Grokking Algorithms: An illustrated guide for programmers and other curious people

by Aditya Y. Bhargava

Big O establishes a worst-case run time

For now, the main takeaways are as follows: Algorithm speed isn’t measured in seconds, but in growth of the number of operations. Instead, we talk about how quickly the run time of an algorithm increases as the size of the input increases. Run time of algorithms is expressed in Big O notation. O(log n) is faster than O(n), but it gets a lot faster as the list of items you’re searching grows.

Recap Binary search is a lot faster than simple search. O(log n) is faster than O(n), but it gets a lot faster once the list of items you’re searching through grows. Algorithm speed isn’t measured in seconds. Algorithm times are measured in terms of growth of an algorithm. Algorithm times are written in Big O notation.