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Addverb Technologies
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I applied via Naukri.com and was interviewed in May 2021. There were 3 interview rounds.
Top trending discussions
I was interviewed in Sep 2017.
A sorting algorithm is a method of arranging elements in a specific order.
Sorting algorithms can be categorized as comparison-based or non-comparison-based.
Common sorting algorithms include bubble sort, insertion sort, selection sort, merge sort, quicksort, and heapsort.
Efficiency of sorting algorithms is measured by their time complexity, space complexity, and stability.
Example: Sorting an array of strings in alphabet
posted on 1 Aug 2024
posted on 16 Nov 2024
I applied via LinkedIn and was interviewed in Oct 2024. There were 2 interview rounds.
2-3 basic dsa questions
I applied via LinkedIn and was interviewed before Aug 2023. There were 2 interview rounds.
Data extraction, solid questions, oops
It was the ask mostly about DSA
I applied via Approached by Company and was interviewed before Feb 2023. There was 1 interview round.
I applied via LinkedIn and was interviewed in Sep 2024. There were 2 interview rounds.
It was a combination of Maths and Electronics basics.
I am a recent graduate with a degree in Computer Science and a passion for coding and problem-solving.
Recent graduate with a degree in Computer Science
Passionate about coding and problem-solving
Strong communication and teamwork skills
I have worked on various projects including a web development project, a data analysis project, and a machine learning project.
Developed a website for a local business using HTML, CSS, and JavaScript.
Conducted data analysis on customer feedback data to identify trends and make recommendations for improvement.
Implemented a machine learning algorithm to predict customer churn for a telecom company.
posted on 16 Apr 2024
I applied via Naukri.com and was interviewed before Apr 2023. There were 2 interview rounds.
Given programming questions
String programs
posted on 6 Feb 2023
I applied via Naukri.com and was interviewed in Jan 2023. There was 1 interview round.
O(n) refers to linear time and space complexity.
O(n) means that the time or space required by an algorithm grows linearly with the size of the input.
It implies that the algorithm's performance is directly proportional to the input size.
For example, if an algorithm takes 10 seconds to process 100 elements, it would take 20 seconds to process 200 elements.
O(n) complexity is considered efficient and desirable in most case
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