quicksort

Why quicksort(or introsort), or any comparison-based sorting algorithm is more common than radix-sort? Especially for sorting numbers. Radix-sort is not comparison based, hence may be faster than O(n logn). In fact, it is O(k n), where k is the number of bits used to represent each item. And the memory overhead is not critical, since you may choose the number of buckets to use, and required memory may be less than mergesort's requirements. Does it have to do with caching? Or maybe accessing random bytes of integers in the array? Two arguments come to my mind: Quicksort/Introsort is more

I have a hard time translating QuickSort with Hoare partitioning into C code, and can't find out why. The code I'm using is shown below: void QuickSort(int a[],int start,int end) { int q=HoarePartition(a,start,end); if (end<=start) return; QuickSort(a,q+1,end); QuickSort(a,start,q); } int HoarePartition (int a[],int p, int r) { int x=a[p],i=p-1,j=r; while (1) { do j--; while (a[j] > x); do i++; while (a[i] < x); if (i < j) swap(&a[i],&a[j]); else return j; } } Also, I don't really get why HoarePartition works. Can someone explain why it works, or at least link me to an article that does? I

Isnt Insertion sort O(n^2) > Quick sort O(nlogn)...so for a small n, wont the relation be the same? Casey Robinson Big-O Notation describes the limiting behavior when n is large, also known as asymptotic behavior. This is an approximation. (See http://en.wikipedia.org/wiki/Big_O_notation ) Insertion sort is faster for small n because Quick Sort has extra overhead from the recursive function calls. Insertion sort is also more stable than Quick sort and requires less memory. This question describes some further benefits of insertion sort. ( Is there ever a good reason to use Insertion Sort? )

What is the median of three strategy to select the pivot value in quick sort? I am reading it on the web, but I couldn't figure it out what exactly it is? And also how it is better than the randomized quick sort. The median of three has you look at the first, middle and last elements of the array, and choose the median of those three elements as the pivot. To get the "full effect" of the median of three, it's also important to sort those three items, not just use the median as the pivot -- this doesn't affect what's chosen as the pivot in the current iteration, but can/will affect what's used