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RE (tilly) 3 (tis true): Randomize an array

by tilly (Archbishop)
 on Sep 08, 2000 at 06:01 UTC ( #31532=note: print w/replies, xml ) Need Help??

in reply to RE: Re: Randomize an array

OK, I just had to go searching for some old documentation and you can see it laid out there.

Clearly what is called qsort really need not be. For many possible reasons.

Now more details. You are right that the average time for qsort to work is n*log(n). However qsort actually has a worst case of n^2. In fact the worst case with a naive qsort is hit on an already sorted list. Perl currently uses a qsort with pivots chosen carefully to move the worst case to something unlikely.

You are also right that no sorting algorithm can possibly beat having an average case of O(n*log(n)). Why not? For the simple reason that there are n! possible permutations you have to deal with. In m comparisons you can only distinguish at most 2^m of them. So the number of comparisons you need will be at least log_2(n!). Well up to a constant factor that is log(n!) which is

```log(n!) = log(1*2*...*n)
= log(1) + log(2) + ... + log(n)
```
which is approximately the integral from 1 to n of log(x). Which in turn is n*log(n)-n+1 plus error terms from the approximation. (After a full derivation you get Stirling's Approximation.)

Right now all that concerns us is that n*log(n) term out front. You cannot get rid of that.

Now that said there are many sorting algorithms out there. qsort is simple and has excellent average performance, but there are others that have guaranteed performance and are order n on sorted datasets. Incidentally there is right now an interesting discussion of this on p5p, including a brand new discovery of a memory leak...

• Comment on RE (tilly) 3 (tis true): Randomize an array

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RE: RE (tilly) 3 (tis true): Randomize an array
by Adam (Vicar) on Sep 09, 2000 at 00:33 UTC
Well..... There is the Radix Sort, which is O(N)... course it also requires more information about what is being sorted, and places constraints on that data set, and well its just not as general so its not considered on par with Qsort or MergeSort.
Can we really call that O(N)? The constant depends upon the number of passes. As you increase the number of items, eventually you have to have long strings which requires lots of passes, indeed with a fixed number of symbols in your alphabet the number of things you can represent rises exponentially in the length you allow...which means it is truly n*log(n) again. :-)

Indeed my explanation about Stirling's formula is still relevant, re-read it and you can see that the fundamental issue is that a set of decisions with fixed branching can only account for an exponential number of possibilities. So the number of branches needed to sort n things grows like log(n!) which is order n*log(n). However the big win is that with radix sort you can get a far better branch factor than 2. (At least initially.)

But unfortunately the radix sort cannot be made to work with arbitrary sort functions since it does not (at least not directly) work off of binary comparisons...

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