Lecture 8 - Analysis Of Common Loops | DSA Basics For Beginners | Placement Course
Welcome to Lecture 8 - Analysis Of Common Loops of our DSA Placement Course. In this lecture, we will get an understanding on how to analyse loops for Complexity Analysis of Algorithms and how to implement them in coding.
The analysis of loops for the complexity analysis of algorithms involves finding the number of operations performed by a loop as a function of the input size. This is usually done by determining the number of iterations of the loop and the number of operations performed in each iteration.
What do you mean by analysis of complexity?
Complexity analysis is defined as a technique to measure how long an algorithm would take to complete given an input of size n; independent of the machine, language, and compiler. It is used for evaluating the variations of execution time on different algorithms.
What is a loop in data structure?
In computer Programming, a Loop is used to execute a group of instructions or a block of code multiple times, without writing it repeatedly. The block of code is executed based on a certain condition. Loops are the control structures of a program.
What is the complexity analysis of nested loop?
At each iteration, nested loop is performing O(1) operation. So overall time complexity = O(n²) * O(1) = O(n²). Let's take an interesting example. Suppose, we have an input matrix X of size m x n containing only 0's and 1's, which are sorted in a row-wise fashion.
This Data Structures and Algorithms course is a part of our Data Structures and Algorithms playlist: • Video
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