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I applied via Approached by Company and was interviewed in May 2022. There were 3 interview rounds.
I am currently working as a Software Development Engineer with expertise in web development and cloud computing.
Proficient in programming languages like Java, Python, and JavaScript
Experience in developing and maintaining web applications using frameworks like React and Angular
Knowledge of cloud computing platforms such as AWS and Azure
Familiarity with database management systems like MySQL and MongoDB
Strong problem-so
I applied via LinkedIn and was interviewed in May 2022. There was 1 interview round.
The time complexity of the program is O(nlogn).
The program has a divide and conquer algorithm.
The program has nested loops.
The program has a recursive function.
Design an algorithm with less time complexity.
Use efficient data structures like hash tables, binary trees, etc.
Avoid nested loops and recursion if possible.
Try to optimize the code by reducing redundant operations.
Use dynamic programming to solve complex problems.
Consider parallel processing for large datasets.
Use built-in functions and libraries instead of writing custom code.
Profile the code to identify bottlenecks
I applied via Approached by Company and was interviewed before Sep 2021. There was 1 interview round.
Merge sort and heap sort are two popular sorting algorithms used in computer science.
Merge sort is a divide-and-conquer algorithm that recursively divides the input array into two halves, sorts them, and then merges them back together.
Heap sort is a comparison-based sorting algorithm that uses a binary heap data structure to sort elements.
Merge sort has a time complexity of O(n log n) and is stable, while heap sort has...
Time complexities of sort algorithms
Bubble sort - O(n^2)
Selection sort - O(n^2)
Insertion sort - O(n^2)
Merge sort - O(n log n)
Quick sort - O(n log n)
Heap sort - O(n log n)
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I applied via Campus Placement and was interviewed in Jul 2021. There were 6 interview rounds.
Google interview questions for designations
I applied via Campus Placement and was interviewed before Apr 2021. There were 2 interview rounds.
2 Coding Ques + Aptitude
posted on 15 May 2017
I was interviewed before May 2016.
Program to calculate sum of level order tree
Traverse the tree level by level using BFS
Add the values of each level and return the sum
Use a queue to store the nodes at each level
Handle edge cases like empty tree or null root
posted on 19 May 2017
I was interviewed in Aug 2016.
Find the length of longest increasing subsequence in an array.
Use dynamic programming to solve the problem efficiently.
Maintain an array to store the length of longest increasing subsequence ending at each index.
Traverse the array and update the array for each index.
Return the maximum value in the array as the length of longest increasing subsequence.
Find maximum of every window of size K in an array
Iterate through the array and maintain a deque of indices of elements in the current window
Remove indices from the front of the deque if they are outside the current window
Remove indices from the back of the deque if their corresponding elements are smaller than the current element
The front of the deque will always contain the index of the maximum element in the current
Implement binary search in a semi-infinite array.
Start with the first element and keep doubling the index until the target element is less than the current element.
Perform binary search on the subarray from the last doubled index to the current index.
If the target element is not found, repeat the process by doubling the last index and searching again.
Handle edge cases where the target element is at the first index or n
posted on 3 Dec 2015
posted on 23 Jan 2017
I was interviewed before Jan 2016.
posted on 20 May 2017
I was interviewed in Dec 2016.
Convert an expression to post-fix notation.
Start with an empty stack.
Scan the expression from left to right.
If the scanned character is an operand, output it.
If the scanned character is an operator, pop two operands from stack, output them in post-fix notation and push the result back.
Repeat until the end of expression.
Find the maximum continuous sum in an array of integers.
Use Kadane's algorithm to find the maximum subarray sum in linear time complexity.
Initialize two variables, one for current maximum sum and another for overall maximum sum.
Iterate through the array and update the variables accordingly.
Example: For array [-2, 1, -3, 4, -1, 2, 1, -5, 4], the maximum continuous sum is 6 (from index 3 to 6).
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