CARS24 Software Developer Interview Questions and Answers

Q1. Explain Deadlock?
Ans. 
Deadlock is a situation in computing where two or more processes cannot proceed because each is waiting for the other to release resources.
• Occurs in multi-threaded environments when processes hold resources and wait for others.

• Example: Process A holds Resource 1 and waits for Resource 2, while Process B holds Resource 2 and waits for Resource 1.

• Can lead to system inefficiency and unresponsiveness.

• Deadlock detection and...read more
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Q2. Explain Red Black Tree?
Ans. 
A Red-Black Tree is a balanced binary search tree with specific properties to ensure efficient operations.
• Each node is colored either red or black.

• The root node is always black.

• Red nodes cannot have red children (no two reds in a row).

• Every path from a node to its descendant leaves must have the same number of black nodes.

• This structure ensures O(log n) time complexity for insertion, deletion, and search operations.

• Exa...read more
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Q3. Find local minima in a 1-D array?
Ans. 
Local minima in a 1-D array are elements smaller than their neighbors. Identify them using comparisons.
• A local minimum at index i satisfies: arr[i] < arr[i-1] and arr[i] < arr[i+1].

• Example: In [9, 6, 3, 4, 5], 3 is a local minimum.

• Boundary cases: For the first element, compare only with the second; for the last, compare only with the second last.

• Example: In [1, 2, 3], 1 is a local minimum since it has no left nei...read more
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Q4. Find local minima in 2-D array?
Ans. 
Local minima in a 2-D array are elements smaller than their neighbors. We can find them using various algorithms.
• A local minimum is defined as an element that is less than its adjacent elements.

• For example, in the array [[9, 8, 7], [6, 5, 4], [3, 2, 1]], the element 1 is a local minimum.

• To find local minima, iterate through each element and compare it with its neighbors (up, down, left, right).

• Consider edge cases where...read more
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Easy level to Medium level

2 Easy questions of DSA

Q1. One DSA question
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Q2. Normal discussion about tech stack
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Q1. Tell about yourself
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Q2. Why do you want to join digit?
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Duration 1Hr
2 coding questions

Q1. Don't remember the questions
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Q2. Don't remember the questions.
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Round duration - 60 Minutes
Round difficulty - Medium

It has 3 Coding Questions of medium-hard level and the time limit was 1 hour only. I don’t exactly remember the questions but I was able to do only two of them completely.

Q1. 
Biggest Number Formation Problem
Your task is to construct the largest number possible by concatenating each of the provided positive integers in the array exactly once.
Input:
Integer T denoting the nu...read more
Ans. 
Construct the largest number by concatenating positive integers in the array exactly once.
• Sort the array of integers in a way that the concatenation of the numbers forms the largest possible number.

• Use a custom comparator function to sort the numbers based on their concatenated values.

• Join the sorted array elements to form the final largest number.
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Q2. 
Number of Longest Increasing Subsequence Problem Statement
Given an integer array ARR of length N, determine the count of longest increasing subsequences present in the array.
Explanation:
The Longest I...read more
Ans. 
Count the number of longest increasing subsequences in an integer array.
• Identify the longest increasing subsequences in the array

• Count the number of such subsequences

• Consider the constraints while implementing the solution

• Examples: For input [50, 3, 90, 60, 80], the output is 2
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Round duration - 60 Minutes
Round difficulty - Medium

First, the interviewer introduced himself and then asked to introduce myself. Then he asked about the projects I did. After an introductory discussion on projects, he gave me 3 coding questions on their personal live code environment.

He asked me to explain the approach first and then code it down. I had to explain the time complexity of each solution and optimal code if possible with lesser time complexity.

Q1. 
Cache Operations Problem
You are provided with a cache that can hold a maximum of 'N' elements. Initially, this cache is empty. There are two main operations you can perform on this cache:
Explanation:
...read more
Ans. 
Implement a cache with insert, update, and retrieve operations, returning results of retrieve operations in order.
• Create a cache data structure with specified size 'N'.

• Implement insert and update operations based on the given criteria.

• For retrieve operation, return the value associated with the 'U_ID' if present, else return -1.

• Handle cases where the cache is full and least frequently used items need to be removed.

• Retu...read more
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Q2. 
Possible Words from a Phone Number: Problem Statement
Given a string S composed of digits ranging from 2 to 9, determine all possible strings that can be created by mapping these digits to their correspon...read more
Ans. 
Given a phone number, generate all possible words by mapping digits to letters on a T9 keypad.
• Create a mapping of digits to letters on a T9 keypad

• Use recursion to generate all possible combinations of letters for the given phone number

• Sort the resulting strings in lexicographical order
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Q3. 
Shortest Unique Prefix Problem
You are given an array containing N words. Your task is to derive the shortest prefix for each word that uniquely identifies it amongst the other words. For instance, given t...read more
Ans. 
Given an array of words, find the shortest unique prefix for each word.
• Create a Trie data structure to efficiently store and search for prefixes.

• Traverse the Trie to find the shortest unique prefix for each word.

• Return the list of shortest unique prefixes for all words.
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Round duration - 60 Minutes
Round difficulty - Hard

In this round interviewer gave me 2 coding questions and asked me to code on any editor of my choice. I opened VS code to code those problems.

Q1. 
Maximum Subarray Sum Problem Statement
Given an array arr of length N consisting of integers, find the sum of the subarray (including empty subarray) with the maximum sum among all subarrays.
Explanation...read more
Ans. 
Find the sum of the subarray with the maximum sum among all subarrays in a given array.
• Iterate through the array and keep track of the maximum sum subarray seen so far.

• Use Kadane's algorithm to efficiently find the maximum subarray sum.

• Handle cases where all elements are negative by returning the maximum element in the array.

• Consider the sum of an empty subarray as 0.
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Q2. 
LRU Cache Implementation
Design and implement a data structure for the Least Recently Used (LRU) cache, which supports the following operations:
1. get(key) - Return the value associated with the key if ...read more
Ans. 
Implement a Least Recently Used (LRU) cache data structure with get and put operations.
• Use a combination of a hashmap and a doubly linked list to efficiently implement the LRU cache.

• Keep track of the least recently used item and remove it when the cache reaches its capacity.

• Update the position of an item in the cache whenever it is accessed or updated.

• Ensure constant time complexity for both get and put operations by u...read more
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Round duration - 40 Minutes
Round difficulty - Easy

The interviewer was very friendly. He asked me about myself and previous interviews.