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I applied via Approached by Company and was interviewed before Sep 2022. There were 4 interview rounds.
I applied via Approached by Company and was interviewed before Oct 2022. There were 4 interview rounds.
Design an API rate limiter to control the number of requests a user can make within a certain time frame.
Implement a token bucket algorithm to track and limit the number of requests per user.
Set a maximum limit of requests per user per time frame (e.g. 100 requests per hour).
Use a sliding window to track the requests and reset the limit after the time frame expires.
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I applied via Referral and was interviewed in Sep 2023. There was 1 interview round.
Merge two sorted linked lists into a single sorted linked list
Create a new linked list to store the merged result
Iterate through both input linked lists and compare nodes to determine the order in which they should be merged
Update the next pointers of the nodes in the new linked list accordingly
I applied via Referral and was interviewed in Jan 2024. There were 4 interview rounds.
Machine Coding of Google Calendar
Machine Coding of MP3 Player
Find duplicates in an array of strings
Iterate through the array and store each element in a hash set
If an element is already in the hash set, it is a duplicate
Return a list of all duplicates found
Simpl offers a collaborative and innovative work environment with competitive compensation.
Simpl values teamwork and creativity in software development
Competitive compensation package offered to attract top talent
Opportunities for growth and learning through challenging projects
It was good , 2 questions are there to code.
Using a map to manipulate strings can simplify tasks like counting characters or finding duplicates efficiently.
Use a HashMap to count occurrences of each character in a string. Example: 'hello' -> {'h': 1, 'e': 1, 'l': 2, 'o': 1}.
To find duplicates, iterate through the map and collect characters with a count greater than 1. Example: 'banana' -> ['a', 'n'].
Maps can also be used to store transformations, like mapp...
React Router is a popular routing library for React applications.
React Router is used for handling navigation in React applications.
It allows defining multiple routes in the application and rendering different components based on the URL.
React Router provides components like BrowserRouter, Route, Switch, and Link for routing.
Example:
I applied via Approached by Company and was interviewed before Oct 2023. There were 2 interview rounds.
A simple Google form assignment to shortlist candidates
Use a hash set to find duplicates in an array of strings.
Create a hash set to store unique elements.
Iterate through the array and check if each element is already in the hash set.
If it is, then it is a duplicate.
Example: ['apple', 'banana', 'apple', 'orange'] should return 'apple' as a duplicate.
I appeared for an interview before Feb 2024.
It was an assignment where we were instructed to create a screen that fetches data from the backend and renders it with the functionality of bookmarking.
I applied via Campus Placement and was interviewed in Mar 2023. There were 4 interview rounds.
A Google Form-based Aptitude Test with Basic Questions
It was the final round asked to do a medium-level coding Question to convert a number such as 244 to word i.e Two Hundred and Forty four
posted on 14 Jun 2025
I appeared for an interview in May 2025, where I was asked the following questions.
I applied via Campus Placement and was interviewed before Jul 2022. There were 5 interview rounds.
50 questions in 12 minutes mostly test your arthimetic, logical knowledge.
3 coding questions in 90 mins, 1st one is from arrays an easy question, 2nd one is related to stacks and queues relatively harder and last one is hard which i am also unable to attempt. I cracked the first two questions and my solutions passed all the test cases.
Sorting algorithms are methods used to arrange elements in a specific order.
Different sorting algorithms include bubble sort, selection sort, insertion sort, merge sort, quick sort, and heap sort.
Some algorithms are more efficient than others depending on the size of the data set and the initial order of the elements.
For example, quick sort is generally faster than bubble sort for large data sets.
BFS and DFS are traversal algorithms used in trees. BFS explores level by level, while DFS explores depth first.
BFS (Breadth-First Search) visits nodes level by level, using a queue. Example: traversing a binary tree level by level.
DFS (Depth-First Search) explores as far as possible along each branch before backtracking. Example: in-order traversal of a binary tree.
based on 3 interview experiences
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