big o notation
Big O notation - worst-case scenario, quantify performance as a input
size becomes arbitrary large
O(1) - constant time
O(log(n)) - logarithmic time
O(n) - linear time
O(n log(n)) - linearlogarithmic time
O(n^2) - quadric time
O(n^3) - cubic time
O(b^n) - exponential time, b > 1
O(n!) - factorial timeBigO Notation
Ο(f(n)) = { g(n) : there exists c > 0 and n0 such that f(n) ≤ c.g(n) for all n > n0. }Copyright © 2021 Codeinu
Forgot your account's password or having trouble logging into your Account? Don't worry, we'll help you to get back your account. Enter your email address and we'll send you a recovery link to reset your password. If you are experiencing problems resetting your password contact us
