performs 10 n2 basic operations, while algorithm B does 300ln(n) basic operations, resulting in a difference of 10 n2. At what point does algorithm B begin to outperform

John tells you that a certain algorithm runs in time n(n2 +200n), and Bill tells you that the same algorithm runs in time (n). Assume that both statements are correct, which one is more informative, i.e., gives you a better estimation of the running time? Why?

Given an unsorted array A of integers of any size, n ≥ 3, and an integer value x, write an algorithm as a pseudo code (not a program!) that would find out if there exist EXACTLY3 occurrences in the array with value x.  What is the time complexity of your algorithm, in terms of Big-O? What is the space complexity of your algorithm, in terms of Big-O? What if , the given array A is sorted. Will time complexity change from the case that A was unsorted? • If yes; give a new algorithm that achieves this better complexity (indicate the time complexity as of that algorithm). • If no, explain why such new constraints/conditions cannot lead to a better time complexity.

Suppose an algorithm requires 2n steps to complete a task for an input of size n. If the size of the input is doubled, what happens to the number of steps?     The number of steps for the larger input is equal to the number of steps for the original input.     The number of steps for the larger input is twice the number of steps for the original input.     The number of steps for the larger input is four times the number of steps for the original input.     The number of steps for the larger input is the square of the number of steps for the original input.     The number of steps for the larger input is more than the number of steps for the original input, but is none of the above.

Hello, hope you're having a great day. Can you please help me do exercise 1, 2 and 3 please? Thank you!