Date of Publication
11-10-2003
Document Type
Master's Thesis
Degree Name
Master of Science in Computer Science
Subject Categories
Computer Sciences
College
College of Computer Studies
Department/Unit
Computer Science
Thesis Adviser
Rachel Edita O. Roxas
Defense Panel Chair
Jose Ronello Bartolome
Defense Panel Member
Teresita C. Limoanco
Allan B. Borra
Abstract/Summary
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.
Abstract Format
html
Language
English
Format
Electronic
Accession Number
TG03606; CDTG003606
Shelf Location
Archives, The Learning Commons, 12F Henry Sy Sr. Hall
Physical Description
x, 120 leaves ; 28 cm.
Keywords
Computer algorithms; Sorting (Electronic computers); Electronic data processing
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Recommended Citation
Seño, J. L. (2003). An adaptive comparison-based internal sorting algorithm (S-sort). Retrieved from https://animorepository.dlsu.edu.ph/etd_masteral/3130