Hash sort: A linear time complexity multiple-dimensional sort algorithm
William F. Gilreath

TL;DR
Hash sort is a novel non-comparison sorting algorithm that achieves linear time complexity, outperforming traditional comparison-based sorts like quicksort, and offers new possibilities for efficient data organization.
Contribution
The paper introduces hash sort, a non-comparison sorting algorithm with linear time complexity, surpassing traditional algorithms like quicksort.
Findings
Hash sort has linear time complexity in the worst case.
Hash sort outperforms quicksort in efficiency.
It opens new avenues for data sorting methods.
Abstract
Sorting and hashing are two completely different concepts in computer science, and appear mutually exclusive to one another. Hashing is a search method using the data as a key to map to the location within memory, and is used for rapid storage and retrieval. Sorting is a process of organizing data from a random permutation into an ordered arrangement, and is a common activity performed frequently in a variety of applications. Almost all conventional sorting algorithms work by comparison, and in doing so have a linearithmic greatest lower bound on the algorithmic time complexity. Any improvement in the theoretical time complexity of a sorting algorithm can result in overall larger gains in implementation performance.. A gain in algorithmic performance leads to much larger gains in speed for the application that uses the sort algorithm. Such a sort algorithm needs to use an alternative…
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Taxonomy
TopicsAlgorithms and Data Compression · Computability, Logic, AI Algorithms · DNA and Biological Computing
