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I applied via Job Portal and was interviewed in Mar 2024. There was 1 interview round.
Good discussion there are 10 people and we got topic emerging use of technology in training the staff
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)
I applied via Naukri.com and was interviewed in May 2019. There were 4 interview rounds.
I applied via Company Website and was interviewed in May 2019. There were 4 interview rounds.
Implemented a new customer feedback system that increased customer satisfaction by 20%
Implemented a new customer feedback system to gather insights and improve customer experience
Analyzed feedback data to identify common issues and areas for improvement
Implemented changes based on feedback to address customer concerns and enhance overall satisfaction
Trained team members on how to effectively use the new system and inte...
I applied via Naukri.com
I applied via Recruitment Consultant and was interviewed before Jul 2020. There was 1 interview round.
Function to return mutual friends given two ids and getFriends(id) function
Call getFriends(id) for both ids to get their respective friend lists
Iterate through both lists and compare to find mutual friends
Return the list of mutual friends
Function to return list of friends of friends in decreasing order of mutual friends
Use a set to store all friends of friends
Iterate through the list of friends of the given id
For each friend, iterate through their list of friends and count mutual friends
Sort the set of friends of friends by decreasing number of mutual friends
Given time slots, find a specific time with maximum overlap. Prove solution.
Create a list of all start and end times
Sort the list in ascending order
Iterate through the list and keep track of the number of overlaps at each time
Return the time with the maximum number of overlaps
Prove solution by testing with different input sizes and edge cases
Find the longest sub-array with increasing order of integers.
Iterate through the array and keep track of the current sub-array's start and end indices.
Update the start index whenever the current element is smaller than the previous element.
Update the end index whenever the current element is greater than or equal to the next element.
Calculate the length of the sub-array and compare it with the longest sub-array found s
Find the length of longest increasing subsequence and print the sequence from an array of integers.
Use dynamic programming to solve the problem
Create an array to store the length of longest increasing subsequence ending at each index
Traverse the array and update the length of longest increasing subsequence for each index
Print the sequence by backtracking from the index with the maximum length
Time complexity: O(n^2)
Exam...
Code to find a given integer in a rotated sorted array.
Use binary search to find the pivot point where the array is rotated.
Divide the array into two subarrays and perform binary search on the appropriate subarray.
Handle edge cases such as the target integer not being present in the array.
Use a min-heap to keep track of the largest K numbers seen so far.
Create a min-heap of size K.
For each incoming integer, add it to the heap if it's larger than the smallest element in the heap.
If the heap size exceeds K, remove the smallest element.
At the end, the heap will contain the largest K numbers in the input.
LRU Cache is a data structure that stores the most recently used items and discards the least recently used items.
Use a doubly linked list to keep track of the order of items in the cache
Use a hash map to store the key-value pairs for fast access
When an item is accessed, move it to the front of the linked list
When the cache is full, remove the least recently used item from the back of the linked list and the hash map
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