A hopefully modern description of Object-Oriented Design

We left off in the last post with an idea of how Object-Oriented Analysis works: if you’re thinking that it used around a thousand words to depict the idea “turn nouns from the problem domain into objects and verbs into methods” then you’re right, and the only reason to go into so much detail is that the idea still seems to confuse people to this day.

Similarly, Object-Oriented Design – refining the overall problem description found during analysis into a network of objects that can simulate the problem and provide solutions – can be glibly summed up in a single sentence. Treat any object uncovered in the analysis as a whole, standalone computer program (this is called encapsulation), and do the object-oriented analysis stuff again at this level of abstraction.

You could treat it as turtles all the way down, but just as Physics becomes quantised once you zoom in far enough, the things you need an object to do become small handfuls of machine instructions and there’s no point going any further. Once again, the simulation has become the deployment: this time because the small standalone computer program you’re pretending is the heart of any object is a small standalone computer program.

I mean, that’s literally it. Just as the behaviour of the overall system could be specified in a script and used to test the implementation, so the behaviour of these units can be specified in a script and used to test the implementation. Indeed some people only do this at the unit level, even though the unit level is identical to the levels above and below it.

Though up and down are not the only directions we can move in, and it sometimes makes more sense to think about in and out. Given our idea of a User who can put things in a Cart, we might ask questions like “how does a User remember what they’ve bought in the past” to move in towards a Ledger or PurchaseHistory, from where we move out (of our problem) into the realm of data storage and retrieval.

Or we can move out directly from the User, asking “how do we show our real User out there in the world the activities of this simulated User” and again leave our simulation behind to enter the realm of the user interface or network API. In each case, we find a need to adapt from our simulation of our problem to someone’s (probably not ours, in 2021) simulation of what any problem in data storage or user interfaces is; this idea sits behind Cockburn’s Ports and Adapters.

Moving in either direction, we are likely to encounter problems that have been solved before. The trick is knowing that they have been solved before, which means being able to identify the commonalities between what we’re trying to achieve and previous solutions, which may be solutions to entirely different problems but which nonetheless have a common shape.

The trick object-oriented designers came up with to address this discovery is the Pattern Language (OK, it was architect Christopher Alexander’s idea: great artists steal and all that), in which shared solutions are given common names and descriptions so that you can explore whether your unique problem can be cast in terms of this shared description. In practise, the idea of a pattern language has fared incredibly well in software development: whenever someone says “we use container orchestration” or “my user interface is a functional reactive program” or “we deploy microservices brokered by a message queue” they are relying on the success of the patterns language idea introduced by object-oriented designers.

Meanwhile, in theory, the concept of patterns language failed, and if you ask a random programmer about design patterns they will list Singleton and maybe a couple of other 1990s-era implementations patterns before telling you that they don’t use patterns.

And that, pretty much, is all they wrote. You can ask your questions about what each object needs to do spatially (“who else does this object need to talk to in order to answer this question?”), temporally (“what will this object do when it has received this message?”), or physically (“what executable running on what computer will this object be stored in?”). But really, we’re done, at least for OOD.

Because the remaining thing to do (which isn’t to say the last thing in a sequence, just the last thing we have yet to talk about) is to build the methods that respond to those messages and pass those tests, and that finally is Object-Oriented Programming. If we start with OOP then we lose out, because we try to build software without an idea of what our software is trying to be. If we finish with OOP then we lose out, because we designed our software without using knowledge of what that software would turn into.

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