Algorithms Introduction and Analysis

Posterior Analysis: It is done after the actual implementation and execution of the algorithm using any programming language like C, C++, Java, or Python. It is the actual analysis in which the space and time complexity of the algorithm is calculated more correctly. (alert-passed) 

This method of measuring the approximate complexity is known as asymptotic complexity. (alert-success) 

Now, I hope you understand the above example and the term asymptotic but even if you are unable to get it completely don't worry as we are going to cover this in more detail soon. 

First, we need to learn more about the types of asymptotic notations. There are three asymptotic notations that are used to calculate the space and time complexity of an algorithm. They are Big O, Big Ω, and Big Θ. But every time we are not going to calculate all three for an algorithm.  

Types of Asymptotic notation.

C++ Example Code for Linear Search.

//Linear Search Algorithm code in C++
#include <iostream>
using namespace std;

int linearSearch(int arr[], int n, int target) {
    for (int i = 0; i < n; i++) {
        if (arr[i] == target) {
            return i; // return the index of the target element if found
        }
    }
    return -1; // return -1 if target element is not found
}

int main() {
    int arr[] = {5, 2, 8, 3, 1, 9};
    int n = sizeof(arr) / sizeof(arr[0]);
    int target = 3;

    int index = linearSearch(arr, n, target);
    if (index != -1) {
        cout << "Element found at index: " << index << endl;
    } else {
        cout << "Element not found." << endl;
    }

    return 0;
}