Comment by kuboble
1 day ago
To complement on other comments that have already provided definitions.
The big O notation is very often used to denote exact complexity of an algorithm even if the notation is technically an upper bound.
The little o notation is usually used to denote a small asymptotic improvement over some known complexity.
For example if some sublinear algorithm would have n^(7/8) complexity - would be probably advertised as big O of that. But n^(1-eps) is shared as o(n) with exact constant provided as a detail.
Pedantic correction: big O is more like <=, little o like strict <. Big theta, Θ, is like =. There's also omegas, big and small, for >= and >.
I don’t think this is pedantic in this case! It’s the relevant precision necessary to understand the way in which the title is notated.