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Determine the "worst-case" runtime for the following sorting algorithm written in this code? 


1 sort (array a) {
2     for (n=a.size; n>1; --n) {
3         for (i=0; i<n-1; ++i) {
4             if (a[i] > a[i+1]) {
5                 a.swap(i, i+1)
6             }
7         }
8     }
9 }

Determine the worst-case runtime:


O(n2)

	
O(1)

	
O(n*log(n))

	
O(n)


What I have tried:

which option determine the worst-case runtime for the following sorting algorithm written in  this code?

O(n2)

	
O(1)

	
O(n*log(n))

	
O(n)
Posted
Updated 20-Dec-21 11:06am
Comments
Rick York 20-Dec-21 16:25pm
   
One of the above. Do you really expect us to do your homework for you?

It is not difficult. Just follow the code trying to figurate the (rough) maximum number of swap operations needed in the worst scenario.
   
Comments
Greg Utas 21-Dec-21 13:58pm
   
The time complexity of a sort algorithm is usually based on the number of comparisons.
CPallini 21-Dec-21 14:03pm
   
In this case, the number of comparisons is independent of the worst case scenario.
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