Exercise 2 (Binary Search) Assume a binary search is performed on the following array of integers: {1, 14, 15, 24, 55, 59, 73, 90, 94, 99} Trace through each iteration of the algorithm, writing the number that will be the middle element and the left and right bounds (indexes), when searching for the number 73.
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- Matrix Addition• Write an addition function that accepts two 2D numpy arrays, andreturns the sum of the two (if they are the same size). This functionshould test that the arrays are the same size before performing theaddition. If the arrays are not the same size, the function shouldreturn -1. solve in pythonAlgorithms Assignment Quicksort is a divide and conquer algorithm that re-order the elements over the same input array (to be distinguished from the quicksort version that implements out-place re-ordering). There are two basic operations in the algorithm, swapping items in place and partitioning a section of the array. In light of this, write a report about the quicksort algorithm, which includes the following: • Discuss sorting as a problem and the algorithms used for sorting (briefly discuss merge-sort, insertion sort, etc.). • Discuss and explain the quicksort algorithm (Step, Pseudo-code). • Implement the algorithm using Java/Python and add comments to the code. Show the output of the algorithm (screenshots). • Analyze the best, worst and average case. Provide and analyze example inputs for the best, worst and average cases (use the implementation). Some good references: https://www.geeksforgeeks.org/quick-sort/ https://en.wikipedia.org/wiki/Quicksort01. ""Implementation of the Misra-Gries algorithm.Given a list of items and a value k, it returns the every item in the listthat appears at least n/k times, where n is the length of the array By default, k is set to 2, solving the majority problem. For the majority problem, this algorithm only guarantees that if there isan element that appears more than n/2 times, it will be outputed. If thereis no such element, any arbitrary element is returned by the algorithm.Therefore, we need to iterate through again at the end. But since we have filtredout the suspects, the memory complexity is significantly lower thanit would be to create counter for every element in the list. For example:Input misras_gries([1,4,4,4,5,4,4])Output {'4':5}Input misras_gries([0,0,0,1,1,1,1])Output {'1':4}Input misras_gries([0,0,0,0,1,1,1,2,2],3)Output {'0':4,'1':3}Input misras_gries([0,0,0,1,1,1]Output None. """
- AIM: Write a program to do Binary Search using a given Search Key in a Sorted Linear Array 'A' which has N values in it. Description: The binary search algorithm can only be used with sorted array and eliminates one half of the elements in the array being searched after each comparison. The binary search algorithm applied to our array A works as follows: Algorithm: (Binary Search) Here A is a sorted Linear Array with N elements stored in it in sorted order and SKEY is a given item of information to search. This algorithm finds the location of SKEY in A and if successful, it returns its location otherwise it returns -1 for unsuccessful. BinarySearch (A, N, SKEY) [Initialize segment variables.] 1. Set START=0, END=N-1 and MID=int((START+END)/2). 2. Repeat Steps 3 and 4 while START ≤ END and A[MID]+SKEY. 3. If SKEY< A[MID] Then Set END=MID-1. Else Set START=MID+1. [End of If Structure.] 4. Set MID=int((START +END)/2). [End of Step 2 loop.] 5. If A[MID] = SKEY then Set LOC= MID Else Set…Best Partition You are given an array of positive numbers of size N and an integer K. You need to partition the array into K continuous segments. For each segment, the sum of its elements needs to be calculated. The segment with the minimum sum is called the bestSegment and the sum of the elements of the bestSegment is called the bestSum. For all possible combinations of partitions of the array when divided into K segments, their bestSum needs to be calculated and the one among them with maximum value needs to be returned. Input Specification: input1: an array of N positive numbers input2: an integer N denoting the length of the array input3: an integer K Output Specification: Return an integer denoting the maximum value of all possible bestSum. Example 1: input1: (1,2,3,4} input2: 4 input3: 2 Output: 4 Explanation: You can partition the given array into 2 continuous segments in the following manner- • 123 14- the sum of individual segments is (6,4) and the bestSum is 4 • 12134- the…1.""Implementation of the Misra-Gries algorithm.Given a list of items and a value k, it returns the every item in the listthat appears at least n/k times, where n is the length of the array By default, k is set to 2, solving the majority problem. For the majority problem, this algorithm only guarantees that if there isan element that appears more than n/2 times, it will be outputed. If thereis no such element, any arbitrary element is returned by the algorithm.Therefore, we need to iterate through again at the end. But since we have filtredout the suspects, the memory complexity is significantly lower thanit would be to create counter for every element in the list. For example:Input misras_gries([1,4,4,4,5,4,4])Output {'4':5}Input misras_gries([0,0,0,1,1,1,1])Output {'1':4}Input misras_gries([0,0,0,0,1,1,1,2,2],3)Output {'0':4,'1':3}Input misras_gries([0,0,0,1,1,1]Output None""".expl.
