… It’s in words that the magic is–Abracadabra, Open Sesame, and the rest–but the magic words in one story aren’t magical in the next. The real magic is to understand which words work, and when, and for what; the trick is to learn the trick.
… And those words are made from the letters of our alphabet: a couple-dozen squiggles we can draw with the pen. This is the key! And the treasure, too, if we can only get our hands on it! It’s as if–as if the key to the treasure is the treasure!
John Barth, Chimera
It’s a copy of a quotation that appears in The Structure and Interpretation of Programs. It speaks to the fact that if you know the name of something, as in a way to refer to it, then you have control over it. Like functions or closures for instance. If you can refer to it by name, you can tell it to someone else. Or pass it to another function. You can remember the name, so you can speak it when you’re ready. When the context is right. Like when all the variables, objects, and functions have aligned.
The idea of metalinguistic abstraction is a fundamental one. It’s a bottom-up way of thinking about your problem-space, and figuring out primitives and operations on those primitives. Rather than trying to build a system that satisfies a particular set of constraints in the given problem-space, the idea is to build a way to express more complex concepts using those very primitives and operations. That way, changes to the system can be made by changing higher level constructs - and going further down the layered stack of abstractions as needed, depending on how fundamental the changes are. This way, changes (or any new set of constraints) can be handled in a more clean and elegant fashion, and the entire system benefits automatically by a change made at a lower level.
If this sounds like building what these days is called a domain-specific language (DSL), then sure, but it is not a new way of doing things. It is however, possible to do a lot of this stuff easier in “enterprise-type” scenarios, because of a larger acceptance of more dynamic languages. Like Ruby, for example. It isn’t particularly easy to write software this way - it involves a change in the way most of us were taught programming. Everything is not imperative any more, code doesn’t have to be “written” before it runs, lines between data and code begin to blur. On that last point, what is a closure? Is it data or is it a procedure? It’s sometimes one, sometimes the other, and occasionally both, and indeed, sometimes it is neither. Here’s an example -
def create_coord(x, y)
Proc.new { |selector|
if selector == :x
x
elsif selector == :y
y
end
}
end
c = create_coord 10, 20
puts “X is ” + c.call(:x).to_s
puts “Y is ” + c.call(:y).to_s
So, the question here is, what is c? Is it data? Or is it code, that does something? Here, c is an object that represents a cartesian coordinate, but without any explicit data elements like variables or attributes… so, what is it?
Note - This is Ruby code, but a different language, (like Lua, for example, that has syntactic sugar for things like keys on a hash table) could make it unnecessary for the call(:symbol) syntax and instead, just calling x and y would translate it to a call on the object with the given method name.
The point, however, is that there are more ways to think about abstraction than just OO, and to paraphrase Paul Graham, some of them can transcend objects. The bottom-up approach itself can be implemented using plain objects and OO thinking, but there are other ways which can make for some powerful expressablilty. The code above approaches functional programming, and I’m interested in scaling that model to build large systems from pure or near-pure functional constructs. I’m nowhere close to being proficient in writing software this way, but it is my intention to learn.
