Yes, this is another reason to prefer julia's dispatch over manual dispatch. In this case the cost of the dynamic type being returned is just a _single_ dynamic

Yes, this is another reason to prefer julia's dispatch over manual dispatch. In this case the cost of the dynamic type being returned is just a _single_ dynamic dispatch. Dynamic dispach means that the correct function foo will be looked up in julia's method table. But when this foo is called, all types are inferred, and it will run optimized for these types. This is called a function barrier. A function barrier can be used as an optimization too: if you have a large function where one of the local variables has a type that is abstract / not concrete / not properly inferred by the compiler (e.g. `::Union{A,B,C}`, `::AbstractVector`, `::Any`), it can be beneficial to split the function into two functions, such that the latter function can be optimized for concrete types, and the former function only has the overhead of a single dynamic dispatch.