The BIG O Notation

Manuel Portelli

Hi to all.

Attached with this topic there is a file "program.cs" which is a C-Sharp file created with visual studio.
This file contains a simple console application in which the user is asked to enter 3 integer numbers (to be 3 sides of a triangle), and the application outputs if the 3 sides of the triangle given are equilateral, isosceles, scalene triangle or otherwise it outputs that the sides do not make up a triangle.

My problem is that i am asked to examine the complexity of the code which i created using the BIG O notation.

Can anyone please help me out with this problem?
I am a dummy in this type of notation so please if anyone is going to explain be simple.

Thanks & Regards.
Combinu

P.S. I have also posted this topic in the C-Sharp Language forum so i kindly request a moderator to remove one of the topics, thanks and sorry for any inconvenience caused.

3 Replies

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Vulpes14y ago
It seems to me that the time (or number of steps) needed to execute the algorithm will be just the same whatever the inputs (i.e. the length of the triangle's sides) happen to be.

So, in other words, the algorithm will execute in constant time i.e. O(1).

There's a description of 'Big O' notation in the link below:

http://en.wikipedia.org/wiki/Big_O_notation

Notice the description for computer science:

"In computer science, big O notation is used to classify algorithms by how they respond (i.e., in their processing time or working space requirements) to changes in input size."
Manuel Portelli14y ago
Yes i can see that the notation does not depend on the type of sides i am going to input but on the executable code that i have written.

My problem is on how to calculate this notation. If it is O(1) how did you deduce this notation to my program that is written.
Vulpes14y ago
As far as I can see, the time taken by the algorithm you're using to determine the type of triangle doesn't depend on the lengths of the sides. In other words, it will take the same time to execute the program whatever the inputs are.

I'd therefore say the algorithm is O(1) which is constant time.