- *Data Structures and Algorithm Professor Holmes came up with the idea of a sorting algorithm that he calls Trinary Sort which he claims is asymptotically faster than merge sort, despite being similar in logic. Unlike merge sort, trinary sort splits the input list into three roughly equal parts at each step of the recursion as long as the list is splittable (i.e., has at least 3 elements in this case). The merge operation, similar to what it does in mergeSort, takes three already sorted subarrays, and merges them. (a) In merge sort, merge operation makes exactly n−1 comparisons in total to merge two lists of size n/2 in the worst case, which takes O(n) time. How many comparisons will the merge operation of Trinary sort make in the worst case to merge three sublists of size (n/3) (give an exact number)? Why? What would be the asymptotic bound? (b) What is the total running time of the Trinary Search algorithm? Show it using the tree expansion method.6 - Merge sorted arrays Program a method merge_sorted(a,b) that when given two sorted arrays a and b, returns a new sorted array c that has the elements from array a and array b. For example when given = [1,3,5,6,10] a b = [1,4,6,8] %3D the resulting array should be: C = = [1,1,3,4,5,6,6,8,10] This method should not call a sorting method. Instead, the resulting array should be produced by "zipping" the two input arrays together: we repeatedly select the least element that we did not consider before from a and b and include this in c. For example: a = [1,3,5,6,10] b = [1,4,6,8] C = [1,1,3, ...] the arrows (^) point to the lowest element we did not consider before. Of these, element 4 from b is less than element 5 from a. For this reason, we select 4 as the next element and advance the arrow ^ for b to point to 6.True or False For each statement below, indicate whether you think it is True or False If you have an array with no “holes”, the append function performs at O(1) Inserting an element at the front and shifting all elements performs significantly worse than appending an element at the end of the list For the insert function, if the array is empty, there are no comparison operations that need to be performed and you can immediately add the new element Binary search can be used on an unsorted array to significantly improve its performance from O(n) to O(1) Because the update algorithm depends on using linear search, its performance is O(1) in the worst case scenario True If you search for and delete an element in an unsorted array and then shift the rest of the elements to fill the hole, the worst case performance is O(n) If you search for and delete an element in an unsorted array and then move the last element to fill the hole, the worst case performance is O(n)
- True or False For each statement below, indicate whether you think it is True or False If you have an array with no “holes”, the append function performs at O(1) Inserting an element at the front and shifting all elements performs significantly worse than appending an element at the end of the list For the insert function, if the array is empty, there are no comparison operations that need to be performed and you can immediately add the new element Binary search can be used on an unsorted array to significantly improve its performance from O(n) to O(1)Part 1 & 2) Lottery Winners Write a program that initializes an array with ten numbers (given below). Then let the player enter his or her lottery number. The program should ask the user if he/she wants to perform a linear search or binary search. (If the user chooses binary search, using one of the sorting algorithms we learned in the class, sort the array). Based on the searching algorithm payer chooses, it should print out the number of searching comparisons performed and if it was a winning number. int ticket[] = {85647, 62483, 13579, 26792, 52551, 33445, 79422, 76172, 93121, 26791 };\ Microsoft Visual Studio Debug Console Enter your 5-digit lottery number: 12345 Press 1 to perform linear search, 2 for binary search: 1 Original values: 85647 62483 13579 26792 52551 33445 79422 76172 93121 26791 Number of comparisons made: 10 You did not win. Microsoft Visual Studio Debug Console Enter your 5-digit lottery number: 12345 Press 1 to perform linear search, 2 for binary search: 2…Section A: Multiple Choice Questions : Q1: Consider searching element 45 using binary search in an array A [ ] = { 23, 34, 45, 67, 78, 54, 87, 91 }. The returned index would be a) Index [0] b) Index [2] c) Index [3] d) None of these Q2: In the context of recursive search a) Recursion terminates when the item is found b) Same function is called again and again c) Slower than iterative search d) All options are correct Q3: Which one of the following is an approach for a systematic trial and error to search an item? a) Binary search b) Backtracking c) Recursion d) Iteration Q4: In terms of time efficiency, the following method is ____. public int function(int n) { int result = 1; for (int k = 1; k returnType methodName(methodParameters) c) methodModifiers returnType methodName (methodParameters) d) methodModifiers returnType methodName(methodParameters) Q8: Given a function f(n) = n2 + 20n on an input parameter n, which of the following is true a) f(n)=O(1) b) f(n)=O(n) c)…