Comparative of Advanced Sorting Algorithms (Quick Sort, Heap Sort, Merge Sort, Intro Sort, Radix Sort) Based on Time and Memory Usage

Every algorithm has its own best-case as well as its worst-case scenario, so it is difficult to determine the best sorting algorithm just by its Big-O. Not only that, the amount of memory required also affect the algorithm's efficiency. This research provides an overview for the advanced sortin...

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Bibliographic Details
Published in2021 1st International Conference on Computer Science and Artificial Intelligence (ICCSAI) Vol. 1; pp. 154 - 160
Main Authors Marcellino, Marcellino, Pratama, Davin William, Suntiarko, Steven Santoso, Margi, Kristien
Format Conference Proceeding
LanguageEnglish
Published IEEE 28.10.2021
Subjects
Artificial intelligence
Big-O
Codes
Computer science
Efficient of Timing
Heap
Introspective
Memory management
Memory Required
Merge
Radix
Sorting
Sorting Algorithm
Timing
Visualization
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DOI10.1109/ICCSAI53272.2021.9609715

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Summary:Every algorithm has its own best-case as well as its worst-case scenario, so it is difficult to determine the best sorting algorithm just by its Big-O. Not only that, the amount of memory required also affect the algorithm's efficiency. This research provides an overview for the advanced sorting algorithms, namely Radix Sort, Heap Sort, Quick Sort, Merge Sort, and Introspective Sort, that are used directly in real life work to sort 11K GoodRead's data and compare each algorithm, in terms of time required and memory usage to complete the sort. The test is completed by using visual studio code to write the application and is implemented using python programming language. The program will do the testing for each algorithm up to 5 times in a row and will be recorded. This research show that Introspective sort is the best at time and Heap sort is the best at memory usage.
DOI:10.1109/ICCSAI53272.2021.9609715