The lack of generic programming in Go is a huge deal. It's vital for modelling complex systems without a mess of runtime checks, and generally leads to clean and reusable designs.
With D, you can get very close to the generic ideal, "This
is the last implementation of linear search I'll ever need
to write." Or binary search. Or stable matching. Or
Levenshtein distance. I searched around, and it looks
like D is the only language offering Levenshtein distance
on UTF strings without copying the input and without
special-casing per encoding. D just has the abstraction
power to deal with variable-width entities efficiently
and within a unified definition (that works with many other
inputs, such as linked lists of floating point numbers, if
you want). It's really the last Levenshtein implementation
I need to write. Now, you may not care about that particular
algorithm, but there are benefits of that power for many
structures, algorithms, and design artifacts that might be
important to you.
