Interactive

Big-O in Practice — Double the input and count what happens to the work

Big-O in Practice: Count the Steps as the Input Grows

Computer scientists describe how fast an algorithm is with Big-O notation: O(log n), O(n), O(n log n), O(n²). Behind the letters is a simple question: when the input gets twice as big, what happens to the work? Here four real algorithms run on lists of up to 4,096...

Logic Gates — AND, OR, NOT and XOR — build the truth table yourself

Boolean Logic Gates: Interactive Truth Table Builder

Logic gates are the fundamental building blocks of every computer ever made. Every decision your device takes — from checking a password to rendering a pixel — ultimately comes down to billions of these tiny circuits asking simple true-or-false questions. In this...

Caesar Cipher — Encode and decode secret messages with a shift cipher

Caesar Cipher: Encode and Decode Secret Messages

The Caesar cipher is one of the oldest encryption tricks in the book — legend has it Julius Caesar used it to send secret military messages over 2,000 years ago. The idea is beautifully simple: shift every letter in your message a fixed number of steps along the...

Binary Search — Halve the list at every step to find a number fast

Binary Search: Find Numbers Fast in a Sorted List

Have you ever wondered how a computer can find one record among millions in a fraction of a second? The secret is binary search — an elegant algorithm that works on any sorted list by repeatedly cutting the remaining possibilities in half. Instead of checking every...

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