CST 370 - Week 2

 Hey everyone,

This week in class was a mix of challenges, "aha" moments, and some solid progress in understanding how algorithms really tick under the hood. We dove deeper into asymptotic notations like Big-O, Big-Theta, and Big-Omega—which, to be honest, felt a little abstract at first. But once I started thinking of them as tools to describe how fast an algorithm grows, it started to click. Theta notation stood out to me the most because it gives the full picture—kind of like saying, "Hey, this is how your algorithm behaves on average, not just in the worst case."

We also covered recursive vs. non-recursive algorithms, and I practiced breaking down recurrence relations using backward substitution. There’s something strangely satisfying about peeling back the recursion layer by layer until you hit the base case and suddenly realize, “Oh! This runs in linear time!”

On the more interactive side, I shared a few tips in our class Discord group, which was pretty rewarding. It made me realize that teaching or explaining something really helps reinforce your own understanding. 

Overall, it’s been a productive week. Slowly but surely, the concepts are connecting. One step closer to feeling like I actually get algorithm analysis instead of just memorizing formulas. 

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