Sunday 2:30 p.m.–3 p.m. in Grand Ballroom C

Big-O: How Code Slows as Data Grows

Ned Batchelder


Big-O is a computer science technique for analyzing how code performs as data gets larger. It's a very handy tool for the working programmer, but it's often shrouded in off-putting mathematics. In this talk, I'll teach you what you need to know about Big-O, and how to use it to keep your programs running well. Big-O helps you choose the data structures and algorithms that will let your code work efficiently even on large data sets. You can understand Big-O even if you aren't a theoretical computer science math nerd. Big-O isn't as mystical as it appears. It's wrapped in mathematical trappings, but doesn't have to be more than a common-sense assessment of how your code will behave.