Demandbase Senior Software Engineer Interview Questions and Answers

Q1. Full day exam on saturday
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Q2. Coding related, dsa, aptitude etc
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Based on concepts and past experience

Q1. Minimum element in an array
Ans. 
Find the minimum element in an array of strings
• Iterate through the array and compare each element to find the minimum

• Use built-in functions like Math.min() or sort() to find the minimum

• Handle edge cases like empty array or array with only one element
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Q2. Reverse a linked list
Ans. 
Reverse a linked list by changing the next pointers of each node
• Iterate through the linked list and change the next pointers to reverse the list

• Use three pointers - prev, current, and next to keep track of nodes

• Example: 1 -> 2 -> 3 -> 4 -> null, after reversing: 4 -> 3 -> 2 -> 1 -> null
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Q1. Java8 and multhithreading based questions
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Q2. 1 Leetcode easy question
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Q1. TDD based live coding and spring based question
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Q2. 1 leetcode medium question
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Q1. Salary negotiations and company fit based questions
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Q1. To do list design
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Q1. Project related
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Q1. Famous Java Questions like why string is immuatable and basics of OOPs.
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Q2. Easy to medium level DSA based on array and string.
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Q1. Project Related Questions
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Q2. Questions related to java 8 stream API
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Q1. Question related to basic recursion
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Q2. Top kafka interview questions
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Q1. Telecome domain related questions along with Unix shell scripting and SQL database question .
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Round duration - 120 minutes
Round difficulty - Easy

After round 1 there was a break of 15 mins and the coding round started.
We had a choice to attempt the exam in R language & SQL or python & sql
I chose python and sql
It had 8 questions 4 python and 4 sql

Q1. 
Longest Common Subsequence Problem Statement
Given two strings, S and T with respective lengths M and N, your task is to determine the length of their longest common subsequence.
A subsequence is a seque...read more
Ans. 
The task is to find the length of the longest common subsequence between two given strings.
• Use dynamic programming to solve this problem efficiently.

• Create a 2D array to store the lengths of longest common subsequences of substrings.

• Iterate through the strings to fill the array and find the length of the longest common subsequence.

• Example: For strings 'abcde' and 'ace', the longest common subsequence is 'ace' with leng
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Round duration - 15 minutes
Round difficulty - Medium

The interview was mostly analytical based and how you approach the round a few technical questions in dbms and oops were also asked.

Round duration - 20 Minutes
Round difficulty - Medium

Similar to first round
For Shortlists after elimination from first round.

Q1. 
Car Pooling Capacity Problem
You are a cab driver with a car that initially has 'C' empty seats. The car moves in a straight line towards the forward direction only. Your job is to determine if it is poss...read more
Ans. 
Determine if it is possible to accommodate all passenger trips within a car's capacity without exceeding it at any point.
• Iterate through each trip and keep track of the total number of passengers in the car at each point.

• Check if the total number of passengers exceeds the car capacity at any point.

• Return 'True' if all trips can be accommodated within the car capacity, otherwise return 'False'.
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Round duration - 20 minutes
Round difficulty - Easy

After two technical round interviews, the last round was a hr interview. The whole process can take up one whole day or more and your interview can be at any time
My process started at 5 pm and ended at 10:30 pm
All the interviewers were very friendly no pressure.

Q1. 
Nth Fibonacci Number Problem Statement
Calculate the Nth term in the Fibonacci sequence, where the sequence is defined as follows: F(n) = F(n-1) + F(n-2), with initial conditions F(1) = F(2) = 1.
Input:
...read more
Ans. 
Calculate the Nth Fibonacci number efficiently using dynamic programming.
• Use dynamic programming to store previously calculated Fibonacci numbers to avoid redundant calculations.

• Start with base cases F(1) and F(2) as 1, then iterate to calculate subsequent Fibonacci numbers.

• Time complexity can be optimized to O(N) using dynamic programming.

• Example: For N = 5, the 5th Fibonacci number is 5.
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