rge sort algorithm solve the recurrence relation to give a tight bound on the running time. mofified merge sort (A, p, r) if p

Consider median-3 quick sort and bubble sort. When using these two algorithms to sort a list of n elements that have already been sorted in increasing order, which of the following is true for the worst-case time complexity?

The Big O of the linear search is O(n) and of the binary search is O(log n). What key aspectof both the binary search (Chapter 6) and the merge sort accounts for the logarithmic portion oftheir respective Big Os?

Design of algorithms - divide-and-conquer: (a) Design a divide-and-conquer algorithm DC_PROD that receives as input an array A with n>0 integers and returns the product of the elements in A. You may assume n is a power of 2. In your algorithm identify the relevant parts of a divide-and-conquer strategy: (i) divide, (ii) conquer, and (iii) combine. (b) Establish the recurrence relation for the running time, T(n), of DC_PROD. (c) Apply the Master Theorem to give a tight bound for T(n).