CSUMB Learning Journal 2025

 This week in CST370 focused on foundational algorithm design strategies and search techniques. We started with brute force string matching and exhaustive search , which involve checking all possible matches or solutions to find a correct answer. Although these approaches are often inefficient, they are simple to understand and serve as a good starting point for problem solving. We then learned about the depth-first search (DFS) algorithm , which explores a structure by going as deep as possible before backtracking. DFS is useful for tasks like path finding and exploring all possible configurations, especially when memory usage needs to be minimized. Next, we studied the breadth-first search (BFS) algorithm , which explores all nodes at one level before moving deeper. BFS is especially effective for finding the shortest path in unweighted graphs, though it typically requires more memory than DFS. Finally, we were introduced to divide and conquer algorithm design , a strategy tha...

       This week in CST370 we focused on understanding how to analyze and reason about algorithm efficiency. We began with asymptotic notations , which provide a way to describe an algorithm’s performance as input size grows. Notations like Big-O help us focus on long-term behavior rather than exact runtimes, making it easier to compare algorithms. We then explored the analysis of nonrecursive algorithms , where we evaluate loops and statements to determine time complexity. This reinforced how simple code structures can still have significant performance impacts depending on how often operations are repeated. Next, we studied the analysis of recursive algorithms , which introduced recurrence relations. Learning how to break a problem into smaller subproblems and analyze how recursive calls contribute to overall complexity helped clarify how recursion affects performance. Finally, we covered brute force algorithm design , which emphasizes solving problems by exhaustiv...

      This journal entry marks the first week completion of my CST370 class. I'm going to be honest, this looks like it will be a tough one. This week we covered a variety of topics in the lectures ranging from and introduction to algorithms, some pseudocode examples, important problem types (sorting and searching, graphs), fundamental data structures, algorithm analysis frameworks, and some puzzle problems. It was a lot to cover in a week one but I believe that it was all necessary for us to learn/review ASAP. I really liked learning about the weighted coin puzzle. It was a basic puzzle but it teaches you how you can narrow down a fake among a group of things, that logic can be applied to many different scenarios.       After learning about the coin puzzle I immediately thought of a similar puzzle with light bulbs and switches where you trying and find out which switch turns on the light in another room(3 switches 1 light bulb). Where you try to find ...