CST 370 Week 2

This week was a little more challenging. In this week’s module, I learned more about asymptotic notation and how to analyze the efficiency of algorithms. I had seen Big O notation before, but learning more about Big Theta and Big Omega helped me better understand how algorithms can be described based on their growth rates. It was also interesting to learn how best-case, worst-case, and average-case scenarios can affect the analysis of an algorithm. Some of the problems were challenging at first, especially when determining the correct notation from code, but working through the examples helped make the concepts clearer.

I also learned how to analyze recursive algorithms. Recursive algorithms were more difficult for me to analyze because each function call creates additional calls that also need to be considered. Learning how to write recurrence relations and follow the number of recursive calls helped me better understand how the running time grows. Overall, I would say this week was challenging but informative, and I feel more comfortable analyzing the efficiency of both iterative and recursive algorithms.