coding-interview-questions

Binary search is an efficient algorithm for searching a value in a sorted array using the divide and conquer idea. It compares the target value with the value at the mid-index and repeatedly reduces the search interval by half. The search continues until the value is found or the subarray size gets reduced to 0. The time complexity of the binary search is O(log n).

Given an array of n integers, find the length of the longest consecutive sequence. In other words, we need to find the length of the longest subsequence such that elements in the subsequence are consecutive integers. The consecutive numbers can be in any order. Note: This is an excellent problem to learn problem-solving using sorting and hash table.

Given two strings X[] and Y[] of sizes m and n, design an algorithm to find the length of the longest common subsequence (LCS). There can be many possible common subsequences of two strings, but we need to return the common subsequence of the longest length. Note that this is an excellent problem to learn dynamic programming.

Given a binary search tree and a key value. Write a program to delete the given key from the binary search tree and return the updated root node. This is an excellent problem to learn pointer manipulation in binary trees and problem-solving using both iterative and recursive approaches.

Write a program to find the number of structurally unique binary search trees (BSTs) that have exactly n nodes, where each node has a unique integer key ranging from 1 to n. In other words, we need to determine the count of all possible BSTs that can be formed using n distinct keys.

Write a program to convert a sorted array of integers into a balanced binary search tree. Each node in the tree must follow the BST property, and the height of the left and right subtrees should be as close to equal as possible. Note: This is an excellent problem to learn problem-solving using the divide and conquer approach.

Write a program to find the minimum number of operations required to convert string X to string Y. You have the following three operations permitted on a string: 1) Insert a character 2) Delete a character 3) Replace a character. The edit distance between two strings is the minimum number of operations (insertions, deletions, or substitutions of characters) required to transform one string into the other.

The flood fill problem is a way to fill a region of connected pixels with a new colour, starting from a given pixel in an image. You are given an image represented by an m x n grid of integers, where the image[i] represents the pixel value at position (i, j). You are also given the coordinates of a starting pixel (x, y) and a new colour to use for the flood fill operation.

Write a program to count the number of possible triangles that can be formed with three elements from a given unsorted array of positive integers. The three elements, representing the lengths of the sides of a triangle, must satisfy the triangle inequality: the sum of any two sides must be greater than the third side.

Write a program that returns a fixed point in the given sorted array of distinct integers. A fixed point is an index i such that X[i] = i. If a fixed point exists, the program should return the index of the fixed point. If no fixed point is found, the program should return -1. Note that the integers in the array can be both positive and negative.

Counting sort is a stable sorting algorithm that works in O(n) time and space complexity when input are integers in the range 0 to k and k = O(n). Instead of comparison, counting sort uses array indexing to determine position of elements. For each element x, it counts values less than x and places x directly into its correct position in the sorted array.

Given the head of a linked list, write a program to find if linked list has a cycle or not. Return true if there is a cycle or loop in the linked list. Otherwise, return false. A linked list with cycle causes iteration to fail because the iteration will never reach the end. So, detecting a linked list loop is important before applying an iterative approach.

Level order traversal accesses nodes in level by level order. This is also called breadth first search or BFS traversal. Here we start processing from the root node, then process all nodes at the first level, then process all nodes at the second level, and so on. In other words, we explore all nodes at the current level before going to nodes at the next level.

Given a binary tree, write a program to find its height. In other words, we are given a binary tree and we need to calculate the maximum depth of the binary tree. The height or maximum depth of a binary tree is the total number of edges on the longest path from the root node to the leaf node. Note: This is an excellent problem to learn problem-solving using DFS and BFS traversal.

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. Note: This is an excellent problem to learn problem-solving using iterative and recursive inorder traversal of a binary tree.

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 binary search tree. Note: This is an excellent problem to learn problem solving using recursive and iterative inorder traversal and data structure augmentation (storing extra information inside BST nodes for solving a problem).

Write a program to implement a stack using queues. We must use queue operations like enqueue, dequeue, front, size to implement stack operations like push, pop, and top. We have discussed three approaches: 1) Using two queues: O(n) pop and O(1) push 2) Using two queues: O(1) pop and O(n) push 3) Using one queue: O(1) pop and O(n) push.

Write a program to implement queue using stack. We should use stack operations like push, pop, top, size, and isEmpty for implementing queue operations like enqueue, dequeue, and front. In this blog, we have discussed two approaches for implementing queue using two stacks: 1) Dequeue O(1) and Enqueue O(n) 2) Enqueue O(1) and Dequeue O(1).

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 max and min heap data structures. The quick-select approach (divide and conquer) is also worth exploring because it helps to optimize time complexity to O(n) on average.

There is a staircase with n steps, and you can climb either 1 or 2 steps at a time. Write a program to count and return the number of unique ways to climb the nth stair. The order of steps taken matters. Note: Climbing stairs is an excellent problem to learn the dynamic programming approach and the application of the Fibonacci series in problem-solving.

