Learnitweb

Author: Editorial Team

  • Backspace String Compare

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    Problem Statement You are given two strings s and t. Each string may contain the backspace character #, which means the previous character should be deleted. Your task is to determine if the two strings are equal after applying all backspace operations. Example 1: Example 2: Input: s = “a##c”, t = “#a#c”Output: trueExplanation: Example…

  • Middle of the Linked List

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    Problem Statement You are given the head of a singly linked list, and your task is to return the middle node of the linked list. Example 1: Example 2: Constraints: Approach 1: Count Nodes (Two Pass) Time Complexity: O(n) – two traversals of the linked list.Space Complexity: O(1) – only a few pointers are used.…

  • Counting Elements

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    Problem Breakdown Given an integer array arr, you need to determine how many elements x exist such that x + 1 is also present in arr. If there are duplicates of x, each occurrence should be counted separately. Example 1: Input: arr = [1, 2, 3] Output: 2 Explanation: Both 1 and 2 are counted…

  • Group anagrams

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    Problem Statement You are given an array of strings strs. The task is to group the strings that are anagrams of each other. Definition: Two strings are anagrams if they have the same characters in the same frequency but possibly in a different order. Example: Constraints: Approach The main idea is to use a hash…

  • Move Zeroes

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    Problem Statement You are given an array of integers where some elements are zero. Your task is to move all the zeroes to the end of the array, maintaining the relative order of non-zero elements. The solution must be: Example Input: [4, 2, 0, 4, 0, 3, 0, 5, 0, 1]Output: [4, 2, 4, 3,…

  • Happy Number

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    Problem Statement You are given a positive integer n. Replace the number by the sum of the squares of its digits, and repeat the process until: Return true if n is a happy number. Otherwise, return false. What is a Happy Number? A happy number is a number that eventually reaches 1 when you repeatedly…

  • Space Complexity

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    What Is Space Complexity? As discussed earlier, algorithm complexity includes two main components: In this section, we’ll focus on the space complexity, which is usually denoted as the function . All the rules for evaluating space complexity using Big-O notation are identical to those used for time complexity. Example 1: Simple Function Call Let’s consider…

  • Amortized Analysis

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    Amortized analysis is a powerful technique used to analyze the time complexity of algorithms, especially when an occasional expensive operation is offset by many cheap ones. Let’s explore this concept step-by-step with a concrete example. Understanding the Problem Suppose we have a fully filled array of elements, and we want to insert one more element.…

  • Understanding Recursive Function Complexity in Algorithms

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    In this section, we’ll explore how to analyze the complexity of recursive functions, a topic often perceived as challenging, but highly important in computer science. To determine the complexity of a recursive function, we follow these general steps: Example 1: A Simple Recursive Chain Consider the following function: Here’s how to evaluate its complexity: As…

  • Advanced Complexity Evaluation: Addition, Multiplication, Logarithms, and Strings

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    In this tutorial, we’ll dive deeper into algorithm complexity, focusing on common operations such as addition, multiplication, logarithmic algorithms, and the role of string manipulation in evaluating time complexity. 1. Complexity of Addition and Multiplication Let’s start by analyzing sequential and nested loops. Example: Sequential Loops Suppose we have the following scenario: These loops run…