1.Importance
time complexity :-
The time
complexity of an algorithm is the total amount of time required by an algorithm
to complete its execution. In simple words, every piece of code we write, takes
time to execute. The time taken by any piece of code to run is known as the
time complexity of that code. The lesser the time complexity, the faster the
execution.
2. Find
out the time complexity and errors from the code :-
#include
<stdio.h>
int main() {
int counter, N,i;
printf("Enter a Positive Number\n");
scanf("%d",&N);
for (counter = 1; counter <= N;
counter++)
{
printf("%d \n", counter);
}
int a=12,n=12;
if(N>10)
{
for(i=0; i<a; i++)
{
for(i=0; i<a; i++)
{
a++;
}
}
for(i=0;i<a;i*=2)
{
printf("hello");
}
}
return 0;
}
From this code
we find out 3 errors.
(a). Declare
the variable i;
(b). We added for before (counter = 1; counter <= N; counter++)
(c). We
added semicolon (;) after printf("hello");
Those are
the errors of the code.
Time
complexity for the code :-
According to
the codeblocks, We see,
Line 7 :
a loop of size N.
Line 13 to
20 : Size of loop n^3 and one operations.
So, We get,
N + n^3
Again, when
we have an asymptotic analysis, we drop all constants and leave the most
important term: n^3. So, in big O notation, it would be O(n^3).