Suppose we want to make a change for a given value K of cents, and we have an infinite supply of each of coin[ ] = [C​1​​, C​2​​, …, C​m​​] valued coins. Write a program to find the minimum number of coins required to make the change. Note: This is an excellent counting problem to learn problem solving using dynamic programming approach.

Given an array of n elements, write a program to find the maximum subarray sum. A subarray of array X[] is a contiguous segment from X[i] through X[j], where 0 <= i <= j <= n. Note: Max subarray sum is an excellent problem to learn problem-solving using the divide and conquer approach, dynamic programming, and single loop (kadane's algorithm).

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. Note: This is an excellent problem to learn problem solving using dynamic programming.

Given an array, find the next greater element for every element in the array (NGE). The next greatest element for an element is the first largest element on the right side. For elements for which no next largest element exists, consider the next greater element as -1. We have discussed two stack-based solutions: 1) Traversing from left to right, 2) Traversing from right to left.

Given a sorted array, write a program to remove duplicates from the array. We need to remove repeated elements so that there is a single occurrence of each element and return the length of the array containing unique elements. Note: This is an excellent problem to learn the fast and slow pointers approach. We have discussed two O(n) time in-place solutions.

Given a boolean 2D array, where each row is sorted. Find the row with the maximum number of 1s. This is an excellent matrix problem that can be solved in linear time complexity. The best part is — we are using the sorted order property and nested loops to improve the solution over the binary search approach.

Given an array of integers sorted in ascending order, the program should find the first and last occurrence of a given element. The goal is to design an algorithm with O(log n) time complexity. Note that this is an excellent question to learn problem-solving using binary search. Here, the binary search needs to be applied twice to solve this problem.

In an array of size 2N, there are N + 1 unique elements, and exactly one of these elements is repeated n times. Write a program to return the N-repeated element in the given 2N size array. Note: This is an excellent problem to learn optimization using the mathematical approach. Sometimes mathematical insights into the problem can help us to get efficient solutions.

You are given an array of 1s and 0s and you are given an integer k which signifies the number of flips allowed. Write a program to find the position of zeros which when flipped will produce a maximum continuous series of 1s. Note: This is an excellent problem to learn problem solving using sliding window technique in O(n) time and O(1) space.

You are given an array X[] of n elements, write a program to find majority element in an array. A majority element is an element that appears more than n/2 times, so there is at most one such element. Assume that array is non-empty and majority element always exists in the array. Note: This is an excellent problem to learn various approaches.

Given an array X[] of integers, find the maximum parity index. The parity index is the maximum index difference between two elements (X[i], X[j]) such that, j > i and X[j] > X[i]. In other words, we need to find maximum j - i such that j > i and X[j] > X[i]. Note: This is an excellent problem to learn problem solving using sorting and two pointers approaches

Given an array A[] of n integers, find out the maximum difference between any two elements such that the larger element appears after the smaller element. In other words, we need to find max(A[j] - A[i]), where A[j] > A[i] and j > i. Note: This is an excellent problem to learn problem-solving using divide and conquer and a single loop.

Given two unsorted arrays of size m and n, find whether one array is a subset of another array or not. An array Y[] will be a subset of another array X[] if each element of Y[] is present in X[]. Assume that there are no repeated elements in both arrays and n <= m. Note: This is an excellent problem to learn problem solving using various approaches.

Given an array of n integers and a target number, write a program to find whether a pair sum exists in the array or not. In other words, we need to check for a pair of elements in the array that sum exactly to the target value. Assume that all elements are distinct. Note: This is an excellent problem to learn problem solving using two pointers and hash table.

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 problems for learning step-by-step time complexity optimization using various approaches. An in-place hashing solution uses the same input array to process values and generate output.

A binary array X[] is given where elements are either 0 or 1. Write a program to find the maximum consecutive ones. The subarray with max continuous 1's can be present anywhere, starting from some index i and ending at some index j. This is an excellent problem to learn problem solving using a sliding window approach and single loop.

Given a string S, write a program to find the length of longest substring without repeating characters. The substring is a continuous subpart of the string and we need to return the largest substring which has all unique characters. Note: This is an excellent problem to learn problem solving and time complexity optimization using sliding window approach.

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 endpoints of line i is at (i, height[i]) and (i, 0). Find two lines, which together with x-axis form a container, such that container contains the most water. This is an excellent problem to learn two pointers approach.

Given n non-negative integers representing an elevation map where the width of each bar is 1. Write a program to 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 using O(n) time and O(1) space.

Given an array consisting of 0s, 1s, and 2s, write a program to sort this array of 0, 1, and 2 in ascending order. We need to sort the array in O(n) time complexity without using sorting algorithms or extra space. Note: This is a variation of the Dutch national flag problem and an excellent problem to learn problem solving using three pointers.

