- Big O notation is the language we use for articulating how long an algorithm takes to run. It's how we compare the efficiency of different approaches to a problem.
- With big O notation we express the runtime in terms of—brace yourself—how quickly it grows relative to the input, as the input gets arbitrarily large.
O(1) : Static
O(log n) : Divide and conquer. Ex: ( Binary search )
O(n ) : Directly and linearly related to n
O(n log n ) : Merge search : deck of cards
O(n2) : Checking list + grocery cart
O(infinity ): Tossing a coin
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