Which of the following is true about searching elements in an ordered array? You cannot use binary search on an ordered array so the performance is O(n) If there are no holes in the array and the elements are all next to each other, then the performance for search improves to O(1) If you do a linear search on a sorted array, the performance improves to O(log n)

Implement external sort: for sort phase use normal sort,   for merge phase use two way merge to merge n sorted files (merge2way(n)), for array sort use heapsort. Also write merge(f1, f2, f3) to merge two sorted files f1 and f2 into f3.. Write mergenway(n) method and print execution time of both merges for initial input file over 10MB data. A sample input is as follow:Note:First input is max array size for sort           10   84   82   52   80   96   85   75   75   82   87  92   89   57   94   93   92   63   99   87  72   73   56   74   50   84   62   72   55   86   75  74  100   83   60   53   68   89   67  66  65   72   94   73   54   98   96   85   75   75   82   87  92   89

Find the complexity of the function used to find the k th the smallest integer in an unordered array of integer

During each iteration of Quick Sort algorithm, the first element of array is selected as a pivot. The algorithm for Quick Sort is given below. Modify it in such a way that last element of array should be selected as a pivot at each iteration. Also explain the advantages.

Coding in Python, we have the function to perform this task, V col_Hdeg whichinputs the adjacency matrix A of the graph and initializes the array vert_color s tohold vertex colors. It then calculates the degree of each vertex and stores it in thearray degrees.The while loop iterates until all vertices are colored and at each iteration, thevertex v with the highest degree is colored. The array temp is used to find the currentcolors of the neighbors of vertex v and an unused smallest color is determined aftersorting this array.

Below is the exercise for unsorted arrays. True or False: For each statement below, indicate whether you think it is True or False 3) 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 5) Because the update algorithm depends on using linear search, its performance is O(1) in the worst case scenario 6) 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) 7) 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)

Heapsort has heapified an array to: 96 71 57 36 25 and is about to start the second for loop. What is the array after each loop iteration? i= 4: Ex: 86, 75, 30 i = 3: i = 2: i = 1:

The PARTITION(A) procedure inputs an array A, and takes the fınal element x = A[r] as the pivot element. The output is an array where all elements to the left of x are less than x, and all elements to the right of x are greater than x. An example is provided on pg. 172 of the textbook. In this example, A = [2,8,7,1,3,5,6,4]. The pivot element is x=4 (highlighted in red). The end result of PARTITION is [2,1,3,4,7,5,6,8]. Notice that all elements to the left of 4 are less than 4, and all elements to the right of 4 are greater than 4. I strongly encourage you to go through this example, step by step. Let A = [1,2,7,8,9,6,3,4,5]. Determine PARTITION(A).

Heapsort has heapified an array to: 98 71 63 38 16 and is about to start the second for loop. What is the array after each loop iteration? i = 4: Ex: 86, 75, 30 i = 3: i = 2: i = 1: