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COMP2080 Assignment 1 (10%) Due: 6th March XXXXXXXXXX:30PM Given: 13th February 2022 Submission Instructions: 1) Fill in your full name and student number in the spaces provided further down this...

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COMP2080
Assignment 1 (10%)
Due: 6th March XXXXXXXXXX:30PM
Given: 13th Fe
uary 2022
Submission Instructions:
1) Fill in your full name and student number in the spaces provided further down this page.
2) Fill in all results into the tables provided.
3) Paste the code for each class and main program into this document after the question.
4) Upload this document to blackboard .
· You must have your name and student ID number commented in all code submitted. Failure to do this will result in a loss of marks.
· All submissions should at least compile.
· Non-compiling assignments will NOT be marked and will be given a grade of 0.
· All your submissions should be suitably documented.
Name :_________________
Student ID:_________________
Description:
The purpose of this question is to allow the student to independently compare the run time of various sorting and searching algorithms. This will allow the student to get a better understanding of time complexity. It also aims to build an appreciation of the effects that the size and organization of data have on the speed of algorithms.
The sorting algorithms that will be examined are:
a) Selection sort
) Insertion sort
c) Merge sort
d) Quick Sort
All sorting algorithms must sort the a
ays in descending order.
Each sorting and searching algorithm will be comparatively run on a
ays of the following sizes:
1. fifty (50)
2. one thousand (1,000)
3. ten thousand (10,000)
4. one hundred thousand (100,000)
5. one million (1,000,000)
Each sort and search is to be tested on the same data set to strive for some consistency.
Sorting Methodology and Requirements:
1. Create a core data set called “coreData” which must be a single a
ay of size one million (1,000,000) integers filled with random numbers between one (1) and two million (2,000,000).
2. For each comparative sorting test, four (4) copies (one for each sort to be tested) consisting of the same data from “coreData” must be made. For example, if the comparative test is on one thousand (1,000) elements, four a
ays of size XXXXXXXXXXshould be made and filled with a copy of the first one thousand XXXXXXXXXXelements of “coreData”.
All recorded times must be measured using System.nanoTime() for consistency. An example of how to use it is given below.
long start = System.nanoTime();
code to be tested
long end = System.nanoTime();
long timeTaken = end – start;
    Test data size
    Time unit
    50
    nanoseconds
    1,000
    nanoseconds
    10,000
    nanoseconds
    100,000
    nanoseconds
    1,000,000
    milliseconds
The unit for printing the time must be done according to the following table:
Output requirements:
The name of each sorting algorithm tested and the time it took to sort the data must be shown grouped by the test data size. For example if the test data size is fifty (50), the time taken for all the sorting algorithms to sort the data must be shown one after another.
Fill in the tables below with the results of your tests.
Sorting Comparison
    
    Number of Items
    Selection Sort
    50
    1,000
    10,000
    100,000
    1,000,000
    Run 1
     
     
     
     
     
    Run 2
     
     
     
     
     
    Run 3
     
     
     
     
     
    Run 4
     
     
     
     
     
    Run 5
     
     
     
     
     
    Average
     
     
     
     
     
    
    Number of Items
    Insertion Sort
    50
    1,000
    10,000
    100,000
    1,000,000
    Run 1
     
     
     
     
     
    Run 2
     
     
     
     
     
    Run 3
     
     
     
     
     
    Run 4
     
     
     
     
     
    Run 5
     
     
     
     
     
    Average
     
     
     
     
     
    
    Number of Items
    Merge Sort
    50
    1,000
    10,000
    100,000
    1,000,000
    Run 1
     
     
     
     
     
    Run 2
     
     
     
     
     
    Run 3
     
     
     
     
     
    Run 4
     
     
     
     
     
    Run 5
     
     
     
     
     
    Average
     
     
     
     
     
    
    Number of Items
    Quick Sort
    50
    1,000
    10,000
    100,000
    1,000,000
    Run 1
     
     
     
     
     
    Run 2
     
     
     
     
     
    Run 3
     
     
     
     
     
    Run 4
     
     
     
     
     
    Run 5
     
     
     
     
     
    Average
     
     
     
     
     
Searching Methodology and Requirements:
1. Create a core data set called “coreData” which must be a single a
ay of size one million (1,000,000) integers filled with random numbers between one (1) and two million (2,000,000). This a
ay must then be sorted in descending order. (You may use the sorted a
ay from the first part).
2. For each comparative search test, you must search for the number 2,500,000 (two million five hundred thousand). This number does not exist in the a
ay and represents the worst case for both searches. You must repeat the tests 5 times with binary search and linear search, timing how long it takes to complete for each dataset size. Place the results in the table below.
All recorded times must be measured using System.nanoTime() for consistency.
Fill in the tables below with the results of your tests.
Searching Comparison
    
    Number of Items
    Binary Search
    50
    1,000
    10,000
    100,000
    1,000,000
    Run 1
     
     
     
     
     
    Run 2
     
     
     
     
     
