Design an algorithm to find min and max -The algorithm should do, at most, about 3n/2 comparisons (in the worst case scenario) for problems of size n elements. - The algorithm is supposed to take in a list, assumed to be integers. - The list given to the algorithm is unsorted.

Suppose that, even unrealistically, we are to search a list of 700 million items using Binary Search, Recursive (Algorithm 2.1). What is the maximum number of comparisons that this algorithm must perform before finding a given item or concluding that it is not in the list? Solution: 고

Counting sort always obtains in the worst case   the complexity to O(n) n being the number of elements in a input list

Assume that you are given an array containing n integer numbers from the set {0, 1, . . . , k} for some k ≤ n. Design an algorithm to produce a sorted array containing those n numbers in non-decreasing order in time O(n). Present the pseudocode for the algorithm and provide a justification for its running time.

Evaluations of algorithmsCalculate the algorithmic complexity of binary search in terms of time. Please offer detailed instructions.

A sequential search of a sorted list can halt when the target is less than a given element in the list. Define a modified version of this algorithm and state the computational complexity, using big-O notation, of its best-, worst-, and average- case performances.

Performing sequential search for an item that is not present in an unsorted list has Best-Case running time equals to:           1     log(n)     n     n2