Understanding Time Complexity For Beginners

The Basic Definition of time complexity is, In computer science, the time complexity is the computational(involving the calculation of answers, amounts, results, etc) complexity that describes the amount of computer time it takes to run an algorithm.

E.g Consider the below simple code

class Demo {
public static void main(String[] args) {
System.out.println("Hello There Good Morning");
}
}

In the above example the output prints only one time so its time is number 1, in and its denotes by Big Oh of 1 (O(1)) that is constant time, The above O -> is called Big – Oh which is an asymptotic notation.

E.g Consider The Below Simple code

class Demo2 {
public static void main(String[] args)
{
int i, n = 8;
for (i = 1; i <= n; i++) {
System.out.println("Hello Good Evening");
}
}
}
so the output of the above code is Hello Good Evening will print 8 times in console
so thats means the time complexity of above code is O(n) where n = 8 and as the value of n can changes according to programmer so thats why its time complexity is O(n).