Big Omega

Big Omega

    With the introduction of big omega we developed a number of different related proofs. In comparison to big o proofs, big omega proofs seem as if they deal more heavily with variables in terms of other variables as opposed to concrete expressions of an nth degree. Or at least that's what differentiates our big omega examples from the big o ones. In fact I'm curious to see how we'll develop the big theta idea which will essentially combine the big o and big omega ideas into one.

    As I started working on my third assignment in CSC108, going through the programming I had the mindset of minimizing runtime. I didn't necessarily go through a whole proof analyzing the total number of steps yet I did try to reduce everything to the lowest big o notation it could be while still performing the given task. This really did help with runtime efficiency which was a problem in the CSC108 assignment two.

    Another point I'd like to bring up is the runtime analysis of various sorting algorithms. I'm curious as to whether this runtime is variable in certain situations based on what algorithm is used. I'd assume it is as it'd make sense that if certain algorithms were better suited in different situations then the runtime would vary dependent on what situation is currently occurring. All in all, I certainly appreciate the whole run time analysis of this course and see it's usefulness in computer science.