Tata 1mg Software Engineer Interview Questions and Answers

Round duration - 60 Minutes
Round difficulty - Easy

Q1. 
0/1 Knapsack Problem Statement
A thief is planning to rob a store and can carry a maximum weight of 'W' in his knapsack. The store contains 'N' items where the ith item has a weight of 'wi' and a value of...read more
Ans. 
Yes, the 0/1 Knapsack problem can be solved using dynamic programming with a space complexity of not more than O(W).
• Use a 1D array to store the maximum value that can be stolen for each weight capacity from 0 to W.

• Iterate through each item and update the array based on whether including the item would increase the total value.

• The final value in the array at index W will be the maximum value that can be stolen.
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Q2. 
Find the Second Largest Element
Given an array or list of integers 'ARR', identify the second largest element in 'ARR'.
If a second largest element does not exist, return -1.
Example:
Input:
ARR = [2,...read more
Ans. 
Find the second largest element in an array of integers.
• Iterate through the array to find the largest and second largest elements.

• Handle cases where all elements are identical.

• Return -1 if a second largest element does not exist.
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Round duration - 60 Minutes
Round difficulty - Easy

System Design Round

Q1. Design a system for Twitter, discussing its architecture, key components, and scalability considerations.
Ans. 
Design a scalable system for Twitter with key components and architecture.
• Use microservices architecture for scalability and fault isolation.

• Key components include user service, tweet service, timeline service, and notification service.

• Use a distributed database like Cassandra for storing tweets and user data.

• Implement a message queue like Kafka for handling real-time updates and notifications.

• Use a caching layer like ...read more
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Round duration - 30 Minutes
Round difficulty - Easy

It is just a formality

Basic coding only not to worry much

Q1. Tell me about ur self
Ans. 
I am a passionate software developer with experience in Java, Python, and web development.
• Experienced in Java, Python, and web development technologies

• Strong problem-solving skills

• Excellent team player with good communication skills
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Q2. What is ur projects
Ans. 
I have worked on various projects including a web-based inventory management system and a mobile app for tracking fitness goals.
• Developed a web-based inventory management system using React and Node.js

• Created a mobile app for tracking fitness goals using Flutter

• Implemented RESTful APIs for communication between frontend and backend systems
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The exam duration is one and a half hours.

The total exam time is one and a half hours.

It encompasses all topics related to full stack development.

Q1. Asks questions on SQL
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Q2. Asks question in typical topics
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Q1. Where do you see yourself in two years?
Ans. 
In two years, I see myself as a senior software developer leading a team on innovative projects.
• Advancing to a senior software developer role

• Leading a team on new and innovative projects

• Continuing to enhance my technical skills through ongoing learning and training
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There were 2 questions.
1. Knapsack
2. Median in an array

Q1. LLD(machine coding) of Google meet
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Q1. In depth discussion on my projects and resume
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Q1. It was lld question to design a cab booking system.
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Q2. Tell me about yourself
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3 coding question
2 medium 1 hard

Q1. Online polling system based on OOPs
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Q2. Explaining the above code
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3 Medium level dsa questions

Q1. Lld of cab booking system
Ans. 
The Low Level Design (LLD) of a cab booking system involves detailing the system architecture and components at a lower level of abstraction.
• Identify the main components of the system such as user interface, booking engine, payment gateway, and driver allocation algorithm.

• Define the interactions between these components and how data flows between them.

• Specify the data structures and algorithms used for efficient bookin...read more
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Q2. Discussion about online assesment
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Q1. Implementation of LRU cache
Ans. 
LRU cache is a data structure that stores the most recently used items, discarding the least recently used items when full.
• Use a doubly linked list to keep track of the order of items based on their usage.

• Use a hash map to quickly access items in the cache.

• When a new item is accessed, move it to the front of the linked list. If the cache is full, remove the item at the end of the list.
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Q2. Implementation of HashMap
Ans. 
HashMap is a data structure that stores key-value pairs and allows for fast retrieval of values based on keys.
• HashMap is implemented using an array of linked lists or a balanced tree to handle collisions.

• It uses a hash function to map keys to indices in the array.

• Example: HashMap map = new HashMap<>(); map.put("key", 123); int value = map.get("key");
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