Abstract
AbstractSorting implies the task of presenting a specific type of data in a specific order. These tasks are getting accomplished by different algorithms proposed by researchers. Researchers are trying to achieve this task in minimal space and time complexity with improved stability, correctness, finiteness and effectiveness. Sorting is used in wide range of fields namely, in Operating systems, Data Base Management systems, in searching and in various other data science related areas. In this paper, a divide and conquer approach-based algorithm is proposed to sort the data in a specific order using min–max searching. The time complexity of the proposed Swift Sort algorithm is O(nlogn) and O(n2) in the average and worst cases, respectively. Moreover, time complexity of the proposed algorithm is comparable to Quick Sort, Merge Sort, Heap Sort and TimSort but at the same time Randomised Quick Sort, Merge Sort and Heap Sort produces a better Time Complexity in their worst cases than Swift Sort. The experimental results prove the correctness of the proposed algorithm.KeywordsSortingSwift sortTime complexitySpace complexityDivide and conquerData science
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