Java Eclipse Data Structures Programming Project Help Need help in java. Instructions Provided. Needs to be done in eclipse. Price negotiable. ***There is

Java Eclipse Data Structures Programming Project Help Need help in java. Instructions Provided. Needs to be done in eclipse. Price negotiable. ***There is no
correlation between
Parts. Each Part is
different***
Part 1
Sorts.java is a test harness program for testing various sorting methods. The program
includes a swap method that is used by all of the sorting methods to swap array elements.
a) Modify the program so that after calling a sorting method the program prints out
the number of swaps required to sort an array of 50 random integers.
b) Test the modified program by running the selectionSort, bubbleSort,
shortBubble, insertionSort, mergeSort, heapSort,and quickSort.
c) Modify the program so that after calling a sorting method the program prints out
the number of comparisons required to sort an array of 50 random integers.
d) Test the modified program by running the selectionSort, bubbleSort,
shortBubble, insertionSort, mergeSort, heapSort, and quickSort.
e) In order to run the program just once, a backupValues array can be used in the
initValues method. Use it to save all of the random numbers assigned to the
values array. Then, create a resetValues method to reset the values array back to
the original values by using the backupValues array each time you call one of the
sorting methods. Of course, the backup array doesn’t need to be reset for the first
call to a sort—just the subsequent calls to the other sorts, because you need to
start with the original unsorted array.
Here is a sample output:
Initial Array The
values array is:
88 49 69 19 03 54
92 72 78 10 08 13
30 44 80 74 66 60
09 97 62 60 21 51
08 18 48 41 38 22
0 swaps.
0 comparisons.
57
46
79
63
58
83
29
36
83
99
42
73
05
87
19
48
90
63
22
94
SelectionSort The
values array is:
03 05 08 08 09 10
21 22 22 29 30 36
46 48 48 49 51 54
62 63 63 66 69 72
80 83 83 87 88 90
49 swaps.
1225 comparisons.
13
38
57
73
92
18
41
58
74
94
19
42
60
78
97
19
44
60
79
99
BubbleSort
The values array is:
03 05 08 08 09 10 13
21 22 22 29 30 36 38
46 48 48 49 51 54 57
62 63 63 66 69 72 73
80 83 83 87 88 90 92
621 swaps.
1225 comparisons.
ShortBubble The
values array is:
03 05 08 08 09 10 13
21 22 22 29 30 36 38
46 48 48 49 51 54 57
62 63 63 66 69 72 73
80 83 83 87 88 90 92
621 swaps.
1215 comparisons.
InsertionSort The
values array is:
03 05 08 08 09 10 13
21 22 22 29 30 36 38
46 48 48 49 51 54 57
62 63 63 66 69 72 73
80 83 83 87 88 90 92
621 swaps.
667 comparisons.
MergeSort doesn’t
swap
The values array is:
03 05 08 08 09 10 13
21 22 22 29 30 36 38
46 48 48 49 51 54 57
62 63 63 66 69 72 73
80 83 83 87 88 90 92
0 swaps.
223 comparisons.
QuickSort The
values array is:
03 05 08 08 09 10 13
21 22 22 29 30 36 38
46 48 48 49 51 54 57
62 63 63 66 69 72 73
80 83 83 87 88 90 92
73 swaps.
271 comparisons.
HeapSort The values
array is:
03 05 08 08 09 10 13
21 22 22 29 30 36 38
46 48 48 49 51 54 57
18
41
58
74
94
19
42
60
78
97
19
44
60
79
99
18
41
58
74
94
19
42
60
78
97
19
44
60
79
99
18
41
58
74
94
19
42
60
78
97
19
44
60
79
99
18
41
58
74
94
19
42
60
78
97
19
44
60
79
99
18
41
58
74
94
19
42
60
78
97
19
44
60
79
99
18 19 19
41 42 44
58 60 60
62 63 63 66 69 72 73 74 78 79
80 83 83 87 88 90 92 94 97 99
49 swaps.
419 comparisons.
Part 2
1) Insert 10 random employees into an HMap with an initial size of 10
and load factor of 1. Print the HMap after each insertion—the
contents of the HMap will be displayed. This is just a test to make
sure the toString method is working and displaying accurate results
before extensive testing.
