The way I explained is the simple way; a complete answer takes only one sentence. "Count the number of fundamental operations that take place" is much simpler and less nerdy than any complicated description about iteration counts and nested loops.

I am looking on how to measure in terms of either seconds or milliseconds of the runtime of an algorithm with real data, i.e. of a program.

What would be the best implementation of this? This would either be for C or C++.

However, what I am looking for example, is something similar along the lines of how one would get a script execution time (render time), in a typical PHP program. You all have seen at the bottom of forums or other PHP based web pages and have seen that calculation. Would this be one way to implement this?

How would I implement such without using too many system dependent libraries (e.g. windows), but rather either a custom or by standard libraries?

Any thoughts? At first I thought, before calling that algorithm function, say myTestFunction(), I would make a system call to request the time, then after the function has completed it's run and returned to the original call position, to make the system call again and then do a simple subtraction somehow on the time then that would be the result. Of course, I could just be dreaming this all as I have yet to fully investigate this, but is this how it would be done?

Any other ways?

Thanks

U can calculate time complexity of an alg using foll steps.
1.Recursive alg
Form a recursive relation of the alg and solve the relation
2. Non recursive ralation
find no. of times the stmt r executed
For deatiled explanation refer Analysis and design of alg by Anany Levitin

i want to ask some questions,how con i do that?

can you please tell me how did u come to the conclusion it is a average case ? is average case = best case ??

can somebody give me an example for exponential time complexity ???
in the previous i saw the example for everything except exponential one !!

Thanks for the good explanation !! good job. ;-)

"So to answer your question: A function or an algorithm's runtime can be depicted by different theta expressions. However, these are equal theta expressions. Remember that Theta(n^2) refers to the set of all functions that grow at the same pace as n^2. Well, Theta(2 * n^2) refers to exactly the same set! (If a function grows at the same pace as n^2, then it also grows at the same pace as 2*n^2.)"

my question is ,

is it only for theta ? or it can applied to Oh and Omega also ??

find big-Oh noyation forf(n)=n+log n

Hi ! I read all dicussion about time complexity on this page. Please tell me if there is a lengthy programm that too written in c++, how I can calculate its time complexity.:mad:

Is there some software which can do this job automatically ?

Fahim

You find the time complexity for big programs the same way you find it for small programs.

There is no software that can do this automatically.