CST370 Module Two

 

CST370 Module Two

Recursive and Non-Recursive Analysis, Brute Force and Selection/Bubble Sort

What I learned this week:

This week we covered a few key topics associated with analyzing algorithms. Asymptotic Notation was the first section of our readings where we distinguished some of the underlying bounds and roles that Big O and Big Theta play when analyzing the different case scenarios. Basically, Big O notation is and will be our primary method for analysis as it covers the worst-case scenario. It's also important to note that discovery of the Big O of an algorithm requires the least amount of work, as you can deduce the worst case by locating the basic operation. However, if you were to fully analyze the algorithm, and calculate the Total Time execution, you can further deduce the Total Time by getting rid of coefficients only keeping the highest-order of the equation(in association with input size, of course). Big Theta is primarily reserved for the case in which the Best and Worst case scenario is the same, Otherwise, you can still use Big Theta, so long as you explicitly state that it is intended for the worst-case scenario.