# Posts published in “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)

## Python3

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 = 
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)

## Python3

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++

You have n binary tree nodes numbered from 0 to n - 1 where node i has two children leftChild[i] and rightChild[i], return true if and only if all the given nodes form exactly one valid binary tree.

If node i has no left child then leftChild[i] will equal -1, similarly for the right child.

Note that the nodes have no values and that we only use the node numbers in this problem.

Example 1:

Input: n = 4, leftChild = [1,-1,3,-1], rightChild = [2,-1,-1,-1]
Output: true


Example 2:

Input: n = 4, leftChild = [1,-1,3,-1], rightChild = [2,3,-1,-1]
Output: false


Example 3:

Input: n = 2, leftChild = [1,0], rightChild = [-1,-1]
Output: false


Example 4:

Input: n = 6, leftChild = [1,-1,-1,4,-1,-1], rightChild = [2,-1,-1,5,-1,-1]
Output: false


Constraints:

• 1 <= n <= 10^4
• leftChild.length == rightChild.length == n
• -1 <= leftChild[i], rightChild[i] <= n - 1

## Solution: Count in-degrees for each node

in degree must <= 1 and there must be exact one node that has 0 in-degree.

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

## C++

Given an array where elements are sorted in ascending order, convert it to a height balanced BST.

For this problem, a height-balanced binary tree is defined as a binary tree in which the depth of the two subtrees of every node never differ by more than 1.

Example:

Given the sorted array: [-10,-3,0,5,9],

One possible answer is: [0,-3,9,-10,null,5], which represents the following height balanced BST:

0
/ \
-3   9
/   /
-10  5

## Solution: Recursion

Recursively build a BST for a given range.

def build(nums, l, r):
if l > r: return None
m = l + (r – l) / 2
root = TreeNode(nums[m])
root.left = build(nums, l, m – 1)
root.right = build(nums, m + 1, r)
return root

return build(nums, 0, len(nums) – 1)

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

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