Although the shell sort algorithm is significantly better than insertion sort there is still room for improvement. One of the most popular sorting algorithms is quicksort. Quicksort executes in O(n lg n) on average and O(n2) in the worst-case. However with proper precautions worst-case behavior is very unlikely. Quicksort is a non-stable sort. It is not an in-place sort as stack space is required. For further reading consult Cormen .
The quicksort algorithm works by partitioning the array to be sorted then recursively sorting each partition. In Partition (Figure 2-3) one of the array elements is selected as a pivot value. Values smaller than the pivot value are placed to the left of the pivot while larger values are placed to the right.
int function Partition (Array A int Lb int Ub); begin select a pivot from A[Lb]...A[Ub]; reorder A[Lb]...A[Ub] such that: all values to the left of the pivot are <= pivot all values to the right of the pivot are >= pivot return pivot position; end; procedure QuickSort (Array A int Lb int Ub); begin if Lb < Ub then M = Partition (A Lb Ub); QuickSort (A Lb M - 1); QuickSort (A M Ub); end;
In Figure 2-4(a) the pivot selected is 3. Indices are run starting at both ends of the array. One index starts on the left and selects an element that is larger than the pivot while another index starts on the right and selects an element that is smaller than the pivot. In this case numbers 4 and 1 are selected. These elements are then exchanged as is shown in Figure 2-4(b). This process repeats until all elements to the left of the pivot <= the pivot and all elements to the right of the pivot are >= the pivot. QuickSort recursively sorts the two subarrays resulting in the array shown in Figure 2-4(c).
Figure 2-4: Quicksort Example
As the process proceeds it may be necessary to move the pivot so that correct ordering is maintained. In this manner QuickSort succeeds in sorting the array. If we’re lucky the pivot selected will be the median of all values equally dividing the array. For a moment let’s assume that this is the case. Since the array is split in half at each step and Partition must eventually examine all n elements the run time is O(n lg n).
To find a pivot value Partition could simply select the first element (A[Lb]). All other values would be compared to the pivot value and placed either to the left or right of the pivot as appropriate. However there is one case that fails miserably. Suppose the array was originally in order. Partition would always select the lowest value as a pivot and split the array with one element in the left partition and Ub - Lb elements in the other. Each recursive call to quicksort would only diminish the size of the array to be sorted by one. Therefore n recursive calls would be required to do the sort resulting in a O(n2) run time. One solution to this problem is to randomly select an item as a pivot. This would make it extremely unlikely that worst-case behavior would occur.
An ANSI-C implementation of quicksort is included.
T and comparison operator
compGT should be altered to reflect the data
stored in the array. Two version of quicksort are included: quickSort
partition. If the list is partially ordered this will be a good choice. Worst-case behavior occurs when the center element happens to be the largest or smallest element each time
insertSortis called. Due to recursion and other overhead quicksort is not an efficient algorithm to use on small arrays. Consequently any array with fewer than 50 elements is sorted using an insertion sort. Cutoff values of 12-200 are appropriate.
Included is a version of quicksort that sorts linked-lists. Also included is an ANSI-C implementation of qsort a standard C library function usually implemented with quicksort. Recursive calls were replaced by explicit stack operations. Table 2-1 shows timing statistics and stack utilization before and after the enhancements were applied.
|4 096||34 183||20 016||1 908||168|
|65 536||658 003||460 737||2 436||252|
A Visual Basic implementation for quick sort and qsort is included.