5] 2. Below is an algorithm which (naively) counts the number of distinct elements in an array of n integers. Every element in the array is compared to the previous entries. If it is not found among these entries, the count (of distinct elements) is increased by 1. (a) Determine the worst-case time-complexity function f(n) in terms of the array size n and find the best big-oh approximation of f. Algorithm: Distinct Element Count Input: An array of integers 1], 22, ..., In Output: The number of distinct elements count 0 for i 1 to n do found false + 1 to i-1 do | if x; = x, then found + true end if found false then count count +1 end return count for j Note: The inner for loop does not run if the end value i - 1 is smaller than the start value 1 (which happens when i 1). (b) What would change in a best-case analysis? Is the best big-oh approximation different than in the worst case? Note: This can be answered in a few sentences; do not write paragraphs of explanations