Microsoft Word - Project 1.docx
CMSC 451 Project 1
The first project involves benchmarking the behavior of Java implementations of two of the
following sorting algorithms, bu
le sort, selection sort, insertion sort, Shell sort, merge sort,
quick sort or heap sort. You must post your selection of the two algorithms that you chose in the
"Ask the Professor" conference. Every student must have a unique combination of algorithms..
You must write the code to perform the benchmarking of the two algorithms that you selected.
You do not have to write the sorting algorithms yourself, you may take them from some source,
ut you must reference your source.
You must identify some critical operation to count for each algorithm that reflects the overall
performance and modify each of the two sorting algorithms so that they count that operation. In
addition to counting critical operations you must measure the actual run time in nanoseconds.
In addition, you should examine the result of each call to verify that the data has been properly
sorted to verify the co
ectness of the algorithm. If the a
ay is not sorted, an exception should be
thrown.
It should also randomly generate data to pass to the sorting methods. It should produce 40 data
sets for each value of n, the size of the data set and average the result of those 40 runs. The exact
same data must be used for both sorting algorithms. It should also create 12 different sizes of
data sets. Choose sizes that will clearly demonstrate the trend as n becomes large. Be sure that
the data set sizes are evenly spaced so this data can be used to generate graphs in project 2
This project should consist of two separate programs. The first of those programs should perform
the benchmarking described above and generate two data files, one for each of the two sorting
algorithms.
The benchmarking program must be written to conform to the following design:
The purpose of the methods in the abstract class AbstractSort are as follows:
• The method sort is an abstract method that must be implemented in both of your classes
that contain the sorting methods that you have selected
• The startSort method should be called before the sort begins and it should initialize the
counter and record the starting time of the sort
• The endSort method should be called after the sort ends and it should compute the
elapsed time of the sort
• The incrementCount method should be called whenever the critical operation that you
selected is executed and it should increment the critical operation counter
• The getCount method should return the final value of the counter
• The getTime method should return the elapsed time
The output files should contain 12 lines that co
espond to the 12 data set sizes. The first value on
each line should be the data set size followed by 40 pairs of values. Each pair represents the
critical element count and the time in nanoseconds for each of the 40 runs of that data set size.
The values on each line should be delimited by spaces.
The second program should produce the report. It should allow the user to select the input file
using JFileChooser. The report should contain one line for each data set size and five columns
and should be displayed using a JTable. The first column should contain the data set size the
second the average of the critical counts for the 40 runs and the third the coefficient of variation
(https:
en.wikipedia.org/wiki/Coefficient_of_variation) of those 40 values expressed as a
percentage. The fourth and fifth column should contain similar data for the times. The coefficient
of variation of the critical operation counts and time measurement for the 40 runs of each data set
size provide a way to gauge the data sensitivity of the algorithm.
Shown below is an example of how the report should look:
On the due date for project 1, you are to submit a .zip file that includes the source code for both
programs. All the classes should be in the default package.
You must research the issue of JVM warm-up necessary for properly benchmarking Java
programs and ensure that your code performs the necessary warm-up so the time measurements
are accurate.
Criteria
Design
Input
Calculations
Output
Meets
60 points
Implemented the required design
(60)
60 points
Created 12 different sizes of data
sets (30)
Produced 40 data sets for each
value of n (30)
105 points
Co
ectly averaged the count and
time results of the 40 data sets
(30)
Calculated the coefficient of
variance of the critical operation
counts and time measurement (15)
Included co
ect sorting algorithm
and code to verify data was
properly sorted (30)
Performed the necessary warm-up
50 the time measurements were
accurate (30)
75 points
Output all the required data (45)
Output displayed in the required
format (30)
Does Not Meet Criterion Score
0 points 760
Did not implement the required
design (0)
0 points 760
Did not create 12 different sizes
of data sets (0)
Did not produce 40 data sets fo
each value of n (0)
0 points /105
Did not co
ectly average the
count and time results of the 40
data sets
Did not calculate the coefficient of
variance of the critical operation
counts and time measurement (0)
Did not Include co
ect sorting
algorithm and code to verify data
was properly sorted (0)
Did not perform the necessary
warm-up so the time
measurements were accurate (0)
0 points 175
Did not output all the required
data (0)
Output not displayed in the
equired format (0)