traversal of BST is: 1 5 6 7 9 10 11
Time Complexity: O(n Log n)
Auxiliary Space: (n)