Description
The first project involves benchmarking the behavior of Java implementations of one of the
following sorting algorithms, bubble sort, selection sort, insertion sort, Shell sort, merge sort,
quick sort or heap sort. You must post your selection in the “Ask the Professor” conference. No
more than five students may select any one algorithm.
You must write the code to perform the benchmarking of the algorithm you selected. Your
program must include both an iterative and recursive version of the algorithm. You do not have
to write the sorting algorithms yourself, you may take them from some source, but you must
reference your source.
You must identify some critical operation to count that reflects the overall performance and
modify each version so that it counts 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 correctness of the algorithm. If the array is not sorted, an exception should be
thrown.
It should also randomly generate data to pass to the sorting methods. It should produce 50 data
sets for each value of n, the size of the data set and average the result of those 50 runs. The exact
same data must be used for the iterative and the recursive algorithms. It should also create 10
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 containing the results from
the iterative algorithm and the one containing the results of the recursive algorithm.
The benchmarking program must be written to conform to the following design:
+recursiveSort(inout int[] list) +iterativeSort(inout int[] list) +getCount() : int +getTime() : long
«interface» SortInterface
YourSort +main(in String[] args) BenchmarkSorts UnsortedException
Exception
The output files should contain 10 lines that correspond to the 10 data set sizes. The first value
on each line should be the data set size followed by 50 pairs of values. Each pair represents the
critical element count and the time in nanoseconds for each of the 50 runs of that data set size.
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 50 runs and the third the coefficient of variance
of those 50 values expressed as a percentage. The fourth and fifth column should contain similar
data for the times. The coefficient of variance of the critical operation counts and time
measurement for the 50 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.
Grading Rubric
Criteria Meets Does Not Meet
100 points 0 points
Design
20 points 0 points
Implemented the required design (20) Did not implement the required design
(0)
Input 20 points 0 points
Created 10 different sizes of data sets
(10)
Did not create 10 different sizes of data
sets (0)
Produced 50 data sets for each value of
n (10)
Did not produce 50 data sets for each
value of n (0)
Sorting Algorithm
Benchmark
Calculations
35 points 0 points
Correctly averaged the count and time
results of the 50 data sets (10)
Did not correctly average the count
and time results of the 50 data sets
Calculated the coefficient of variance
of the critical operation counts and
time measurement (5)
Did not calculate the coefficient of
variance of the critical operation
counts and time measurement (0)
Included correct sorting algorithm and
code to verify data was properly sorted
(10)
Did not Include correct sorting
algorithm and code to verify data was
properly sorted (0)
Performed the necessary warm-up so
the time measurements were accurate
(10)
Did not perform the necessary warmup so the time measurements were
accurate (0)
Output
25 points 0 points
Output all the required data (15) Did not output all the required data (0)
Output displayed in the required
format (10)
Output not displayed in the required
format (0)
