Recursive Algorithms

This week we learned how to analyze and measure recursive algorithms, even algorithms that are partially recursive depending on some base case. This is key to analyzing and understanding the potential impact an algorithm can have on an application and it's feasibility as a software solution to a problem.

Big O notation is the classic way to express the computation required to run algorithms on a sufficiently large dataset.

We also learned a little a bit about brute force algorithms / strategy. There is benefit in the fact that brute force solutions are typically the easiest to implement and acceptable for many solutions.