please answer the following definitions: A programming construct that is defined within a programming language to store a collection of data is a(n)____ Which of the following is not a characteristic of the merge sort algorithm? It can be implemented using recursion. It is stable. It exploits the divide-and-conquer problem-solving technique. Its worst-case time complexity is O(n2). Assuming s1 is a string object and cs1 is an array of characters, which of the following is a valid statement? cs1 = s1; strcpy(cs1,s1); cs1 = s1.c str(); s1 = cs1;

Implement the following two sorting algorithms in a program called p3.py. Write two separate functions for these algorithms. Both functions must take a list of integers as the input parameter.1) Bogosort: first shuffle the list argument (i.e., randomize the positions of every element) and then check to see if the result is in sorted order. If it is, the algorithm terminates successfully and returns True, but if it is not then the process must be repeated.2) Bozosort: choose two elements in the list at random, swap them, and then check if the result is in sorted order. If it is, the algorithm terminates successfully and returns True, but if it is not then the process must be repeated.Write a main() function and call both sorting functions using the same list as their arguments. The list can be of any size (try a small list first). Does any of your algorithms terminate? If yes, count the number of iterations it uses to sort the list. Does it always use the same number of repetitions? If…

2. An interpolation search assumes that the data in an array is sorted and uniformly distributed.Whereas a binary search always looks at the middle item in an array, an interpolation searchlooks where the sought-for item is more likely to occur. For example, if you searched yourtelephone book for Victoria Appleseed, you probably would look near its beginning ratherthan its middle. And if you discovered many Appleseeds, you would look near the lastAppleseed. Instead of looking at the element a[mid] of an array a, as the binary search would,an interpolation search examines a[index], where p = (desiredElement - a[first]) / (a[last] - a[first]) index = first + [(last – first) × p]Implement an interpolation search of an array. For particular arrays, compare the outcomesof an interpolation search and of a binary search. Consider arrays that have uniformlydistributed entries and arrays that do not. Modify and save the file asSearchComparerYourlastname.java.

Quicksort is a powerful divide-and-conquer sorting algorithm that can be described in just four lines ofpseudocode. The key to Quicksort is the PARTITION(A, p, r) procedure, which inputs elementsptorof array A,and chooses the final element x = A[r] as the pivot element. The output is an array where all elementsto the left ofxare less thanx, and all elements to the right of x are greater than x. In this question, we will use the Lomuto Partition Method from class and assume that the pivot isalwaysthe last (right-most) element of the input array. Question: Let A be an array withn= 2k−1 elements, where k is some positive integer. Determine a formula (in terms of n) for the minimum possible number of total comparisons required by Quicksort, as well as a formula for the maximum possible number of total comparisons required by Quicksort. Use your formulas to show that the running time of Quicksort is O(nlogn) in the best case and O(n2) in the worst case.

What are the steps for making a list?

Merge sort is an efficient sorting algorithm with a time complexity of O(n log n). This means that as the number of elements (chocolates or students) increases significantly, the efficiency of merge sort remains relatively stable compared to other sorting algorithms. Merge sort achieves this efficiency by recursively dividing the input array into smaller sub-arrays, sorting them individually, and then merging them back together. The efficiency of merge sort is primarily determined by its time complexity, which is , where n is the number of elements in the array. This time complexity indicates that the time taken by merge sort grows logarithmically with the size of the input array. Therefore, even as the number of chocolates or students increases significantly, merge sort maintains its relatively efficient performance. Regarding the distribution of a given set of x to y using iterative and recursive functions, the complexity analysis depends on the specific implementation of each…