Some time ago I suddenly got an idea for a new sorting algorithm. What if you walked through an unsorted list of numbers, doing so until the next number was no longer greater than its predecessor, moved that number to the front and started again? I soon realized that this was a very brute and therefore somewhat inefficient approach. Performance could drastically improve if you don’t move the smaller number to the fron but keep it in memory during your next walk-through and insert it into the right spot when you pass it.

I wanted to test this so I made a Java program to implement my new sorting algorithm, which I dubbed ‘H sort’. Of course I needed a benchmark to test against, and I recalled the famous Q sort algorithm from my freshman year. I dusted off my old Pascal book (never thought I’d ever do that again!) and used it to implement Q sort in Java. Strangely enough Q sort does not seem to be in any standard Java library.

As I’d thought, brute H sort performed tragically badly. Its speed also seems highly dependent on the degree of ‘unsortedness’ of the sort list. Sorting an array of 10 integers ranging from 1 through 100 takes approximately 45 microsecs for Q sort, while brute H sort needs 80 up to 600 micros! Improved H sort takes around 50 micros, so that’s indeed quite acceptable.

Further comparing Q and (improved) H sort:

- Array size 50: 125 vs. 520 micros
- Array size 100: 260 vs. 1800 micros
- Array size 1000: 4,000 vs. 18,000 micros

OK, so it’s quite good but not nearly as good as the old Q sort! Of course I need to test this further, running tests automatically for many times and averaging the results. I also want to vary the degree of ‘sortedness’ of the arrays, using partly-sorted ones for testing. I hope to work on this in my spare time the coming days and I’ll keep you posted! I’ll also look into whether this ‘H sort’ algorithm of mine is indeed new or if someone already came up with this (which seems very likely).