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Posts published in “Tree”

花花酱 LeetCode 1382. Balance a Binary Search Tree

Given a binary search tree, return a balanced binary search tree with the same node values.

A binary search tree is balanced if and only if the depth of the two subtrees of every node never differ by more than 1.

If there is more than one answer, return any of them.

Example 1:

Input: root = [1,null,2,null,3,null,4,null,null]
Output: [2,1,3,null,null,null,4]
Explanation: This is not the only correct answer, [3,1,4,null,2,null,null] is also correct.

Constraints:

  • The number of nodes in the tree is between 1 and 10^4.
  • The tree nodes will have distinct values between 1 and 10^5.

Solution: Inorder + recursion

Use inorder traversal to collect a sorted array from BST. And then build a balanced BST from this sorted array in O(n) time.

Time complexity: O(n)
Space complexity: O(n)

C++

花花酱 LeetCode 1379. Find a Corresponding Node of a Binary Tree in a Clone of That Tree

Given two binary trees original and cloned and given a reference to a node target in the original tree.

The cloned tree is a copy of the original tree.

Return a reference to the same node in the cloned tree.

Note that you are not allowed to change any of the two trees or the target node and the answer must be a reference to a node in the cloned tree.

Follow up: Solve the problem if repeated values on the tree are allowed.

Example 1:

Input: tree = [7,4,3,null,null,6,19], target = 3
Output: 3
Explanation: In all examples the original and cloned trees are shown. The target node is a green node from the original tree. The answer is the yellow node from the cloned tree.

Example 2:

Input: tree = [7], target =  7
Output: 7

Example 3:

Input: tree = [8,null,6,null,5,null,4,null,3,null,2,null,1], target = 4
Output: 4

Example 4:

Input: tree = [1,2,3,4,5,6,7,8,9,10], target = 5
Output: 5

Example 5:

Input: tree = [1,2,null,3], target = 2
Output: 2

Constraints:

  • The number of nodes in the tree is in the range [1, 10^4].
  • The values of the nodes of the tree are unique.
  • target node is a node from the original tree and is not null.

Solution: Recursion

Traverse both trees in the same order, if original == target, return cloned.

Time complexity: O(n)
Space complexity: O(h)

C++

Python3

花花酱 LeetCode 1373. Maximum Sum BST in Binary Tree

Given a binary tree root, the task is to return the maximum sum of all keys of any sub-tree which is also a Binary Search Tree (BST).

Assume a BST is defined as follows:

  • The left subtree of a node contains only nodes with keys less than the node’s key.
  • The right subtree of a node contains only nodes with keys greater than the node’s key.
  • Both the left and right subtrees must also be binary search trees.

Example 1:

Input: root = [1,4,3,2,4,2,5,null,null,null,null,null,null,4,6]
Output: 20
Explanation: Maximum sum in a valid Binary search tree is obtained in root node with key equal to 3.

Example 2:

Input: root = [4,3,null,1,2]
Output: 2
Explanation: Maximum sum in a valid Binary search tree is obtained in a single root node with key equal to 2.

Example 3:

Input: root = [-4,-2,-5]
Output: 0
Explanation: All values are negatives. Return an empty BST.

Example 4:

Input: root = [2,1,3]
Output: 6

Example 5:

Input: root = [5,4,8,3,null,6,3]
Output: 7

Constraints:

  • Each tree has at most 40000 nodes..
  • Each node’s value is between [-4 * 10^4 , 4 * 10^4].

Solution: Recursion

Time complexity: O(n)
Space complexity: O(h)

C++

Python3

花花酱 LeetCode 1372. Longest ZigZag Path in a Binary Tree

Given a binary tree root, a ZigZag path for a binary tree is defined as follow:

  • Choose any node in the binary tree and a direction (right or left).
  • If the current direction is right then move to the right child of the current node otherwise move to the left child.
  • Change the direction from right to left or right to left.
  • Repeat the second and third step until you can’t move in the tree.

Zigzag length is defined as the number of nodes visited – 1. (A single node has a length of 0).

Return the longest ZigZag path contained in that tree.

Example 1:

Input: root = [1,null,1,1,1,null,null,1,1,null,1,null,null,null,1,null,1]
Output: 3
Explanation: Longest ZigZag path in blue nodes (right -> left -> right).

Example 2:

Input: root = [1,1,1,null,1,null,null,1,1,null,1]
Output: 4
Explanation: Longest ZigZag path in blue nodes (left -> right -> left -> right).

Example 3:

Input: root = [1]
Output: 0

Constraints:

  • Each tree has at most 50000 nodes..
  • Each node’s value is between [1, 100].

Solution: Recursion

For each node return
1. max ZigZag length if go left
2. max ZigZag length if go right
3. maz ZigZag length within the subtree

ZigZag(root):
ll, lr, lm = ZigZag(root.left)
rl, rr, rm = ZigZag(root.right)
return (lr+1, rl + 1, max(lr+1, rl+1, lm, rm))

Time complexity: O(n)
Space complexity: O(h)

C++

Python3

花花酱 LeetCode 1367. Linked List in Binary Tree

Given a binary tree root and a linked list with head as the first node. 

Return True if all the elements in the linked list starting from the head correspond to some downward path connected in the binary tree otherwise return False.

In this context downward path means a path that starts at some node and goes downwards.

Example 1:

Input: head = [4,2,8], root = [1,4,4,null,2,2,null,1,null,6,8,null,null,null,null,1,3]
Output: true
Explanation: Nodes in blue form a subpath in the binary Tree.  

Example 2:

Input: head = [1,4,2,6], root = [1,4,4,null,2,2,null,1,null,6,8,null,null,null,null,1,3]
Output: true

Example 3:

Input: head = [1,4,2,6,8], root = [1,4,4,null,2,2,null,1,null,6,8,null,null,null,null,1,3]
Output: false
Explanation: There is no path in the binary tree that contains all the elements of the linked list from head.

Constraints:

  • 1 <= node.val <= 100 for each node in the linked list and binary tree.
  • The given linked list will contain between 1 and 100 nodes.
  • The given binary tree will contain between 1 and 2500 nodes.

Solution: Recursion

We need two recursion functions: isSubPath / isPath, the later one does a strict match.

Time complexity: O(|L| * |T|)
Space complexity: O(|T|)

C++