An adaptive comparison-based internal sorting algorithm (S-sort)
Ssort, an adaptive comparison-based internal sorting algorithm in the same order O(n log n) comparisons as that of Classical Quicksort, has been developed. The best case and worst case time complexities of the proposed sorting algorithm have also been analyzed. It was also empirically evaluated on r...
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oai:animorepository.dlsu.edu.ph:etd_masteral-99682023-05-24T03:41:03Z An adaptive comparison-based internal sorting algorithm (S-sort) Seño, Jose L. Ssort, an adaptive comparison-based internal sorting algorithm in the same order O(n log n) comparisons as that of Classical Quicksort, has been developed. The best case and worst case time complexities of the proposed sorting algorithm have also been analyzed. It was also empirically evaluated on randomly-generated data sets with various sortedness ratios. With the application of adaptability measurement, Adaptive Ssort has improved the performance of Ssort. Its best case time complexity is O(n) comparisons while its worst case is O(n log n) comparisons. Similarly, its performance was evaluated and compared with classical Quicksort. 2003-11-10T08:00:00Z text application/pdf https://animorepository.dlsu.edu.ph/etd_masteral/3130 https://animorepository.dlsu.edu.ph/context/etd_masteral/article/9968/viewcontent/CDTG003606_F_Redacted.pdf Master's Theses English Animo Repository Computer algorithms Sorting (Electronic computers) Electronic data processing Computer Sciences |
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Computer algorithms Sorting (Electronic computers) Electronic data processing Computer Sciences |
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Computer algorithms Sorting (Electronic computers) Electronic data processing Computer Sciences Seño, Jose L. An adaptive comparison-based internal sorting algorithm (S-sort) |
description |
Ssort, an adaptive comparison-based internal sorting algorithm in the same order O(n log n) comparisons as that of Classical Quicksort, has been developed. The best case and worst case time complexities of the proposed sorting algorithm have also been analyzed. It was also empirically evaluated on randomly-generated data sets with various sortedness ratios. With the application of adaptability measurement, Adaptive Ssort has improved the performance of Ssort. Its best case time complexity is O(n) comparisons while its worst case is O(n log n) comparisons. Similarly, its performance was evaluated and compared with classical Quicksort. |
format |
text |
author |
Seño, Jose L. |
author_facet |
Seño, Jose L. |
author_sort |
Seño, Jose L. |
title |
An adaptive comparison-based internal sorting algorithm (S-sort) |
title_short |
An adaptive comparison-based internal sorting algorithm (S-sort) |
title_full |
An adaptive comparison-based internal sorting algorithm (S-sort) |
title_fullStr |
An adaptive comparison-based internal sorting algorithm (S-sort) |
title_full_unstemmed |
An adaptive comparison-based internal sorting algorithm (S-sort) |
title_sort |
adaptive comparison-based internal sorting algorithm (s-sort) |
publisher |
Animo Repository |
publishDate |
2003 |
url |
https://animorepository.dlsu.edu.ph/etd_masteral/3130 https://animorepository.dlsu.edu.ph/context/etd_masteral/article/9968/viewcontent/CDTG003606_F_Redacted.pdf |
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1767197074889113600 |