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I applied via campus placement at National Institute of Technology,(NIT), Delhi and was interviewed in Jul 2023. There were 5 interview rounds.
In this round 2 basic coding question was there along with few mcqs.
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I applied via Naukri.com
Replication of databases involves copying and maintaining multiple copies of the same database for redundancy and fault tolerance.
Replication helps in ensuring high availability and fault tolerance by having multiple copies of the same data.
There are different types of replication such as master-slave replication, master-master replication, and multi-master replication.
Replication can be synchronous or asynchronous, wi...
There were three coding questions.
I applied via Job Fair and was interviewed in Dec 2024. There were 3 interview rounds.
OA test 3 Dsa questions 2 medium 1 hard you have to solve 1.5 questions in 120 minutes
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)
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
I applied via Campus Placement
2 coding questions and a few MCQs
I applied via Job Portal and was interviewed in Aug 2024. There were 2 interview rounds.
DSA + JAVA + Spring boot
LLD (bookmyshow) + DSA
What is your name write it in binary format using Ensemble language and how to optimize super computer
Use merge sort algorithm to sort the array in O(nlogn) time complexity.
Implement merge sort algorithm which divides the array into two halves, recursively sorts the halves, and then merges the sorted halves.
Time complexity of merge sort is O(nlogn) where n is the number of elements in the array.
Example: ['apple', 'banana', 'cherry', 'date'] can be sorted using merge sort in O(nlogn) time complexity.
Use binary search to find element in sorted array efficiently.
Start with middle element and compare with target
If target is less, search left half, if greater search right half
Repeat until element is found or search space is empty
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