EatClub Software Development Engineer Intern Interview Questions and Answers

There were 2 questions, first one was the three sum problem of leetcode and the second one was related to stacks amd strings

Q1. What is encapsulation in OOP?
Ans. 
Encapsulation is the concept of bundling data and methods together within a class, hiding internal details from the outside world.
• Encapsulation helps in achieving data abstraction and data hiding.

• It allows for better control over the access to the internal state of an object.

• By encapsulating data, we can protect it from being modified by external code.

• Encapsulation promotes code reusability and maintainability.

• Example:...read more
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Find min and max in an array

OA test 3 Dsa questions 2 medium 1 hard you have to solve 1.5 questions in 120 minutes

Q1. DSA Round Astreoid collision leetcode
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Q2. Dp question based on exclusion and inclusion
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DSA 2 question
1 -> Find Lca and traverse a tree path available on GFG
2 -> LinkedList pallindrome check (you have to solve that in 0(1) space complexity)

Q1. LRU Cache - how to tackle
Ans. 
LRU Cache is a data structure that maintains a list of items in order of most recently used to least recently used.
• Implement using a doubly linked list and a hashmap for efficient operations

• When an item is accessed, move it to the front of the list

• When the cache is full, remove the least recently used item from the end of the list
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Q2. LRU Cache implementation based on a real time system. How would the main work which will be called etc etc
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Q1. What is ambitionbox
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Q2. How many questions are there in that
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Q1. Same as above questions
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Q2. Same as above questions second one
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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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3 coding questions, medium

Q1. Related to string and prefix sum
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Q2. How priority queue works and its implementation using min heap
Ans. 
Priority queue is a data structure that stores elements based on their priority, allowing for efficient retrieval of the highest priority element.
• Priority queue can be implemented using a min heap, where the root node always contains the minimum element.

• Insertion: Add the new element to the end of the heap and then heapify up to maintain the min heap property.

• Deletion: Remove the root node (minimum element), move the l...read more
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