Name: _____________________________
October 9, 2015
Time Comparisons of Sorting Algorithms
For this lab, a random set of numbers has been generated and stored in a file named "rand.dat". A
subset of the numbers will be sorted using 3 different algorithms: bubble, insertion, and quick sort. The
amount of time (in seconds) needed for each sort will be displayed. Then another set of sorts will be
executed on a larger set of numbers. The point of this lab is:


Notice what happens to execution time for bubble and insertion when array size is
increased by a factor of n.
Appreciate how much faster a quick sort is.
Download the source file (timeCompare.cpp) and the .dat file (rand.dat) from D2L. Place the files in a VS
project. Compile and run.
Fill in this table as the program runs
Seconds required to sort
Number of data items sorted
Sorting Algorithm
Bubble Sort
Insertion Sort
Quick Sort
1000
5000
10,000
50,000
100,000
200,000
300,000
Look at the results for bubble sort and fill in this table.
To calculate the "factor" value for each column divide the 2nd number by the first. I have filled in the
first 2 under input size. 10,000 / 5,000 = 2. Now divide the execution time for 10,000 by the execution
time for 5000.
Bubble Sort
Input size
increased by a
factor of
From 5000 to 10000
2
From 10,000 to 50,000
5
Execution
time
increased by
a factor of
From 5000 to 50,000
From 50,000 to 100,000
From 50,000 to 300,000
From 100,000 to
200,000
From 100,000 to
300,000
How would you express execution time as a function of input size? ______________________
Now do the same thing for insertion sort.
To calculate the "factor" value for each column divide the 2nd number by the first. I have filled in the
first 2 under input size. 10,000 / 5,000 = 2. Now divide the execution time for 10,000 by the execution
time for 5000.
Insertion Sort
Input size
increased by a
factor of
From 5000 to 10000
2
From 10,000 to 50,000
5
Execution
time
increased by
a factor of
From 5000 to 50,000
From 50,000 to 100,000
From 50,000 to 300,000
From 100,000 to
200,000
From 100,000 to
300,000
How would you express execution time as a function of input size? ______________________
Now do you see why bubble sort and insertion sort belong to O(n2) ?