Entries from 2016-05-08 to 1 day

Week3 Lecture

Big o = O, upper bound of whatever it costs algorithms, i.e. maximum time to run one algorithm. O(n^2)のように使用し、最大で変数nの2乗オーダーの時間が掛かるということ。 Omega = Lower bound Bubble sort, selection sort, insertion sort, merge…