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 In a Binary Search Tree (BST), finding the minimum absolute difference between the values of any two distinct nodes is a classic problem in tree data structure algorithms. This problem is a natural extension of the concept of BST properties and is useful in scenarios such as range queries, nearest neighbor searches, and optimization problems. In this blog post, we’ll walk through the approach to solve the problem of finding the minimum distance between two nodes in a BST. We will break down the solution, discuss different strategies, and demonstrate an optimized approach to solve the problem efficiently. Problem Statement: Minimum Distance Between BST Nodes (LeetCode Problem 783) Problem Description: You are given the root of a Binary Search Tree (BST). Your task is to find the minimum absolute difference between the values of any two distinct nodes in the tree. For example: Input 1: root = [4, 2, 6, 1, 3] Output: 1 The nodes with values 2 and 3 have the smallest absolute difference

When working with Binary Search Trees (BSTs), one of the most common operations is searching for a node with a specific value. This operation is fundamental to many algorithms and data structures that rely on trees. In this blog post, we will explore how to search for a node in a Binary Search Tree (BST), explain the step-by-step approach, and optimize it for better performance. What is a Binary Search Tree (BST)? Before diving into the search algorithm, let's quickly define a Binary Search Tree (BST) . A BST is a type of binary tree where each node has at most two children: a left child and a right child. The key property of a BST is that for each node: All values in the left subtree are less than or equal to the node’s value. All values in the right subtree are greater than or equal to the node’s value. This property allows for efficient searching, as we can eliminate half of the remaining search space at each step, just like binary search in an array. The Problem: Search in a Bi

In this LeetCode problem, we're tasked with transforming a given binary string into a "beautiful" string. A beautiful string is one that can be partitioned into substrings, each containing only 0s or 1s and having an even length. To achieve this beauty, we're allowed to change any character in the string to either 0 or 1. The challenge lies in determining the minimum number of such changes required. Intuition and Approach To solve this problem efficiently, we can employ a greedy approach. We'll iterate through the string, keeping track of the current character and the count of consecutive occurrences of that character. Iterate and Count: Start with the first character and initialize a count to 1. As we traverse the string, we increment the count if the current character matches the previous one. If the current character is different, we've encountered a new substring. Handle Odd-Length Substrings: If the current count is odd, we'll need to make

String manipulation is a common task in programming, especially when it comes to optimizing data storage or transmission. One fascinating challenge is the "String Compression III" problem from LeetCode, which requires you to compress a string according to specific rules. In this post, we’ll explore the problem statement, discuss a practical solution, and delve into the intricacies of the algorithm. Whether you’re preparing for coding interviews or simply want to enhance your problem-solving skills, this guide will provide valuable insights. Problem Statement You are given a string called word , and your task is to compress it using a specific algorithm. The rules for compression are as follows: Begin with an empty string comp . While word is not empty, remove a maximum length prefix made of a single character c , which can repeat at most 9 times. Append the length of the prefix followed by the character c to comp . Continue this process until all characters in word are pro

When it comes to data structures in computer science, binary trees and linked lists are fundamental concepts that often come into play. In this post, we will explore an intriguing problem: converting a binary tree into a doubly linked list (DLL). This task may seem daunting, but with the right approach, we can achieve it seamlessly. Let's dive into the details! Understanding the Problem What is a Binary Tree? A binary tree is a hierarchical structure in which each node has at most two children referred to as the left child and the right child. This structure is crucial for organizing data hierarchically, facilitating efficient searching, inserting, and deleting operations. What is a Doubly Linked List? A doubly linked list (DLL) is a linear data structure consisting of nodes, where each node contains three components: a data field and two pointers. One pointer points to the next node in the sequence (next), while the other points to the previous node (prev). This bidirectional natu

String manipulation is one of the most commonly tested topics in coding interviews, and LeetCode's Problem 1593: Split a String Into the Max Number of Unique Substrings gives us an interesting challenge. The goal is to split a string into as many unique substrings as possible. In this blog post, we’ll go step by step to understand the problem, come up with an efficient solution, and analyze its time and space complexity. Problem Statement Given a string s , your task is to split it into the maximum number of unique substrings . You can break the string into any list of non-empty substrings as long as the concatenation of all substrings forms the original string, and all the substrings in the split are unique . A substring is defined as a contiguous sequence of characters within a string. Example 1: Input : s = "ababccc" Output : 5 Explanation : One way to split the string is ["a", "b", "ab", "c", "cc"] . Note that each

When working with binary trees, one common task is to analyze the properties of the tree's levels. In this blog post, we'll walk through a solution to LeetCode Problem 2583: Kth Largest Sum in a Binary Tree , a problem that challenges us to compute and find specific sums from different levels of a binary tree. Problem Statement You are given the root of a binary tree and a positive integer k . Your goal is to return the k-th largest level sum in the tree. The level sum is defined as the sum of the values of all nodes at the same depth in the tree. If the number of levels in the tree is less than k , the function should return -1 . Example 1: Input: root = [5, 8, 9, 2, 1, 3, 7, 4, 6] , k = 2 Output: 13 Explanation: Level 1 sum: 5 Level 2 sum: 8 + 9 = 17 Level 3 sum: 2 + 1 + 3 + 7 = 13 Level 4 sum: 4 + 6 = 10 The 2nd largest sum is 13 . Example 2: Input: root = [1, 2, null, 3] , k = 1 Output: 3 Explanation: The largest level sum is 3 (at the third level). This problem essentia

The much-awaited trailer for the film GOAT , starring Vijay, has finally been released, and it’s generating a huge buzz among fans. The trailer has quickly become a hit online, capturing the excitement of the audience. GOAT will be hitting theaters in Tamil, Telugu, and Hindi on September 5, offering a multi-language experience for moviegoers. The trailer for GOAT , featuring the popular actor Vijay, has finally been released and it's creating a lot of excitement. The trailer gives a glimpse into a fast-paced action thriller that has fans eager for the film's release. Directed by Venkat Prabhu, GOAT cleverly weaves some of Vijay’s iconic lines into the story, which has thrilled his fans. One of the standout features of the trailer is a new title card for Vijay that has sparked curiosity among viewers, with many speculating about hidden meanings and clues. The movie's music, composed by Yuvan Shankar Raja, initially received mixed reviews, but his background score for the

LeetCode Problem 624, titled "Maximum Distance in Arrays," challenges us to find the maximum distance between any two elements from different arrays within a given list of arrays. In this blog post, we will break down the problem, explain the code solution step-by-step, and discuss the time and space complexity of the solution. Problem Explanation The problem presents us with a 2D array where each sub-array is sorted in ascending order. Our task is to determine the maximum distance between any two elements such that the elements come from different sub-arrays. Code Explanation Here's a clean and efficient solution to the problem using C++:     class Solution {     public:         int maxDistance ( vector < vector < int >> & arrays )         {             int min_value = arrays [ 0 ][ 0 ];             int max_value = arrays [ 0 ][ arrays [ 0 ]. size () - 1 ];             int maximum_distance = 0 ;             for ( int i = 1 ; i <