uthors of modern software libraries are nice enough to include a sort$()$ function

for use in applications. These libraries claim that the sort functions use an algorithm that is at least

O$($n $$ lg$($n$))$ in nature. Let$$s test this claim by writing a small program.

In your language of choice, use the sort routine provided by the language to sort randomly generated

data sets of $5,10,50,100,500,1000,5000,$ and $10,000$ integers. Since we are looking at average data

set sizes, you will need to sort at least $10$ or more random data sets for each data set size.

You should implement an algorithm that looks like this:

Algorithm $3$: Test the order of the library sort

Output: A data set of run times for each data set size

for size in $[5,10,50,100,500,1000,5000,100000]$ do

Set totalRunTime $0$;

for runNumber in $[0..$ NumberOfRuns$)$ do

GenerateRandomDataSet $($dataSet$,$size$)$;

Note start time;

Sort $($dataSet$)$;

Note end time;

Set elapsed time to difference between end and start times;

Add elapsed time to totalRunTime;

Set averageRunTime $=$ totalRunTime $/$ NumberOfRuns;

The function GenerateRandomDataSet$($dataSet$,$ size$)$ needs to generate a random set of integers

of whatever size is passed into the function as an input