NeatSort - A practical adaptive algorithm
Marcello La Rocca, Domenico Cantone

TL;DR
NeatSort is a simple, efficient adaptive sorting algorithm that performs close to the theoretical lower bound for nearly sorted data and outperforms traditional quicksort implementations in practical scenarios.
Contribution
Introduces NeatSort, a new adaptive sorting algorithm with optimal disorder metrics performance and simple implementation, outperforming standard sorting methods in practice.
Findings
NeatSort has a theoretical lower bound of Ω(|X|) and an upper bound of O(|X| log |X|).
NeatSort performs better than qsort and quicksort on various data sets.
NeatSort adapts effectively to the level of disorder in the input data.
Abstract
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 , our algorithm has a theoretical lower bound and a 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, \textit{NeatSort} has proven itself competitive with (and often better than) \textit{qsort} and any \textit{Random Quicksort} implementation, even on random arrays.
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Taxonomy
TopicsFuzzy Logic and Control Systems
