Tight bound — where it appears
Named by 3 essays across 3 fields — each of them below, with the objects they name alongside it.
What O-notation does not say
Big-O is a statement about a limit. It does not say how fast, it does not say which is better, it does not say anything at all about any particular n, and it discards precisely the factor that usually decides the answer. Knowing exactly what it claims is the difference between using it and being misled by it.
The floor under moving data
The information-theoretic floor for comparison sorting is log₂(n!) and it says nothing about a file on a disk. In the external model the floor is (n/B)·log_{M/B}(n/B), it is a bound on every algorithm rather than on merge sorts, and a measured external sort sits 2.40 to 2.97 times above it. Both numbers are computable, and the gap between them is what a real implementation costs.
The counter that takes the smallest slot
Space-Saving keeps two numbers per key and they bracket the truth from both sides. On the twenty heaviest keys of a stream its mean error is a tenth of one arrival, against a hundred and ten for Misra-Gries at the same bits — and on the keys ranked past a hundred the ordering reverses.
Named alongside it
The objects these essays reach for when they reach for this one.
Asymptotic notationBlock transferComparison countConstant factorCount-MINCounting argumentDistributionExternal-memory modelExternal merge sortGuaranteeHeavy hitterInformation-theoretic bound