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C'est la Z

Sorting - Subtle Errors

Time to wrap up sorting for a while. We just finished quicksort having gone through a series of lessons

  • We started with Quickselect.
  • Then we did a quicksort, copying to new arrays during the partition
  • Then finally to an in place quicksort.

For the final quicksort we used a partition algorithm pretty much the same as the one described here.

We started testing using by building a randomly filled array like this:

Random rnd = new Random();
int a[] = new int[n];
for (int i=0;i<n;i++) {
a[i] = rnd.nextInt(100);

And everything seemed terrific.

Just like when we did the mergesort, we started to increase n. First 20, then 100, then 1000 and so on.

All of a sudden, we started getting a stack overflow. We only made it to about 450,000. Mergesort got to arrays of about 40,000,000 items before we started to have memory problems.

Our algorithm was sound. It worked on everything up to about 450,000. Since Mergesort worked well into the tens of millions, quicksort should have as well.

What was wrong?

We changed the code a bit:

Random rnd = new Random();
int a[] = new int[n];
for (int i=0;i<n;i++) {
a[i] = rnd.nextInt(10000);

Instead of an array of 450,000 values between 0 and 100, our elements now went fro 0 to 10,000.

All of a sudden things were good.

Why? It wasn't long before the student saw that 500,000 elements with values between 0 and 100 meant lots of duplicates. Our partition didn't account for that. If we had duplicate pivots, only one is moved into place, the rest are left unsorted taking us closer to worst case performance and blowing our stack.

Fortunately there was an easy fix:

public int partition(int[] a, int l, int r) {
int tmp;
int pivotIndex = l+rnd.nextInt(r-l);
int pivot = a[pivotIndex];
tmp = a[r];
a[r] = a[pivotIndex];

int wall=l;
int pcount=1;
for (int i=l;i<r;i++) {
if (a[i]<pivot) {
tmp = a[i];
if (a[i]==pivot)
// now copy over all the pivots
int rwall=wall;
tmp = a[rwall];
for (int i=rwall+1;i<=r;i++) {
if (a[i]==pivot) {
tmp = a[rwall];
return (wall+rwall)/2;

When we partition the array, move all the elements equal to the partition to the middle of the array.

That did the trick.

All of a sudden we were blazing through data sets upwards of 100,000,000 elements.

We're done for sorting for a while, at least until the heapsort but it's been a fun couple of weeks

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