# Complexity Intuition

**Track:** Objects, Data Structures & Algorithms — Creative Coding — the existing 50
**Framework / surface:** p5.js
**Level:** Intermediate
**Prerequisites:** Selection Sort Visualized, Merge Sort & Divide-and-Conquer

**In one line:** How work grows with input — fast at scale vs grinding to a halt.

## Theory, aesthetics & inspiration

Complexity analysis asks not how long an algorithm takes but how its work grows as input grows—a question answered with asymptotic notation. The big-O symbolism originates with Paul Bachmann and Edmund Landau and was brought into computing by Donald Knuth, whose 1976 note "Big Omicron and big Omega and big Theta" fixed the modern usage. The intuition is comparative: constant, logarithmic, linear, quadratic, and exponential growth diverge so sharply that the curve, not the constant, decides what is feasible. For the coding artist this is a felt limit—the difference between a sketch that animates smoothly and one that stalls—and plotting the curves makes that boundary visible.