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Comparison Study of Sorting Techniques in Static Data Structure
- Source :
- Scopus-Elsevier
- Publication Year :
- 2018
- Publisher :
- Penerbit UTHM, 2018.
-
Abstract
- To manage and organize large data is imperative in order to formulate the data analysis and data processing efficiency. Therefore, this paper investigates the set of sorting techniques to observe which technique to provide better efficiency. Five types of sorting techniques of static data structure, Bubble, Insertion, Selection with O(n2) complexity and Merge, Quick with O(n log n) complexity have been used and tested on four groups between (100–30000) of dataset. To validate the performance of sorting techniques, three performance metrics which are time complexity, execution time and size of dataset were used. All experimental setups were accomplished using simple linear regression. The experimental results illustrate that Quick sort is more efficiency than other sorting 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 thus, sorting technique with behaviour O(n log n) is more efficient than sorting technique with behaviour O(n2) using array.
- Subjects :
- Sorting algorithm
Selection sort
Computer science
Mechanical Engineering
Materials Science (miscellaneous)
Sorted array
02 engineering and technology
Parallel computing
External sorting
01 natural sciences
Industrial and Manufacturing Engineering
Adaptive sort
Mechanics of Materials
0103 physical sciences
Merge algorithm
Data_FILES
0202 electrical engineering, electronic engineering, information engineering
sort
020201 artificial intelligence & image processing
Electrical and Electronic Engineering
010306 general physics
Algorithm
Counting sort
Civil and Structural Engineering
Subjects
Details
- ISSN :
- 26007916 and 2229838X
- Volume :
- 10
- Database :
- OpenAIRE
- Journal :
- International Journal of Integrated Engineering
- Accession number :
- edsair.doi.dedup.....be105720c9c8dc8609f53bb6f52364ab