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I applied via Recruitment Consulltant and was interviewed in Dec 2024. There were 2 interview rounds.
I applied via Campus Placement and was interviewed in Oct 2024. There was 1 interview round.
I applied via Referral and was interviewed before Feb 2023. There were 2 interview rounds.
Easy to medium level coding interview round.
I applied via Instahyre and was interviewed before Feb 2021. There were 3 interview rounds.
Linkedlist insertion & deletion in Go
In Go, linked lists can be implemented using structs and pointers.
Insertion involves creating a new node and updating the pointers of adjacent nodes.
Deletion involves updating the pointers of adjacent nodes to bypass the node being deleted.
Go's garbage collector automatically frees memory of unused nodes.
SQL is best for structured data, NoSQL for unstructured. Use SQL for complex queries, NoSQL for scalability and speed.
SQL is best for structured data, NoSQL for unstructured
Use SQL for complex queries, NoSQL for scalability and speed
SQL is ACID compliant, NoSQL is BASE
Examples of SQL: MySQL, Oracle, PostgreSQL
Examples of NoSQL: MongoDB, Cassandra, Redis
Query to find the second largest element in a database table
Use ORDER BY and LIMIT to select the second largest element
For MySQL: SELECT column FROM table ORDER BY column DESC LIMIT 1,1
For Oracle: SELECT column FROM (SELECT column FROM table ORDER BY column DESC) WHERE ROWNUM <= 2 MINUS SELECT column FROM (SELECT column FROM table ORDER BY column DESC) WHERE ROWNUM <= 1
Zopsmart Technology interview questions for designations
Top trending discussions
I was interviewed before Dec 2020.
Round duration - 60 Minutes
Round difficulty - Medium
This round was purely based on Data Structures and Algorithms . One has to be fairly comfortable in solving Algorithmic problems to pass this round . Both the questions asked were quite common and luckily I had already prepared them from CodeStudio and LeetCode.
Given a Binary Tree with 'N' nodes, where each node holds an integer value, your task is to compute the In-Order, Pre-Order, and Post-Order traversals of the binar...
Compute the In-Order, Pre-Order, and Post-Order traversals of a Binary Tree given in level-order format.
Implement functions to perform In-Order, Pre-Order, and Post-Order traversals of a Binary Tree.
Use level-order input to construct the Binary Tree.
Traverse the Binary Tree recursively to generate the required traversals.
Ensure proper handling of null nodes represented by -1 in the input.
Return the three traversals as
Given a Singly Linked List of integers, your task is to reverse the Linked List by altering the links between the nodes.
The first line of input is an intege...
Reverse a singly linked list by altering the links between nodes.
Iterate through the linked list and reverse the links between nodes
Use three pointers to keep track of the current, previous, and next nodes
Update the links between nodes to reverse the list
Return the head of the reversed linked list
Round duration - 45 Minutes
Round difficulty - Medium
This round basically tested some concepts from Data Structures and File Manipulation .
Given two arrays A
and B
with sizes N
and M
respectively, both sorted in non-decreasing order, determine their intersection.
The intersection of two arrays in...
The problem involves finding the intersection of two sorted arrays efficiently.
Use two pointers to iterate through both arrays simultaneously.
Compare elements at the pointers and move the pointers accordingly.
Handle cases where elements are equal and update the intersection array.
Return the intersection array as the result.
Tip 1 : Must do Previously asked Interview as well as Online Test Questions.
Tip 2 : Go through all the previous interview experiences from Codestudio and Leetcode.
Tip 3 : Do at-least 2 good projects and you must know every bit of them.
Tip 1 : Have at-least 2 good projects explained in short with all important points covered.
Tip 2 : Every skill must be mentioned.
Tip 3 : Focus on skills, projects and experiences more.
Print the level order traversal of binary tree in spiral form
Perform level order traversal of the binary tree
Alternate the direction of traversal for each level
Use a stack to reverse the order of nodes in each level
Print the nodes in the order of traversal
Find the maximum element in each subarray of size k in a given array.
Iterate through the array from index 0 to n-k.
For each subarray of size k, find the maximum element.
