This week, I learnt about the worst case and big-oh of the case. Understanding the proof of
Wis ∈ O(n2) was the hardest proof I have seen in this course. Bounding a sort part was quiet easy to understand compared to the proof. The general proof structure was easy to understand as well since I already had much experience gained from the assignments. Then, during Wednesday's lecture, I learnt the proof of Wis ∈ Ω(n2). It was easier than the last lecture as I already previewed the lecture slide to better understand the lecture.
Big oh can be used when the time taken for the algorithm to execute command depends on the amount of information the programming it has to read. If there is too much information, the programming will take longer time to execute. O(n2) is such that its performance depends on square of n where n represents the amount of information input we are putting through the algorithm.
What I am worried about is not assignment 2, but term-test that I have next week. Although I did practice and review the lecture slides, proving Wis ∈ O(n2) and Wis ∈ Ω(n2) are still challenges for me. Other than that, I am ready to write my test next week.
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