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I applied via Referral and was interviewed in Apr 2021. There were 4 interview rounds.
2 variable variation of LIS
The problem involves finding the longest increasing subsequence in two arrays
Dynamic programming can be used to solve the problem
The time complexity of the solution is O(n^2)
Example: Given two arrays [1, 3, 5, 4] and [2, 4, 3, 5], the longest increasing subsequence is [3, 5]
Example: Given two arrays [10, 22, 9, 33, 21, 50, 41, 60] and [5, 24, 39, 60, 15, 28, 27, 40], the longest increasing su
Search for an element in a rotated sorted array.
Use binary search to find the pivot point where the array is rotated.
Compare the target element with the first element of the array to determine which half to search.
Perform binary search on the selected half to find the target element.
Time complexity: O(log n), Space complexity: O(1).
Find the first non-repeating character in a continuous character stream.
Use a hash table to keep track of character frequency.
Iterate through the stream and check if the current character has a frequency of 1.
If yes, return the character as the first non-repeating character.
If no non-repeating character is found, return null or a default value.
I applied via Campus Placement and was interviewed in Jul 2022. There was 1 interview round.
Given a node in a family tree, print all nodes on the same level.
Traverse the tree level by level using BFS
Keep track of the level of each node while traversing
Print all nodes with the same level as the given node
Example: If the given node is 'John', print all his siblings and cousins
I applied via LinkedIn and was interviewed in Jul 2022. There were 2 interview rounds.
Prepare from hackerrank array and trees problems
1. Question on Graph LC-Hard 2. Question on BFS LC-Medium
Find missing number in array without extra space
Iterate through the array and XOR all the elements with their indices and the actual numbers
The missing number will be the XOR result
Example: ['1', '2', '4', '5'] -> XOR(0, 1) ^ XOR(1, 2) ^ XOR(2, 4) ^ XOR(3, 5) = 3
Implementing Heap data structure in C++
Use an array to represent the binary tree structure of the heap
Implement functions for inserting elements, deleting elements, and heapifying the array
Ensure that the heap property is maintained (parent node is always greater than or equal to its children)
LRU Cache is a data structure that stores a fixed number of items and removes the least recently used item when the cache is full.
Use a combination of a doubly linked list and a hashmap to efficiently implement LRU Cache.
Keep track of the least recently used item at the tail of the linked list.
When an item is accessed, move it to the head of the linked list to mark it as the most recently used item.
When adding a new it...
I applied via Campus Placement and was interviewed before Dec 2023. There were 3 interview rounds.
Coding test on Amazon own website
I applied via Company Website and was interviewed in Jan 2022. There were 2 interview rounds.
Asked 2 questions
1. Find the strings with maximum pattern match in given array of strings
2. Find the shortest distance between two target elements in given array
I applied via Referral and was interviewed before Mar 2022. There were 4 interview rounds.
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