Compute the time required to put each employee into the HMap and compute
the load ratio after each insertion. Print these two computations after
each insertion.
2) Implement and test the remove method for the HMap class. Print out
the HMap after removing an employee and make sure the remove method
is working properly. Now you are all set to begin your analysis.
3) Insert the following number random employees into a HMap with an
initial size of 50.
a) 50
b) 100
c) 150
4) Compute the total time required to insert all 100 items into the
HMap given the following load factors: 0.50, 0.75, 0.90; this requires
three tests for all three cases in step 3) above.
5) Compute the total time required to remove all of the items from the
HMap. Modify the current capacity of the HMap in the implementation
of the remove method.
For example:
If the original capacity is 50 with a load factor of 0.50, after
inserting 100 employees, the current capacity is 200 (the HMap gets
enlarged three times). Now, after removing the employees, the load factor
will fall below the threshold of 0.50 at some point. After all of the
employees are removed, the current capacity should be reset to the
original capacity (50).
Include all three load factors in your computations here—that includes
all three sizes in step
3) as well (that’s 9 test cases!). This is a lot of testing! Be sure to
generate a nice report*. You can submit the report in the comments
section at the beginning of your driver program or in a separate .txt
file along with your lab files.
6)
Modify the enlarge method to generate better runtimes for the three
cases above? In your report, document how and why you did this. Give me the
runtimes for before and after. If there is no significant difference,
explain why.
7)
Write a report of your findings in the comment area at the top of
your HMapDriver program. An example of the analysis could be that one load
factor allows for a better performance over another, etc.
*Make sure you isolate your testing for all of the cases above. This is the
only way to make sure the runtimes don’t conflict with each other. For
example, only test the case of inserting 150 with a load factor of 0.50 during
runtime. Also, run this in a simulation of at least 1000 iterations and make
sure you clear out the HMap before each run through. The best way to do this
is to pass two runtime parameters before each execution of the simulation. If
you are running with eclipse, follow these instructions to input the runtime
parameters:
1) right-click on the driver file (i.e. Lab9_Temesvari.java) and go to
Properties.
2) from Properties, go to Run/Debug Settings and select New, then Java
Application.
3) then go to (x)= Arguments, and then enter the two Program Arguments
into the window. Make sure you give at least one whitespace character
between each value—this can be a space or a newline. For example:
150 0.50
OR
150
0.50
***There is no correlation between Parts. Each Part is different***
Part 1
Given the following files:
IncreaseFactorial.java
FactorialCounter.java
TestFactorial.java
Complete the parallelized version of the factorial method (n!).
The multipleIncrement method of the FactorialCounter class needs to be completed such that it uses
the increment method.
The result needs to be computed before it is returned from the factorialParallel method of
TestFactorial class.
The multipleIncrement method requires a nested for loop to simulate the multiplication.
A quick tip:
Since you are modifying the count via the increment method, use a copy of it before entering the
loop structure—otherwise, you will be chasing the count in the loop structure forever.
Here is a video to help you better understand what is happening in this parallel scheme.
Answer the following questions:
1) Remove the comments within the run method of the IncreaseFactorial class and observe the
different threads executing with their various hold values.
Do all four threads get to work all of the time?
2) Update the code to use only two threads. Does it run faster? Why, or why not?
3) Why does the parallelized method run slower than the serial version?
Part 2
Write a (N + logN) contains method for the BST such that it is not recursive. The current provided
BST contains method is recursive.
Use the following startup code for the method in the BinarySearchTree class:
public boolean nonRecContains(T target){
LinkedQueue q = new LinkedQueue();
inOrder(root, q);
//O(N)
return
q.contains(target);
}
Since the LinkedQueue calls its contains method, you must implement the contains method inside
the LinkedQueue class. Here is the startup code for the contains method in the LinkedQueue class:
public boolean contains(T target){
//return true if target is found and false if target is not found.
T[] elements = (T[]) new Object[size()];
for(int i = 0; i < elements.length; i++){ //O(N) elements[i] = (T) dequeue(); System.out.println(elements[i]); } //the code for the O(log N) search here: T item; } Please note the use of the compareTo method on the type T data type requires the use of the following syntax, due to the unknow data type T: ((Comparable Purchase answer to see full attachment

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