Is Closest Binary Search Tree Value easy or hard?

Closest Binary Search Tree Value is categorized as an Easy problem. The challenge mainly involves recognizing that the BST ordering enables a binary-search-style traversal rather than scanning the entire tree.

Closest Binary Search Tree Value Python/Java solution

Both Python and Java implementations follow the same logic: maintain a variable storing the closest value and traverse the BST toward the target. At each node, update the closest candidate and move left or right based on comparison with the target. The algorithm runs in O(h) time and O(1) or O(h) space depending on whether iteration or recursion is used.

How to solve Closest Binary Search Tree Value in O(n)?

An O(n) solution performs a full traversal of the binary tree using DFS or BFS and compares every node value with the target. Track the smallest absolute difference encountered during traversal. This approach works for any binary tree but does not take advantage of the BST ordering.

What is the best approach for Closest Binary Search Tree Value?

The best approach uses the Binary Search Tree property to guide the search. Starting from the root, track the value with the smallest absolute difference from the target and move left or right depending on whether the target is smaller or larger than the current node. This reduces the search to O(h) time where h is the tree height, which is O(log n) for balanced BSTs.

Is Closest Binary Search Tree Value asked at Google/Amazon/Meta?

Binary Search Tree search problems like Closest Binary Search Tree Value frequently appear in interviews at companies such as Amazon, Google, and Meta. Interviewers use it to test understanding of BST properties, tree traversal, and efficient search strategies.

What data structure is used in Closest Binary Search Tree Value?

The primary data structure is a Binary Search Tree. The solution relies on its ordering property where left subtree values are smaller and right subtree values are larger than the parent node. Depth-first traversal or iterative binary search is used to navigate the tree efficiently.

What is the time complexity of Closest Binary Search Tree Value?

The optimized BST-based approach runs in O(h) time where h is the height of the tree. In a balanced Binary Search Tree, this becomes O(log n). In the worst case of a skewed tree, the height can reach n, resulting in O(n) time complexity.

Description Solution Video 20:20

270. Closest Binary Search Tree Value

Easy49.2% acceptance7 companiesPremium elsewhere, free here

Given the root of a binary search tree and a target value, return the value in the BST that is closest to the target. If there are multiple answers, print the smallest.

Example 1:

Input: root = [4,2,5,1,3], target = 3.714286
Output: 4

Example 2:

Input: root = [1], target = 4.428571
Output: 1

Constraints:

The number of nodes in the tree is in the range [1, 10⁴].
0 <= Node.val <= 10⁹
-10⁹ <= target <= 10⁹

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270. Closest Binary Search Tree Value

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