    Run 3
     
     
     
     
     
    Run 4
     
     
     
     
     
    Run 5
     
     
     
     
     
    Average
     
     
     
     
     
    
    Number of Items
    Linear Search
    50
    1,000
    10,000
    100,000
    1,000,000
    Run 1
     
     
     
     
     
    Run 2
     
     
     
     
     
    Run 3
     
     
     
     
     
    Run 4
     
     
     
     
     
    Run 5
     
     
     
     
     
    Average
     
     
     
     
     
PASTE YOUR CLASSES FOR THE ASSIGNMENT AND MAIN HERE:
Your code must have your name commented in each new class.
Answered Same DayMar 07, 2022

Solution

Neha answered on Mar 08 2022
34 Votes
COMP2080
Assignment 1 (10%)
Due: 6th March 2022 11:30PM
Given: 13th Fe
uary 2022
Submission Instructions:
1) Fill in your full name and student number in the spaces provided further down this page.
2) Fill in all results into the tables provided.
3) Paste the code for each class and main program into this document after the question.
4) Upload this document to blackboard .
· You must have your name and student ID number commented in all code submitted. Failure to do this will result in a loss of marks.
· All submissions should at least compile.
· Non-compiling assignments will NOT be marked and will be given a grade of 0.
· All your submissions should be suitably documented.
Name :_________________
Student ID:_________________
Description:
The purpose of this question is to allow the student to independently compare the run time of various sorting and searching algorithms. This will allow the student to get a better understanding of time complexity. It also aims to build an appreciation of the effects that the size and organization of data have on the speed of algorithms.
The sorting algorithms that will be examined are:
a) Selection sort
) Insertion sort
c) Merge sort
d) Quick Sort
All sorting algorithms must sort the a
ays in descending order.
Each sorting and searching algorithm will be comparatively run on a
ays of the following sizes:
1. fifty (50)
2. one thousand (1,000)
3. ten thousand (10,000)
4. one hundred thousand (100,000)
5. one million (1,000,000)
Each sort and search is to be tested on the same data set to strive for some consistency.
Sorting Methodology and Requirements:
1. Create a core data set called “coreData” which must be a single a
ay of size one million (1,000,000) integers filled with random numbers between one (1) and two million (2,000,000).
2. For each comparative sorting test, four (4) copies (one for each sort to be tested) consisting of the same data from “coreData” must be made. For example, if the comparative test is on one thousand (1,000) elements, four a
ays of size (1000) should be made and filled with a copy of the first one thousand (1000) elements of “coreData”.
All recorded times must be measured using System.nanoTime() for consistency. An example of how to use it is given below.
long start = System.nanoTime();
code to be tested
long end = System.nanoTime();
long timeTaken = end – start;
    Test data size
    Time unit
    50
    nanoseconds
    1,000
    nanoseconds
    10,000
    nanoseconds
    100,000
    nanoseconds
    1,000,000
    milliseconds
The unit for printing the time must be done according to the following table:
Output requirements:
The name of each sorting algorithm tested and the time it took to sort the data must be shown grouped by the test data size. For example if the test data size is fifty (50), the time taken for all the sorting algorithms to sort the data must be shown one after another.
Fill in the tables below with the results of your tests.
Sorting Comparison
    
    Number of Items
    Selection Sort
    50
    1,000
    10,000
    100,000
    1,000,000
    Run 1
    5134 
     5077381
     181847794
     5791348773
    5991349773 
    Run 2
    39517 
    3145690 
     123919457
     4316861060
    8816867860 
    Run 3
     62258
    3987992 
    142005733 
    5474531263 
    5830031263 
    Run 4
    46107 
    3874315 
    117682091 
    4459005714 
    6655644444 
    Run 5
     39071
    7737978
    170981379
    3533540539
    410916167850 
    Average
     38417.4
     4764671.2
     158916210
    4547250124 
     7100847856
    
    Number of Items
    Insertion Sort
    50
    1,000
    10,000
    100,000
    1,000,000
    Run 1
     29625
    3561909 
    27370035 
    1417805639 
    2237805639 
    Run 2
    27723 
    2280115 
    32857581 
    1144437592 
    1420337580
    Run 3
    30927 
    3677227 
    22464520 
    1419186870 
    32324234344 
    Run 4
     24492
    3245493 
    22860108 
    1238094817 
    7564353455 
    Run 5
    37078
    2839874
    20101737
    1129618717
    113728845760 
    Average
     30398.33
     3120923.6
     25130796.2
    1269828727 
     10886682755
    
    Number of Items
    Merge Sort
    50
    1,000
    10,000
    100,000
    1,000,000
    Run 1
    45546
    5143896
    151179142 
    4484401024 
    4094401024
    Run 2
    39787 
    783115 
    2249320 
    23992943 
    25902740 
    Run 3
     76790
    1302573 
    2080258 
    22389749 
    32434434 
    Run 4
     50476
    1462717 
    1948696 
    17083614 
    343444565 
    Run...
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