Comparison study on sorting techniques in static data structure

To manage and organize large data is imperative in order to formulate the data analysis and data processing efficiency. Thus, to handle large data becomes highly enviable, whilst, it is premised that the sorting techniques eliminate ambiguities with less effort. Therefore, this study investigates th...

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主要作者: Naser Frak, Anwar
格式: Thesis
語言:English
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English
出版: 2016
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spelling my-uthm-ep.9262021-09-09T06:01:05Z Comparison study on sorting techniques in static data structure 2016-03 Naser Frak, Anwar QA75-76.95 Calculating machines To manage and organize large data is imperative in order to formulate the data analysis and data processing efficiency. Thus, to handle large data becomes highly enviable, whilst, it is premised that the sorting techniques eliminate ambiguities with less effort. Therefore, this study investigates the functionality of a set of sorting techniques to observe which technique to provide better efficiency in terms of sorting data. Therefore, five types of sorting techniques of static data structure, namely: Bubble, Insertion, Selection in group O (n2) complexity and Merge, Quick in group O (n log n) complexity using the C++ programming language have been used. Each sorting technique was tested on four groups between 100 and 30000 of dataset. To validate the performance of sorting techniques, three performance metrics which are time complexity, execution time (run time) and size of dataset were used. All experimental setups were accomplished using simple linear regression where experimental results illustrate that Quick sort is more efficiency than Merge Insertion, Selection and Bubble sort based on run time and size of data using array and Selection sort is more efficient than Bubble and Insertion in large data size using array. In addition, Bubble, Insertion and Selection have good performance for small data size using array while Merge and Quick sort have good performance in large data size using array and sorting technique with good behavior O (n log n) more efficient rather than sorting technique with bad behavior is O (n2) using array. 2016-03 Thesis http://eprints.uthm.edu.my/926/ http://eprints.uthm.edu.my/926/1/24p%20ANWAR%20NASER%20FRAK.pdf text en public http://eprints.uthm.edu.my/926/2/ANWAR%20NASER%20FRAK%20COPYRIGHT%20DECLARATION.pdf text en staffonly http://eprints.uthm.edu.my/926/3/ANWAR%20NASER%20FRAK%20WATERMARK.pdf text en validuser mphil masters Universiti Tun Hussein Onn Malaysia Faculty of Computer Science and Information Technology
institution Universiti Tun Hussein Onn Malaysia
collection UTHM Institutional Repository
language English
English
English
topic QA75-76.95 Calculating machines
spellingShingle QA75-76.95 Calculating machines
Naser Frak, Anwar
Comparison study on sorting techniques in static data structure
description To manage and organize large data is imperative in order to formulate the data analysis and data processing efficiency. Thus, to handle large data becomes highly enviable, whilst, it is premised that the sorting techniques eliminate ambiguities with less effort. Therefore, this study investigates the functionality of a set of sorting techniques to observe which technique to provide better efficiency in terms of sorting data. Therefore, five types of sorting techniques of static data structure, namely: Bubble, Insertion, Selection in group O (n2) complexity and Merge, Quick in group O (n log n) complexity using the C++ programming language have been used. Each sorting technique was tested on four groups between 100 and 30000 of dataset. To validate the performance of sorting techniques, three performance metrics which are time complexity, execution time (run time) and size of dataset were used. All experimental setups were accomplished using simple linear regression where experimental results illustrate that Quick sort is more efficiency than Merge Insertion, Selection and Bubble sort based on run time and size of data using array and Selection sort is more efficient than Bubble and Insertion in large data size using array. In addition, Bubble, Insertion and Selection have good performance for small data size using array while Merge and Quick sort have good performance in large data size using array and sorting technique with good behavior O (n log n) more efficient rather than sorting technique with bad behavior is O (n2) using array.
format Thesis
qualification_name Master of Philosophy (M.Phil.)
qualification_level Master's degree
author Naser Frak, Anwar
author_facet Naser Frak, Anwar
author_sort Naser Frak, Anwar
title Comparison study on sorting techniques in static data structure
title_short Comparison study on sorting techniques in static data structure
title_full Comparison study on sorting techniques in static data structure
title_fullStr Comparison study on sorting techniques in static data structure
title_full_unstemmed Comparison study on sorting techniques in static data structure
title_sort comparison study on sorting techniques in static data structure
granting_institution Universiti Tun Hussein Onn Malaysia
granting_department Faculty of Computer Science and Information Technology
publishDate 2016
url http://eprints.uthm.edu.my/926/1/24p%20ANWAR%20NASER%20FRAK.pdf
http://eprints.uthm.edu.my/926/2/ANWAR%20NASER%20FRAK%20COPYRIGHT%20DECLARATION.pdf
http://eprints.uthm.edu.my/926/3/ANWAR%20NASER%20FRAK%20WATERMARK.pdf
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