====== Asymptotics ====== In this topic we will learn how to compare the performance of algorithms on large inputs using //asymptotic notations// — the //Big Oh// and the //Big Omega//. In our examples, we will mainly deal with running times of algorithms (so-called **time complexity**); analogously one can analyze memory usage (so-called **space complexity**), too. We will also investigate how the success probability of an algorithm can depend on input size or security parameters using the concepts //negligible//, //overwhelming// and //noticeable//. {{:asymptotics:Big_Oh.png?nolink&200}} [[asymptotics:01_the_need_for_asymptotic_notation_a_case_study]]\\ [[asymptotics:02_big_oh]]\\ [[asymptotics:03_big_omega]]\\ [[asymptotics:04_multiple_variables]]\\ [[asymptotics:05_polynomial_complexity]]\\ [[asymptotics:06_the_negligible_the_noticeable_and_the_overwhelming]]