Does Big O Measure Memory Requirments Or Just Speed?
I often here people talk about Big O which measures algorithms against each other
Does this measure clock cycles or space requirements.
If people want to contrast algorithms based on memory usage what measure would they use
If someone says "This algorithm runs in O(n) time", he's talking about speed. If someone says "This algorithm runs in O(n) space", he's talking about memory.
If he just says "This algorithm is O(n)", he's usually talking about speed (though if he says it during a discussion about memory, he's probably talking about memory).
If you're not sure which one someone's talking about, ask him.
Short answer : you have 'Big O in space" and "Big O in time".
Long answer: Big O is just a notation, you can use it in whatever context you want.
Big O is just a mathematical tool that can be used to describe any function. Usually people use it to describe speed, but it can just as well be used to describe memory usage.
Also, when we use Big O for time, we're usually not talking directly about clock cycles. Instead, we count "basic operations" (that are implicitly assumed to take a constant number of cycles).
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