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I appeared for an interview before Mar 2024.
It was years ago so don't know if it is still relevant or not. But still, aptitude test was copy paste questions from online sources random questions about cs field.
Run time polymorphism occurs during program execution, while compile time polymorphism is resolved during code compilation.
Compile time polymorphism is achieved through method overloading and operator overloading.
Example of compile time polymorphism: Method overloading in Java.
Run time polymorphism is achieved through method overriding.
Example of run time polymorphism: Using virtual functions in C++.
Quick sort is an efficient sorting algorithm that uses a divide-and-conquer approach to sort elements in an array.
1. Choose a pivot element from the array (e.g., the last element).
2. Partition the array into two sub-arrays: elements less than the pivot and elements greater than the pivot.
3. Recursively apply the same process to the sub-arrays.
4. Base case: If the array has one or zero elements, it is already sorted.
Exa...
I applied via LinkedIn and was interviewed in Aug 2023. There were 3 interview rounds.
Create a model to predict price.
I applied via Approached by Company and was interviewed before Oct 2022. There were 2 interview rounds.
I applied via Referral and was interviewed before Jan 2021. There was 1 interview round.
I applied via Campus Placement and was interviewed before May 2021. There were 2 interview rounds.
Numerical ability and logical reasoning followed by some coding mcqs
Printing 1 to 100 without for loop
Use recursion to print numbers from 1 to 99
Print 100 outside the recursion
Use a base case to stop recursion at 100
I applied via Campus Placement and was interviewed before Jun 2021. There were 2 interview rounds.
Simple aptitude test
I applied via Recruitment Consultant and was interviewed before Jul 2020. There was 1 interview round.
I applied via Naukri.com
I applied via Newspaper Ad and was interviewed before Jun 2021. There were 3 interview rounds.
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)
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