Learn the design, implementation, analysis, and comparison of bubble sort, selection sort, and insertion sort. In data structures and algorithms, these are some of the fundamental sorting algorithms to learn problem-solving using an incremental approach with the help of nested loops. All of them have the same worst-case and average-case time complexity.

There are two sorted arrays A and B of size n each, write a program to find the median of these two sorted arrays obtained after merging (new merged array will be 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.

You have given row-wise and column-wise sorted 2d matrix and integer k, write a program to search k in 2d matrix, i.e. find whether k is present or not. Each row is sorted from left to right, and the first integer of each row is greater than the last integer of the previous row. Note: This is an excellent problem to learn problem solving binary search in a 2d matrix.

You are given an array of n integers that is first increasing and then decreasing. Write a program to find the maximum value in the array. Our goal should be to solve this problem using O(logn) time complexity. Note: This is an excellent problem to learn problem solving using binary search, where we modify binary search to get an efficient solution.

Given an array X[] of size n, write a program to find the maximum and minimum elements while making the minimum number of comparisons. This is an excellent question to learn problem-solving using a single loop and divide and conquer approach. In the efficient single-loop solution, we increment the loop by two to optimize the comparison count.

Given an array X[] of n integers, write a program to find product[] array such that product[i] is equal to product of all array elements except X[i]. We need to solve this problem without using division operations. Note: This is an excellent product array puzzle to learn time complexity optimization using prefix array and a single loop.

Write a program to find the equilibrium index of an array. An array's equilibrium index is an index such that the sum of elements at lower indexes equals the sum of elements at higher indexes. Note: This is an excellent coding question to learn time and space complexity optimization using a prefix array and a single loop using variables.

Given an input array height[] which represents the heights of buildings, write a program to count the number of buildings facing the sunset. Assume that the heights of buildings are distinct. Insight: Here all buildings facing sunlight will be in increasing order. Note: This is an excellent problem to learn problem-solving using a single loop.

Given an integer n, write a program to return string representation of numbers from 1 to n. If number is divisible by 3, we store “Fizz”. If number is divisible by 5, we store “Buzz”. If number is divisible by both 3 and 5, we store “FizzBuzz”. Hint: This is an excellent puzzle to learn coding concepts like conditional statements, loops, etc.

Write a program to find intersection of two sorted linked lists and return the head pointer of the new linked list. Here head pointers of both sorted linked lists are given as input and we shouldn’t do any changes in the structure to generate the output. Note: This is an excellent problem to learn problem-solving using recursion and two pointers in a linked list.

Given two strings, str1 and str2, of size m and n, write a program to check whether two strings are an anagram of each other or not. A string str1 is an anagram of str2 if characters of str1 can be rearranged to form str2. Note: This is an excellent string problem to learn problem-solving and optimization using direct address table.

Given an n x n 2D matrix, write a program to rotate the matrix by 90 degrees in the anticlockwise direction. The program should rotate the matrix 90 degrees without using extra space. In other words, we have to perform the rotation by modifying the 2D matrix directly. Note that this is an excellent problem to learn problem-solving using loops and the transpose of a matrix.

Given a 2-dimensional matrix, write a program to print matrix elements in spiral order. We can imagine spiral traversal as an ordered set of matrix segments with horizontal and vertical boundaries, where both boundaries are reduced by one at each step. Note: This is an excellent problem to learn problem-solving using iteration and recursion.

The head pointer of a linked list is given. Write a program to remove the Nth node from the end of the linked list and return its head. In other words, when the node is traversed from the end, we have to delete the Nth node from there. Note: This is an excellent problem for beginners to learn problem-solving using two pointers in a linked list.

A head pointer of a singly linked list is given, write a program to reverse linked list and return the head pointer of the reversed list. We need to reverse the list by changing the links between nodes. Note: This is an excellent question to learn problem-solving using both iteration (Three-pointers) and recursion (Decrease and conquer approach).

Given a singly linked list, write a program to find the middle element of the linked list. We need to return the second middle node if the node count is even. The goal should be to use a single loop and O(1) extra space to find the middle element. Note: This is an excellent problem to learn problem-solving using fast and slow pointers in the linked list.

Given an array X[] of n elements filled with several integers, some of them being zeroes, write a program to move all the zeros to the end. We need to preserve the relative order of non-zero elements and solve this problem in place using O(n) time complexity. Note: This is an excellent problem to learn problem solving using two pointers approach.

Given an array X[] of n integers, write a program to find the length of largest continuous subarray with zero sum. The subarray length starting from index i and ending at index j will be j - i + 1. So in other words, for all j > i, find max (j - i + 1) among all subarrays with zero sum.. Note: This is an excellent question to learn problem-solving using hash table.

