NeatSort - A practical adaptive algorithm

We present a new adaptive sorting algorithm which is optimal for most disorder metrics and, more important, has a simple and quick implementation. On input X, our algorithm has a theoretical Ω(|X|) lower bound and a O(|X| log |X|) upper bound, exhibiting amazing adaptive properties which makes it run closer to its lower bound as disorder (computed on different metrics) diminishes. From a practical point of view, NeatSort has proven itself competitive with (and often better than) qsort and any Random Quicksort implementation, even on random arrays.