Please answer point 3 and 4In Data Structures, you studied binary heaps. Binary heaps support the insert and extractMinfunctions in O(lgn), and getMin in O(1). Moreover, you can build a heap of n elements injust O(n). Refresh your knowledge of heaps from chapter no. 6 of your algorithms text book.Now implement Merge Sort, Heap Sort, and Quick Sort in C++ and perform the followingexperiment:1. Generate an Array A of 10^7 random numbers. Make its copies B and C. Sort A usingMerge Sort, B using Heap Sort, and C using Quick Sort.2. During the sorting process, count the total number of comparisons between array ele-ments made by each algorithm. You may do this by using a global less-than-or-equal-tofunction to compare numbers, which increments a count variable each time it is called.3. Repeat this process 5 times to compute the average number of comparisons made byeach algorithm.4. Present these average counts in a table. These counts give you an indication of how thedierent algorithms compare asymptotically (in big-O terms) for a large value of n. a. In Data Structures, you studied binary heaps. Binary heaps support the insert and extractMinfunctions in O(lgn), and getMin in 0(1). Moreover, you can build a heap of n elements injust O(n). Refresh your knowledge of heaps from chapter no. 6 of your algorithms text book.Now implement Merge Sort, Heap Sort, and Quick Sort in C++ and perform the followingexperiment:1. Generate an Array A of 107 random numbers. Make its copies B and C. Sort A usingMerge Sort, B using Heap Sort, and C using Quick Sort.2. During the sorting process, count the total number of comparisons between array ele-ments made by each algorithm. You may do this by using a global less-than-or-equal-tofunction to compare numbers, which increments a count variable each time it is called.3. Repeat this process 5 times to compute the average number of comparisons made byeach algorithm.4. Present these average counts in a table. These counts give you an indication of how thedifferent algorithms compare asymptotically (in big-0 terms) for a large value of n.

#include<iostream>#include<climits>using namespace std; // Prototype of a utility…

Answered: In Data Structures, you studied binary…

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Please answer point 3 and 4

In Data Structures, you studied binary heaps. Binary heaps support the insert and extractMin
functions in O(lgn), and getMin in O(1). Moreover, you can build a heap of n elements in
just O(n). Refresh your knowledge of heaps from chapter no. 6 of your algorithms text book.
Now implement Merge Sort, Heap Sort, and Quick Sort in C++ and perform the following
experiment:
1. Generate an Array A of 10^7 random numbers. Make its copies B and C. Sort A using
Merge Sort, B using Heap Sort, and C using Quick Sort.
2. During the sorting process, count the total number of comparisons between array ele-
ments made by each algorithm. You may do this by using a global less-than-or-equal-to
function to compare numbers, which increments a count variable each time it is called.
3. Repeat this process 5 times to compute the average number of comparisons made by
each algorithm.
4. Present these average counts in a table. These counts give you an indication of how the
dierent algorithms compare asymptotically (in big-O terms) for a large value of n.

a. In Data Structures, you studied binary heaps. Binary heaps support the insert and extractMin
functions in O(lgn), and getMin in 0(1). Moreover, you can build a heap of n elements in
just O(n). Refresh your knowledge of heaps from chapter no. 6 of your algorithms text book.
Now implement Merge Sort, Heap Sort, and Quick Sort in C++ and perform the following
experiment:
1. Generate an Array A of 107 random numbers. Make its copies B and C. Sort A using
Merge Sort, B using Heap Sort, and C using Quick Sort.
2. During the sorting process, count the total number of comparisons between array ele-
ments made by each algorithm. You may do this by using a global less-than-or-equal-to
function to compare numbers, which increments a count variable each time it is called.
3. Repeat this process 5 times to compute the average number of comparisons made by
each algorithm.
4. Present these average counts in a table. These counts give you an indication of how the
different algorithms compare asymptotically (in big-0 terms) for a large value of n.

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