Given an unsorted array of n integers, write a program to sort array into a wave array. There can be many possible waveforms, but we need to return any one of them. An array A[] is sorted in wave arrangement if A[0] >= A[1] <= A[2] >= A[3] <= A[4] >= ....and so on. Note: This is an excellent problem to learn problem-solving using a single loop.

A sorted and rotated array of size n is given, write a program to find minimum element in rotated sorted array. Rotation by k times means that the first k sorted elements of the array will move to the last k positions, and the last n - k sorted elements will move to the first n - k positions. Note: We don’t know how many times array is rotated in the given problem.

Given two integer arrays X[] and Y[], write a program to check if arrays are equal or not. Two arrays are equal if they have the same elements in any order. If there are repeated elements, then counts of repeated elements must also be the same for both arrays. Note: This is an excellent problem to learn problem solving using a hash table.

Given a Roman number, write a program to convert Roman number to a corresponding integer value. What are Roman numbers? Roman numbers are the symbols used in a system of numerical notation based on the ancient Roman system. The symbols are I, V, X, L, C, D, and M, which represent integer values respectively for 1, 5, 10, 50, 100, 500, and 1,000.

Given an array X[] of size n, write a program to find the most frequent element in the array, i.e. the element which occurs the most number of times. If multiple elements have maximum frequency, return the smallest (assume that at least one element is repeated). Note: This is an excellent problem to learn problem-solving using sorting and hash table.

Given an integer array X[] of size n, write a program to find all the leaders present in the array X[]. An array element is a leader if it is strictly greater than all elements to its right side. So the largest and last element of an array is a leader by default. Note: This is an excellent problem to learn problem-solving using a single loop and variables.

Given an array X[] of n integers, return true 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[0] < X[1] <...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 two integer arrays, X[] and Y[] of size m and n, write a program to find intersection of these two arrays. The intersection is a list of common elements present in both arrays. Suppose m > n, all array elements are distinct and intersection elements can be in any order. Note: This is an excellent problem to learn problem solving using various approaches.

We can easily implement recursive binary tree traversals (preorder, inorder, and postorder) iteratively using a stack. We need to understand the flow of recursive calls in DFS traversal and mimic what the compiler does in the background. So, we need to follow a similar process and use our own stack to simulate the recursive binary tree traversal using iteration or without using recursion.

The least recently used (LRU) cache is one of the popular caching strategies, which defines the policy to discard the least recently used items first from the cache and make room for new elements when the cache is full. It is used to organize items in order of their use, which allows identifying items that have not been used for a long time.

The least frequently used (LFU) is a cache algorithm used to manage memory within a computer. In this method, the system keeps track of the number of times a block is referenced in memory, and when the cache is full, our system removes the item with the lowest reference frequency. LFU cache get and put operation works in O(1) average time complexity.

The root of the binary search tree and a key k is given. Write a program to insert key k into the binary search tree. Note: BST structure will change after the insertion. So we need to perform insertion in such a way that the BST property continues to hold. In this blog, we have discussed recursive and iterative implementations of insertion in BST.

We start searching from root node and traverse a path downward in binary search tree. For each node in the path, compare target key k with the node key. If equal, search is successful. If k < node key, go to the left subtree. Similarly, if k > node key, go to the right subtree. In this blog, we have discussed recursive and iterative implementations of searching in BST.

Given the root of a binary tree, write a program to check whether tree is a valid binary search tree (BST) or not. To check valid bst, we verify bst property at each node: All node values in the left subtree are less than node’s value, all node values in the right subtree are greater than node’s value, and both subtrees are also binary search trees.

Given a string S[], write a program to sort string S in decreasing order based on the frequency of 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, frequency based sorting must be stable.

Merge sort is one of the fastest comparison based sorting algorithms, which works on the idea of divide and conquer approach. Worst and best case time complexity of merge sort is O(nlogn), and space complexity is O(n). This is also one of the best algorithms for sorting linked lists and learning design and analysis of recursive algorithms.

Quicksort algorithm is often the best choice for sorting because it works efficiently on average O(nlogn) time complexity. It is also one of the best algorithms to learn divide and conquer approach. In this blog, you will learn: 1) How quick sort works? 2) How to choose a good pivot? 3) Best, worst, and average-case analysis 4) Space complexity and properties of quicksort.

Given a binary tree, find its minimum depth. The min depth of a binary tree is the number of nodes along the shortest path from root node down to the nearest leaf node. The path has to end on a leaf node. Note: An excellent problem to understand efficient problem solving using breadth-first search (BFS) when the solution node is nearest to the root node.

Given two numbers n and K, write a program to find all possible combinations of K numbers from 1 to n. You may return answer in any order. Note: This is an excellent problem to learn problem-solving using the inclusion and exclusion principle of combinatorics and backtracking. We can use similar ideas to solve other problems.