cst370 week2

    This week we focused on understanding different ways to analyze algorithm efficiency using Big O, Big Theta, and Big Omega notation. We discussed how each notation is used to describe algorithm behavior. Specifically how and when Big Theta is the most appropriate choice when compared to Big O. This helped understand why we might provide a tight bound versus an upper bound when analyzing an algorithm.

    Later we took a look at recursive algorithm analysis, including using backward substitution to determine time complexity for recursive algorithms. We also learned about the brute force technique and how it solves problems by exhaustively checking all possible solutions.

    I enjoyed the homework for this week, as it gave me a great opportunity to reevaluate my approach and helped me to practice writing more efficient solutions rather than settling for the first one that worked.

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