Algorithm complexity — Big-O notation

What you'll learn

1. 1

   Big-O notation is like a speed rating for algorithms — it tells you how fast or slow a program runs as you give it more data.

2. 2

   If an algorithm checks every item in a list once, what Big-O is it?

3. 3

   Drag the slider to see how many steps O(n) and O(n²) take as n grows from 1 to 10.

4. 4

   Let's compare two algorithms for finding a book on a shelf of 1000 books.

5. 5

   Which Big-O would you use for an algorithm that always takes the same time, no matter how big the list?

6. 6

   An algorithm that compares every pair of items in a list of 10 items does 100 comparisons. What's its Big-O?

7. 7

   Use the slider to see how many steps each Big-O takes for n = 1 to 20. Notice how O(n²) shoots up!