Familiarity with Big O

We want to be familiar with Big O for typical algorithms:

• Given a description of a task, guess its Big O. ``First you sort the input, which is n*log(n), then ...''

• Predict how well an algorithm will scale up. ``Now that my new web service is the hottest thing in the CS Department, will it scale up to every college in the country so I can take it public and make my first billion dollars?''

• Given a program that is too slow, figure out what is wrong. ``The sorting step is taking O(n²) time; that's pathetic.''

• Select algorithms based on data sizes and Big O. ``This set could be large, so we need O(log(n)) lookup ...''