Given two strings str1 and str2 of size m and n, write a program to check whether the two strings are an anagram of each other or not. A string str1 is an anagram of str2 if the characters of str1 can be rearranged to form str2.
Given an array of integers, sort the array into a wave-like arrangement. In other words, An array A[0..n-1] is sorted in wave form if A >= A <= A >= A <= A >= ….This problem has been asked during google coding interview.
Given an array of n integers and a target number, write a program to check whether a pair sum exits in the array or not. In other words, we need to check whether pair of elements in the array sum exactly to the target value.
There is a staircase of n steps and you can climb either 1 or 2 steps at a time. You need to count and return the total number of unique ways to climb the staircase. The order of steps taken matters.
Quicksort is often the best practical choice for sorting because it works remarkably efficiently on average O(nlogn) time complexity. It is also one of the best algorithms to learn problem-solving using recursion and divide and conquer approach. In this blog, we have covered: 1) How quick sort works recursively? 2) Choosing a correct pivot value in the partition algorithm 3) Best, worst, and average-case time complexity analysis 4) Space complexity and essential properties of the quick sort. Explore and Enjoy!
You are given an array X consisting of n elements, write a program to find majority element in an array i..e return the number which appears more than n/2 times. You may assume that the array is non-empty and the majority element always exists in the array. A majority element is an element that appears more than n/2 times, so there is at most one such element.
Write a program to remove the duplicates from the sorted array. For this we are given a sorted array, the task is to remove the duplicate elements such that there is a single occurrence of each element in the array.
Given two integer arrays, X and Y of size m and n. Write a program to find the intersection of these two arrays. The intersection of two arrays is a list of distinct elements present in both arrays. The elements in the intersection can be in any order. Suppose m > n and elements in both arrays are distinct.
There are two sorted arrays A and B of size n each, write a program to find the median of the array obtained after merging both the arrays(i.e., an array of length 2n which is even). The median of a sorted array of size n is defined as the middle element when n is odd and the average of the middle two elements when n is even.
Given an array X with n elements, we need to write a program to find the largest contiguous subarray sum. A subarray of array X of length n is a contiguous segment from X[i] through X[j] where 0<= i <= j <= n. Kadane algorithm idea is intuitive, using a single loop and few variables to solve the problem. We can use a similar idea to solve other coding problems.
An array of non-negative integers is given and the aim is to reach the last index in the minimum number of jumps. You are initially positioned at the first index of the array and each element in the array represents your maximum jump length at that position.
Given an array X consisting of 0s, 1s, and 2s. Write a program to sort the array of 0’s, 1’s, and 2’s in ascending order. This is a famous coding interview problem asked in facebook, microsoft and amazon.
Given the root of a binary tree, write a program to check whether it is a valid binary search tree (BST) or not. A BST is valid if all nodes in the left subtree have values less than the node’s value, all nodes in the right subtree have values greater than the node’s value, and both left and right subtrees are also binary search trees.
Given n non-negative integers representing an elevation map where the width of each bar is 1, compute how much water it can trap after raining. This is a famous interview problem to learn time and space complexity optimization using various approaches. Two-pointers approach provides an efficient solution in O(n) time and O(1) space.
Given an array that includes both positive and negative numbers, write a program to find the first missing positive integer. This is one of the best searching problems for learning step-by-step optimization using various approaches. An in-place hashing solution uses the same input array to process values and generate correct output.
Given an array of n non-negative integers height[n], where each represents a point at coordinate (i, height[i]). n vertical lines are drawn such that the two endpoints of line i is at (i, height[i]) and (i, 0). Write a program to find two lines, which together with the x-axis form a container, such that the container contains the most water.
The binary search is one of the fastest searching algorithms, which search a value in the sorted array in an O(logn) time complexity. Here we search a value using divide and conquer by repeatedly dividing the search interval in half. Problem statement: Given a sorted array X of n elements, search a given element key in X. If the key exists, then return its index in the sorted array. Otherwise, return -1.
Given an array X of n integers, return true if and only if it is a valid mountain array. The array X is a mountain array if and only if n >= 3 and there exists some i with 0 < i < n - 1 such that: X < X <...X[i-1] < X[i] and X[i] > X[i+1] > ...> X[n - 1]. In other words, we call the array mountain array when the array is strictly increasing and then strictly decreasing.
Given an array and a positive integer k, write a program to find the kth smallest element in the array. This is an excellent problem to learn problem-solving using the heap data structure. The quick-select approach (divide and conquer) is also worth exploring that helps optimize time complexity to O(n) time average.
Given the root of a BST and an integer k, write a program to find the kth largest value among all the nodes' values in the tree. This is an excellent problem to learn problem-solving using inorder traversal and data structure augmentation (storing extra information inside BST nodes for solving a problem).
Given the root of a Binary Search Tree (BST), write a program to find the absolute minimum difference between the values of any two nodes in the tree. Here node values in the tree can be positive, negative, or zero. This is an excellent problem to learn problem-solving using in-order traversal in a BST.
Given a string S, write a program to sort it in decreasing order based on the frequency of the characters. The frequency of a character is the number of times it appears in the string. If two characters have the same frequency, whichever occurs earliest in S, must come first. In other words, the sorting must be stable.
Given an array X of distinct elements, write a program to find all the unique triplets in the array whose sum is equal to zero. For example, suppose such triplets in the array are X[i], X[j] and X[k] then X[i] + X[j] + X[k] = 0. Note : solution set must not contain duplicate triplets.
The longest common subsequence algorithm is a problem to find the length of the longest subsequence common to all subsequences of two strings. The lcs algorithm differs from the algorithm of the longest common substring problem. Explore and Enjoy!
Write a program to detect the loop in a linked list. A linked list with a cycle causes iteration over the list to fail because the iteration will never reach the end of the list. Therefore, it is desirable to be able to detect that a linked list has no cycle before trying an iteration. So, we are going to discuss various algorithms to detect a loop in a singly linked list. This is also one of the best-linked list interview problems.
Given an array X of n integers, write a program to find the length of the longest consecutive elements sequence. In other words, we need to find the length of the longest sub-sequence such that elements in the subsequence are consecutive integers. The consecutive numbers can be in any order.
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