基于时间和内存使用的高级排序算法(快速排序,堆排序,合并排序,引入排序,基数排序)的比较

Marcellino Marcellino, Davin Pratama, Steven Santoso Suntiarko, K. Margi
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引用次数: 3

摘要

每个算法都有自己的最佳情况和最坏情况,因此很难仅通过大0来确定最佳排序算法。不仅如此,所需的内存量也会影响算法的效率。本研究概述了在实际工作中直接用于对11K GoodRead数据进行排序的高级排序算法,即Radix Sort、Heap Sort、Quick Sort、Merge Sort和introspecspective Sort,并比较了每种算法完成排序所需的时间和内存使用情况。测试使用visual studio代码编写应用程序,并使用python编程语言实现。该程序将对每个算法进行连续最多5次的测试,并将被记录下来。这项研究表明,内省排序在时间上是最好的,而堆排序在内存使用上是最好的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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 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.
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