Journal 32

 Jan 14 - Jan 20

This week, while still mostly review from my previous course, definitely ramped up in terms of difficulty. The videos and slides focused on analyzing algorithms for efficiency via asymptotic notation, namely BigO, BigΘ, and BigΩ. We were walked though multiple examples on how to identify the dominant term of a function, as well as the steps of eliminating low order terms and constant coefficients when determining time complexity. The given examples clarified that Θ notation is only appropriate when best and worst case scenarios match, and why O notation is usually used for worst-case analysis. Various example problems allowed me to practice analyzing both non-recursive and recursive algorithms, forming recurrence relations, and solving by using backward substitution. The recursive examples such as binary-style recurrences helped to reinforce how algorithm structure affects growth rates such as O(n), O(n²), and O(log n). I specifically enjoyed working through the 4 gallon bucket puzzle, as I was greatly overthinking the problem before realizing the simple solution, as is usually the case when I am programming as well. Overall, this week was very informative, and I feel as though I have a good grasp on the material thus far.