Comparison study on sorting techniques in static data structure

• Main Author: Naser Frak, Anwar
• Format: Thesis
• Language: English; English; English
• Published: 2016
• Subjects: QA75-76.95 Calculating machines
• Online Access: 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; http://eprints.uthm.edu.my/926/

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.