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I applied via Referral and was interviewed before Dec 2021. There were 3 interview rounds.
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Print prime numbers in a given range and optimize the solution.
Use Sieve of Eratosthenes algorithm to generate prime numbers efficiently
Start with a boolean array of size n+1, mark all as true
Loop through the array and mark all multiples of each prime as false
Print all the indexes that are still marked as true
Find angle between hour and minute hand in a clock given the time.
Calculate the angle made by the hour hand with respect to 12 o'clock position
Calculate the angle made by the minute hand with respect to 12 o'clock position
Find the difference between the two angles and take the absolute value
If the angle is greater than 180 degrees, subtract it from 360 degrees to get the smaller angle
To un-hash a string, use a reverse algorithm to convert the hash back to the original string.
Create a reverse algorithm that takes the hash as input and outputs the original string
Use the same logic as the hash function but in reverse order
If the hash function used a specific algorithm, use the inverse of that algorithm to un-hash the string
I appeared for an interview before Dec 2020.
Round duration - 120 minutes
Round difficulty - Medium
The Entire Test is held in HackerRank Platform. It has:
2 coding questions (one easy and one medium)
2 output questions(medium)
2 Aptitude(easy)
1 general Computer science(medium)
It took me 30 min for each coding questions. I did not know that general question is related to bash commands.
Tips: Practice the Warmup questions in Hacker Rank.
Do some Basic aptitude questions.
Thorough with the basic C and C++ concepts
Transform a given Binary Tree into a Doubly Linked List.
Ensure that the nodes in the Doubly Linked List follow the Inorder Traversal of the Binary Tree.
The fi...
Convert a Binary Tree into a Doubly Linked List following Inorder Traversal.
Perform Inorder Traversal of the Binary Tree to get the nodes in order.
Create a Doubly Linked List by linking the nodes in the order obtained from Inorder Traversal.
Return the head of the Doubly Linked List as the output.
Given an arbitrary array arr
consisting of N
non-negative integers where every element appears thrice except for one. Your task is to find the element in the array that appears onl...
Find the unique element in an array where every other element appears thrice.
Use XOR operation to find the unique element.
Iterate through the array and XOR each element to find the unique one.
Return the unique element as the answer.
Round duration - 60 minutes
Round difficulty - Medium
It's completely around the data structures. The questions are a bit tricky but once u think without any tension u can get through easily. The interviewer is helpful and gives u few hints if u catch them at the right point of time u got it.
Tips: got through Data Structures and Algorithms Made Easy by Narasimha Karumanchi. It's a best book for the interviews.
Given a Binary Tree with 'N' nodes, where each node holds an integer value, your task is to compute the In-Order, Pre-Order, and Post-Order traversals of the binar...
Implement a function to compute In-Order, Pre-Order, and Post-Order traversals of a Binary Tree given in level-order format.
Parse the input level-order tree elements to construct the binary tree.
Implement recursive functions for In-Order, Pre-Order, and Post-Order traversals.
Return the traversals as lists of lists for each test case.
Given a singly linked list and two integers 'N' and 'M', traverse the linked list to retain 'M' nodes and then delete the next 'N' nodes. Continue this proces...
Traverse a linked list to retain 'M' nodes and then delete the next 'N' nodes, repeating until the end of the list.
Create a function that takes the head of the linked list, 'N', and 'M' as input parameters.
Traverse the linked list, retaining 'M' nodes and deleting the next 'N' nodes in each iteration.
Update the pointers accordingly to skip 'N' nodes after retaining 'M' nodes.
Repeat this process until the end of the lin...
Round duration - 60 minutes
Round difficulty - Easy
The interviewer asked to put everything on the blackboard and write down the code of each and everything.
Question : Explain all the search algorithm you know with space and Time complexities.
Answer : Linear search : It is a sequential search algorithm where the entire array is traversed till the desired element is not found. Time complexity is O(N) and auxiliary space is O(1).
Binary search : In this algorithm, a sorted array is searched by repeatedly dividing the search interval in half.
Steps :
1. Initially the interval covers the whole array.
2. If the value to be searched is less than the item in the middle of the interval, narrow the interval to the lower half. Otherwise, narrow it to the upper half.
3. The process is repeated until the value is found or the interval is empty.
Time complexity is O(log n) and auxiliary space is O(1) in case of iterative implementation.
Given an array of integers with numbers in random order, write a program to find and return the number which appears the most frequently in the array.
If multip...
Program to find the number with maximum frequency in an array of integers.
Create a dictionary to store the frequency of each number in the array.
Iterate through the array and update the frequency count in the dictionary.
Find the number with the maximum frequency in the dictionary and return it.
If multiple elements have the same maximum frequency, return the one with the lowest index.
Tip 1 : Must do Previously asked Interview as well as Online Test Questions.
Tip 2 : Go through all the previous interview experiences from Codestudio and Leetcode.
Tip 3 : Do at-least 2 good projects and you must know every bit of them.
Tip 1 : Have at-least 2 good projects explained in short with all important points covered.
Tip 2 : Every skill must be mentioned.
Tip 3 : Focus on skills, projects and experiences more.
Print only the leaf nodes of a doubly linked tree.
Traverse the tree and check if a node has no children and both left and right pointers are null.
If yes, then it is a leaf node and print it.
If no, then continue traversing the tree.
Use recursion to traverse the tree in a depth-first manner.
LRU page replacement algorithm is used to replace the least recently used page in memory with a new page.
LRU stands for Least Recently Used
It is a cache eviction algorithm
It is used to manage memory in operating systems
It works by keeping track of the pages that are used recently and the ones that are not
When a new page is to be loaded into memory, the algorithm checks which page has not been used for the longest time
Reverse m nodes and leave n nodes in a linked list till the end.
Traverse the linked list till m nodes and reverse them
Traverse n nodes and continue reversing m nodes
Repeat the above step till the end of the linked list
Handle edge cases like m or n being greater than the length of the linked list
Inorder traversal is a way of visiting all nodes in a binary tree by visiting the left subtree, then the root, and then the right subtree.
Start at the root node
Traverse the left subtree recursively
Visit the root node
Traverse the right subtree recursively
Repeat until all nodes have been visited
Inorder traversal of a tree without recursion
Create an empty stack and initialize current node as root
Push the current node to stack and set current = current.left until current is NULL
If current is NULL and stack is not empty, pop the top item from stack, print it and set current = popped_item.right
Repeat step 2 and 3 until stack is empty
Find the triplicate number in an array of duplicates.
Iterate through the array and keep track of the frequency of each number.
Return the number that appears three times.
If no number appears three times, return null.
Explanation of search algorithms with their space and time complexities.
Linear Search - O(n) time complexity, O(1) space complexity
Binary Search - O(log n) time complexity, O(1) space complexity
Jump Search - O(√n) time complexity, O(1) space complexity
Interpolation Search - O(log log n) time complexity, O(1) space complexity
Exponential Search - O(log n) time complexity, O(1) space complexity
Fibonacci Search - O(log n)
Find the most repeated number in an array of length n with numbers 1-n.
Create a dictionary to store the count of each number in the array
Iterate through the array and update the count in the dictionary
Find the key with the highest count in the dictionary
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