nurture.farm interview experience Real time questions & tips from candidates to crack your interview
SDE - 1
nurture.farm
2 rounds | 4 Coding
problems
Rejected
Interview preparation journey
Journey
Being from a tier-3 college, I got no opportunities in college as there was no coding culture. I ended up starting my career in a service-based company, where I worked for two years. I worked hard to secure multiple offers and ultimately chose Microsoft from them.
Application story
There was an opening on LinkedIn for the role of Backend Engineer at Nurture.farm. I applied for the opening and received a test link from HR. After that, she scheduled interviews for me.
Why selected/rejected for the role?
Rejected. Interview round 2 did not go as I expected. I was unable to answer some of the questions asked by the interviewer.
Preparation
Duration: 4 months
Topics: Data structures, Algorithms, OOPS, OS, DBMS, Computer Networks, System Design
Tip 1: Make sure your computer science fundamentals are crystal clear.
Tip 2: You should know the time complexity of the code you write and understand the internal implementation of the data structures you use while coding.
Tip 3: Be well-versed in everything you mention on your resume.
Tip 4: Practice solving a lot of programming problems and participate in competitive programming contests.
Application process
Where: Linkedin
Eligibility: B.Tech. in Computer Science
Tip 1: Be honest about what you write in your resume.
Tip 2: Include at least two projects.
Tip 3: Maintain a precise, self-explanatory one-page resume.
Tip 4: Add only technical achievements.
Interview rounds
01
Round
Medium
Video Call
Duration75 minutes
Interview date24 Mar 2022
Coding problem2
The interviewer immediately shared a document with two coding questions and gave me some time to think, followed by a discussion.
1. Bursting Balloons
Moderate
40m average time
60% success
0/80
Asked in companies
You are given an array 'ARR' of N integers. Each integer represents the height of a balloon. So, there are N balloons lined up.
Your aim is to destroy all these balloons. Now, a balloon can only be destroyed if the player shoots its head. So, to do the needful, he/ she shoots an arrow from the left to the right side of the platform, from an arbitrary height he/she chooses. The arrow moves from left to right, at a chosen height ARR[i] until it finds a balloon. The moment when an arrow touches a balloon, the balloon gets destroyed and disappears and the arrow continues its way from left to right at a height decreased by 1. Therefore, if the arrow was moving at height ARR[i], after destroying the balloon it travels at height ARR[i]-1. The player wins this game if he destroys all the balloons in minimum arrows.
You have to return the minimum arrows required to complete the task.
Problem approach
- Since we need a smaller window's answer for larger windows, we must store the answer for a window of each size from 1 to n.
- Then, we will have two pointers, left and right, pointing to the two ends of our current window. For example, if we have the array [1,1,2,3,4,5,1] and need to get the answer for the subarray [2,3,4], then left will point to index 2 and right to index 4.
- Now, within the current window, we must burst the balloons in such a sequence that we obtain the maximum value. To achieve this, we need to check each balloon in the window to determine whether bursting it last yields the maximum value.
- For this, we traverse the window from left to right, calculating the value each time under the assumption that the i-th balloon is burst last.
- Thus, while filling the DP table, we populate values for windows in a left-to-right manner. i.e.,
dp[left][right] = Max(already calculated value, burst this ith balloon last and add left and right subarray points within the window)
dp[left][right] = max(dp[left][right], arr[left-1] * arr[i] * arr[right+1] + dp[left][i-1] + dp[i+1][right])
2. LRU Cache
Moderate
0/80
Asked in companies
Design a data structure that satisfies the constraints of a Least Recently Used (LRU).
1. Get(int num): If the key exists, it will return the value of the key stored. Else, return -1.
2. Put(int key, int value): If the key already exists, update the value of the key. Else add the key-value pair to the cache. If the number of keys is more than the capacity for this operation, delete the least recently key used.
Example:
For the following input:
4 2
2 1 4
1 1
1 4
We will initialize an empty LRU cache for the first operation with a maximum capacity of 2.
For the first operation, we need to add a key-value pair (1,4) to the cache.
For the second operation, we need to return the value stored for key 1, i.e., 4
For the third operation, we need to return -1, as we don't have any key 4 in the cache.
So, the final output will be:
4 -1
Problem approach
- Since we need a smaller window's answer for larger windows, we have to store the answer for each window size from 1 to n.
- Then, we will use two pointers, left and right, to indicate the two ends of our current window. For example, if we have the array [1,1,2,3,4,5,1] and we need to get the answer for the subarray [2,3,4], then left will point to index 2, and right will point to index 4.
- Now, within the current window, we need to burst the balloons in such a sequence that we obtain the maximum value. To achieve this, we check for each balloon in the window whether it yields the maximum value when burst last.
- For this, we traverse from left to right within the window and, at each step, calculate the value assuming the i-th balloon is burst last.
- Thus, while filling DP, we will compute values for increasing window sizes from left to right.
dp[left][right] = Max(already calculated value, burst this ith balloon last and add left and right subarray points within the window)
dp[left][right] = max(dp[left][right], arr[left-1] * arr[i] * arr[right+1] + dp[left][i-1] + dp[i+1][right])
02
Round
Hard
Video Call
Duration75 minutes
Interview date31 May 2023
Coding problem2
The interview was primarily focused on development skills and system design (which I was not prepared for). The interviewer also asked one coding question.
1. System Design
Design a Restaurant Management System.
Problem approach
Tip 1: Prepare for System Design questions.
Tip 2: Prepare for previously asked questions.
2. Maximum Sum
Moderate
25m average time
75% success
0/80
Asked in companies
You are given an array ‘arr’ consisting of ‘N’ integers. Your task is to maximize the value of 0 * arr[0] + 1 * arr[1] + 2 * arr[2] … (N - 1) * arr[N - 1] . You can rotate the array as many times as you wish.
For Example:
For the given arr[ ] = { 1, 2, 3, 1}
After 0 rotation arr[ ] = { 1, 2, 3, 1} the sum is = (0 *1 + 1 * 2 + 2 * 3 + 3 * 1) = 11.
After 1 rotation arr[ ] = { 1, 1, 2, 3} the sum is = (0 *1 + 1 * 1 + 2 * 2 + 3 * 3) = 14.
After 2 rotation arr[ ] = { 3, 1, 1, 2} the sum is = (0 *3 + 1 * 1 + 2 * 1 + 3 * 2) = 9.
After 3 rotation arr[ ] = { 2, 3, 1, 1} the sum is = (0 *2 + 1 * 3 + 2 * 1 + 3 * 1) = 8.
So the maximum sum is 14 when arr[ ] = { 1, 1, 2, 3}.
Problem approach
- Traverse the array once and keep updating the frequency of its elements in the map.
- Check whether the size of the map is equal to the total number of distinct elements present in the original array. If true, update the maximum sum.
- While traversing the original array, if the i-th traversal exceeds K elements, update the map by deleting an occurrence of the (i – K)-th element.
- After completing the above steps, print the maximum sum obtained.
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