I'm a computer science student (just started), I was working on writing from pseudocode a randomized pivot version of Quicksort. I've written and tested it, and it all works perfectly however...
The partition part looks a bit too complicated, as it feels I have missed something or overthought it. I can't understand if it's ok or if I made some avoidable mistakes.
So long story short: it works, but how to do better?
Thanks in advance for all the help
void partition(int a[],int start,int end)
{
srand (time(NULL));
int pivotpos = 3; //start + rand() % (end-start);
int i = start; // index 1
int j = end; // index 2
int flag = 1;
int pivot = a[pivotpos]; // sets the pivot's value
while(i<j && flag) // main loop
{
flag = 0;
while (a[i]<pivot)
{
i++;
}
while (a[j]>pivot)
{
j--;
}
if(a[i]>a[j]) // swap && sets new pivot, and restores the flag
{
swap(&a[i],&a[j]);
if(pivotpos == i)
pivotpos = j;
else if(pivotpos == j)
pivotpos = i;
flag++;
}
else if(a[i] == a[j]) // avoids getting suck on a mirror of values (fx pivot on pos 3 of : 1-0-0-1-1)
{
if(pivotpos == i)
j--;
else if(pivotpos == j)
i++;
else
{
i++;
j--;
}
flag++;
}
}
}
This is the pseudo code of partition()
from Introduction to Algorithms , which is called Lomuto's Partitioning Algorithm, and there's a good explanation below it in the book.
PARTITION(A, p, r)
1 x ← A[r]
2 i ← p - 1
3 for j ← p to r - 1
4 do if A[j] ≤ x
5 then i ←i + 1
6 exchange A[i] ↔ A[j]
7 exchange A[i + 1] ↔ A[r]
8 return i +1
You can implement a randomized partition implementation easily based on the pseudo code above. As the comment pointed out, move the srand()
out of the partition
.
// srand(time(NULL));
int partition(int* arr, int start, int end)
{
int pivot_index = start + rand() % (end - start + 1);
int pivot = arr[pivot_index ];
swap(&arr[pivot_index ], &arr[end]); // swap random pivot to end.
pivot_index = end;
int i = start -1;
for(int j = start; j <= end - 1; j++)
{
if(arr[j] <= pivot)
{
i++;
swap(&arr[i], &arr[j]);
}
}
swap(&arr[i + 1], &arr[pivot_index]); // place the pivot to right place
return i + 1;
}
And there is another partition method mentioned in the book, which is called Hoare's Partitioning Algorithm, the pseudo code is as below:
Hoare-Partition(A, p, r)
x = A[p]
i = p - 1
j = r + 1
while true
repeat
j = j - 1
until A[j] <= x
repeat
i = i + 1
until A[i] >= x
if i < j
swap( A[i], A[j] )
else
return j
After the partition, every element in A[p...j] ≤ every element in A[j+1...r]. So the quicksort would be:
QUICKSORT (A, p, r)
if p < r then
q = Hoare-Partition(A, p, r)
QUICKSORT(A, p, q)
QUICKSORT(A, q+1, r)
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