Store the maximum elements in a separate array.
Return the array of maximum elements.
To find the Kth largest element in two sorted arrays, we can use the merge step of merge sort algorithm.
Merge the two arrays into a single sorted array using a modified merge sort algorithm.
Return the Kth element from the merged array.
Merge two sorted arrays into one sorted array with expected time complexity of (m+n).
Use a two-pointer approach to compare elements from both arrays and merge them into the first array.
Start comparing elements from the end of both arrays and place the larger element at the end of the first array.
Continue this process until all elements from the second array are merged into the first array.
The algorithm finds the position of the 3rd occurrence of 'B' in an n-ary tree from a given index in constant time complexity.
Traverse the n-ary tree using a depth-first search (DFS) algorithm
Keep track of the count of 'B' occurrences
When the count reaches 3, return the current position
If the end of the tree is reached before the 3rd 'B', return -1
Check if a given string is a composite of two words from a limited dictionary.
Create a hash set of all the words in the dictionary.
Iterate through all possible pairs of substrings in the given string.
Check if both substrings are present in the hash set.
If yes, return true. Else, return false.
Switch adjacent nodes in a single linked list.
Traverse the linked list and swap adjacent nodes.
Keep track of previous node to update its next pointer.
Handle edge cases for first two nodes and last node.
Example: 1->2->3->4 becomes 2->1->4->3.
Traverse only the left sub-tree of a binary search tree.
Start at the root node
If the left child exists, visit it and repeat the process
If the left child does not exist, return to the parent node
Continue until all nodes in the left sub-tree have been visited
Design an efficient data structure for two lifts in a building of n floors.
Use a priority queue to keep track of the floors each lift is heading to
Implement a scheduling algorithm to determine which lift to assign to a new request
Consider adding a weight limit to each lift to prevent overloading
Use a hash table to keep track of the current location of each lift
To find the maximum number that can be formed from the digits of an integer.
Convert the integer to a string
Sort the characters in descending order
Join the sorted characters to form the maximum number
Reverse all the words in a given string
Split the string into an array of words
Loop through the array and reverse each word
Join the reversed words back into a string
Explaining how to handle 'n' in a string during swapping process
Identify the positions of 'n' in the string
Exclude those positions from the swapping process
Use a temporary variable to swap the characters
Ensure the swapped characters are not 'n'
Return the modified string
We can use any sorting algorithm like quicksort, mergesort, heapsort, etc.
Choose the appropriate sorting algorithm based on the size of the file and the range of numbers
Implement the chosen algorithm in the programming language of choice
Read the numbers from the file into an array or list
Apply the sorting algorithm to the array or list
Write the sorted numbers back to the file
Word suggestions in Eclipse can be implemented using algorithms like Trie or N-gram models.
Use Trie data structure to store the dictionary of words
Implement auto-complete feature using Trie
Use N-gram models to suggest words based on context
Train the N-gram model on a large corpus of text data
Combine both approaches for better accuracy
Consider user's typing speed and frequency of words for better suggestions
To check if a number k lies in a sequence formed by adding previous 2 elements, start with a=0 and b=1 and iterate until k is found or exceeded.
Start with a=0 and b=1
Iterate through the sequence until k is found or exceeded
If k is found, return true. If exceeded, return false
Check if a Binary Tree is a Binary Search Tree (BST)
A BST has the property that all nodes in the left subtree of a node have values less than the node's value, and all nodes in the right subtree have values greater than the node's value
We can traverse the tree in-order and check if the resulting sequence is sorted
Alternatively, we can recursively check if each node satisfies the BST property
Keep track of kth largest number in a stream of numbers.
Use a min-heap of size k to keep track of kth largest number.
For each incoming number, compare it with the root of the heap.
If it is larger than the root, replace the root with the new number and heapify.
The root of the heap will always be the kth largest number.
Infix expression can be evaluated using the concept of operator precedence and associativity.
Convert the infix expression to postfix expression using stack data structure
Evaluate the postfix expression using stack data structure
Use operator precedence and associativity rules to determine the order of evaluation
Parentheses can be used to override the default order of evaluation
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