XDU算法实验：排序算法实验性能比较

个人博客地址：https://travis1024.github.io/

一、问题描述

实现插入排序（Insertion Sort，IS），自顶向下归并排序（Top-down Mergesort，TDM），自底向上归并排序（Bottom-up Mergesort，BUM），随机快速排序（Random Quicksort，RQ），Dijkstra 3-路划分快速排序（Quicksort with Dijkstra 3-way Partition，QD3P）。在你的计算机上针对不同输入规模数据进行实验，对比上述排序算法的时间性能。要求对于每次输入运行10次，记录每次时间，取平均值。

Comparison of running time of sorting algorithms (in Micro Seconds)

	Run1	Run2	Run3	Run4	Run5	Run6	Run7	Run8	Run9	Run10	Average
IS
TDM
BUM
RQ
QD3P

• 回答以下问题：

1. Which sort worked best on data in constant or increasing order (i.e., already sorted data)? Why do you think this sort worked best?

​ 哪种排序对不变或递增顺序的数据(即已经排序的数据)最有效?为什么你认为这种方法效果最好?

2. Did the same sort do well on the case of mostly sorted data? Why or why not?

​ 同样的排序在排序最多的数据中表现良好吗?为什么或为什么不?

3. In general, did the ordering of the incoming data affect the performance of the sorting algorithms? Please answer this question by referencing specific data from your table to support your answer.

​ 一般来说，传入数据的排序会影响排序算法的性能吗?

​ 请在回答这个问题时引用表格中的具体数据来支持你的答案。

4. Which sort did best on the shorter (i.e., n = 1,000) data sets? Did the same one do better on the longer (i.e., n = 10,000) data sets? Why or why not? Please use specific data from your table to support your answer.

5. In general, which sort did better? Give a hypothesis as to why the difference in performance exists.

6. Are there results in your table that seem to be inconsistent? (e.g., If I get run times for a sort that look like this {1.3, 1.5, 1.6, 7.0, 1.2, 1.6, 1.4, 1.8, 2.0, 1.5] the 7.0 entry is not consistent with the rest). Why do you think this happened?

二、算法实验报告+源代码

实验报告+代码开源地址（Github）