Various description of Big O – Time complexity algorithms
Understanding the time complexity of Big O and log.
O(log N) means time goes up linearly while the n goes up exponentially. So if it takes 1 second to compute 10 elements, it will take 2 seconds to compute 100 elements, 3 seconds to compute 1000 elements, and so on. https://stackoverflow.com/a/2307330/2489973
What’s logb(n)?
It is the number of times you can repeatedly cut a log of length n into b equal parts before reaching a section of size 1.
https://stackoverflow.com/a/2480061/2489973
The Stackoverflow link covers complexity very nicely. I am putting it here for easy reference.
Big O complexities cheatsheet
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