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I applied via Company Website and was interviewed before Jul 2023. There were 3 interview rounds.
My favorite Apple product is the iPhone because of its sleek design, user-friendly interface, and wide range of features.
Sleek design: Apple products are known for their elegant and modern design.
User-friendly interface: The iPhone's operating system is intuitive and easy to use.
Wide range of features: From the App Store to the camera quality, the iPhone offers a variety of functions to enhance the user experience.
What is your proudest accomplishment and Tell us about your greatest failure and what you have learned from it
I applied via Referral and was interviewed in Jul 2021. There were 3 interview rounds.
A strong aggressive person can be an asset in sales, but must also be able to listen and adapt to customer needs.
Assertive communication skills are important in negotiating deals
Ability to handle rejection and maintain composure
Understanding the difference between assertiveness and aggression
Flexibility to adapt to different customer personalities and needs
posted on 25 Jun 2024
I applied via Campus Placement and was interviewed before Apr 2021. There were 2 interview rounds.
One abstract topic one current affairs topic
I applied via Newspaper Ad and was interviewed in Apr 2022. There were 2 interview rounds.
I applied via Referral and was interviewed in Apr 2024. There were 2 interview rounds.
I applied via Recruitment Consultant and was interviewed before Jul 2020. There was 1 interview round.
I appeared for an interview in Aug 2017.
Merge Sort is a divide and conquer algorithm that sorts an array by dividing it into two halves, sorting them separately, and then merging the sorted halves.
Divide the array into two halves
Recursively sort the two halves
Merge the sorted halves
Find pairs of integers in a BST whose sum is equal to a given number.
Traverse the BST and store the values in a hash set.
For each node, check if (X - node.value) exists in the hash set.
If yes, add the pair (node.value, X - node.value) to the result.
Continue traversal until all nodes are processed.
Merge overlapping time intervals into mutually exclusive intervals.
Sort the intervals based on their start time.
Iterate through the intervals and merge overlapping intervals.
Output the mutually exclusive intervals.
Example: [(1,3), (2,6), (8,10), (15,18)] -> [(1,6), (8,10), (15,18)]
Different types of hashing and alternative for Linear Chaining
Different types of hashing include division, multiplication, and universal hashing
Alternative for Linear Chaining is Open Addressing
Open Addressing includes Linear Probing, Quadratic Probing, and Double Hashing
An AVL tree is a self-balancing binary search tree where the heights of the left and right subtrees differ by at most one.
AVL tree is a binary search tree with additional balance factor for each node.
The balance factor is the difference between the heights of the left and right subtrees.
Insertion and deletion operations in AVL tree maintain the balance factor to ensure the tree remains balanced.
Rotations are performed ...
Find the minimum number of squares whose sum equals to a given number n.
Use dynamic programming to solve the problem efficiently.
Start with finding the square root of n and check if it is a perfect square.
If not, then try to find the minimum number of squares required for the remaining number.
Repeat the process until the remaining number becomes 0.
Return the minimum number of squares required for the given number n.
Insertion sort for a singly linked list.
Traverse the list and compare each node with the previous nodes
If the current node is smaller, swap it with the previous node
Repeat until the end of the list is reached
Time complexity is O(n^2)
Reverse a binary search tree while maintaining parent-child relationship.
Start by swapping the left and right child of each node recursively.
Use a depth-first search approach to traverse the tree.
Make sure to update the parent-child relationships accordingly.
To find min and max element in stack in O(1), we can use an auxiliary stack.
Create an auxiliary stack to keep track of the minimum and maximum elements.
Push the first element to both the main and auxiliary stack.
For each subsequent element, compare it with the top element of the auxiliary stack and push the smaller element to the auxiliary stack.
To get the minimum element, simply return the top element of the auxiliary...
Given an array, find the next minimum element for each element.
Iterate through the array
For each element, compare it with the elements on its right
Find the minimum element greater than the current element
If no such element exists, assign -1
Build the resultant array
Find median of input stream in minimum time complexity using online algorithm.
Use two heaps, one max heap for elements smaller than current median and one min heap for elements greater than current median.
Maintain balance between the two heaps by ensuring that the size difference is at most 1.
If the size of both heaps is equal, median is the average of the top elements of both heaps. Else, median is the top element of ...
To make a copy of a linked list with two pointers, iterate through the original list and create a new node for each element.
Iterate through the original linked list
Create a new node for each element
Set the 'next' pointer of each new node
Set the 'arbitrary' pointer of each new node
Reverse the nodes of a linked list in pairs of n
Iterate through the linked list in pairs of n
Reverse the nodes within each pair
Connect the reversed pairs together
Handle cases where the number of nodes is not a multiple of n
To check if a singly linked list is a palindrome, reverse the second half and compare it with the first half.
Traverse the linked list to find the middle node
Reverse the second half of the linked list
Compare the reversed second half with the first half to check for palindrome
Given a preorder of binary tree with leaf nodes represented by N, construct the tree.
Start by creating an empty stack.
Iterate through the preorder list.
If the current element is N, create a leaf node and push it onto the stack.
If the current element is not N, create a new node and set its left child to the top of the stack.
Pop the top of the stack and set it as the right child of the new node.
Push the new node onto the...
The question asks to find the maximum occupancy word in each line of a given multiline string and also count the occupancy of capital and small letters separately.
Split the multiline string into individual lines
For each line, split it into words
Initialize variables to store the maximum occupancy word and its count
Iterate through each word and count the occupancy of each letter
If the current word has a higher occupancy ...
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