MindTickle Software Developer Interview Questions and Answers

Q1. Design LLD for Parking Lot
Ans. 
Design LLD for Parking Lot
• Create classes for ParkingLot, ParkingSpot, Vehicle, etc.

• Implement methods for parking, unparking, checking availability, etc.

• Consider different types of vehicles and parking spots (e.g. regular, handicapped, electric)

• Include features like ticketing system, payment processing, and security measures
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Round duration - 50 minutes
Round difficulty - Medium

First round was a basic javascript problem-solving round. The interviewer judged my grasp on fundamental javascript concepts like objects, closures, polyfills, etc. It was during the afternoon and was conducted on google meet and leetcode playground.
The interviewer was very calm. I was first asked some general questions like why I'm applying for this role and what are the projects I've done.

Q1. 
Search in a Row-wise and Column-wise Sorted Matrix Problem Statement
You are given an N * N matrix of integers where each row and each column is sorted in increasing order. Your task is to find the positi...read more
Ans. 
This question asks to find the position of a target integer in a row-wise and column-wise sorted matrix.
• Iterate through each row and column of the matrix

• Compare the target integer with the current element

• If the target integer is found, return the position as {i, j}

• If the target integer is not found, return {-1, -1}
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Round duration - 40 minutes
Round difficulty - Easy

One DSA Question along with some javascript questions were asked like hoisting, difference between JSX and Javascript etc.

Q1. 
Trapping Rain Water Problem Statement
You are given a long type array/list ARR of size N, representing an elevation map. The value ARR[i] denotes the elevation of the ith bar. Your task is to determine th...read more
Ans. 
The question asks to find the total amount of rainwater that can be trapped in the given elevation map.
• Iterate through the array and find the maximum height on the left and right of each bar.

• Calculate the amount of water that can be trapped at each bar by taking the minimum of the maximum heights on the left and right.

• Sum up the trapped water for all bars and return the total amount.
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Round duration - 45 Minutes
Round difficulty - Easy

It was a DSA round where I was asked 2 coding questions and optimised approaches for both.

Q1. 
Ninja and His Meetings Problem Statement
Ninja has started a new startup with a single conference room available for meetings. Given an array/list MEETINGS of consecutive appointment requests, Ninja must ...read more
Ans. 
Find the maximum total booked minutes possible in a conference room for all meetings with a 15-minute break between meetings.
• Iterate through the list of meeting durations and calculate the maximum total booked minutes considering the 15-minute break constraint.

• Keep track of the total booked minutes and skip consecutive meetings that violate the break constraint.

• Return the maximum total booked minutes for each test case...read more
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Q2. 
Trapping Rain Water II Problem Statement
Given an M * N matrix where each cell's value represents its height in a 2-D elevation map, calculate the total volume of water that can be trapped after rainfall.
...read more
Ans. 
Calculate the total volume of water that can be trapped in a 2-D elevation map after rainfall.
• Iterate through each cell in the matrix and calculate the trapped water based on the surrounding heights.

• Use a stack or queue to keep track of the cells to be processed.

• Consider edge cases such as when the matrix is empty or has only one row or column.
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Round duration - 45 Minutes
Round difficulty - Medium

It was more of discussion around my projects and resume. Also asked some questions related to me. What are your hobbies? Willing to relocate?

Q1. 
Smallest Subarray With K Distinct Elements
Given an array A consisting of N integers, your task is to find the smallest subarray of A that contains exactly K distinct integers.
If multiple such subarrays...read more
Ans. 
Find the smallest subarray with exactly K distinct elements in an array.
• Use a sliding window approach to keep track of the subarray with K distinct elements.

• Maintain a hashmap to count the frequency of each element in the window.

• Update the window size based on the number of distinct elements.

• Return the smallest subarray with K distinct elements.
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