Monday, September 14, 2009

DDD: How to tackle complexity

In DDD (Domain Driven Design) you create an object model that represents your application's domain. This model contains all the relationships and logic of that domain. The purpose of this is to make the complexity of the domain manageable. DDD involves lots of patterns and concepts, but when distilled there are a couple big picture things that really serve to tackle the complexity:
  1. Explicit representation of domain concepts
  2. Continuous Refactoring to "Deeper Insight"
The thing about complexity is its complex. Complex things are hard to understand. If they are hard to understand, they are difficult to get right the first time. And as hard as they are the first time, they're exponentially harder the second, and the third, and you get the idea.

This is the real issue: complex software is hard to understand. That's what leads to a system which everyone is so afraid to update, they would rather start from scratch. Maybe at first you're willing to just go in and add a hack or two. But each hack raises the complexity and increases the ugliness of the code until finally its just not worth trying anymore. That's another way of saying FAIL.

So we must come up with a way to deal with this complexity. The first way DDD does this is by taking advantage of the power of Object Orientation, models, and abstraction. But that's a bit too broad. We need to figure out how to structure those objects and models. That's where DDD applies the idea of explicitly representing domain concepts.

The idea is simple. If there is an import concept in your domain, you should be able to see it in the Model. You shouldn't have to dive into the code to extract important concepts, they should be represented by an object in the Model. Say there is some action in your domain that can only be taken when certain conditions are met. If these conditions are minor, you can just add if statement guards to the method that performs the action. But if these conditions are an important part of the domain, hiding them away in the code isn't good enough. Instead of an introduce a Policy Object that represents the conditions that must be met for that action to be performed. Now the conditions are explicitly represented in your domain.

You'll see this same idea expressed in Factories, Repositories, Services, Knowledge Levels, etc. Its a huge part of what it takes to make your system understandable.

The second idea that makes DDD work is Continuously Refactoring to "Deeper Insight." The deeper insight bit means if you discover something new about your domain after you already have a model, you don't just bolt it on. You figure out if that new thing indicates something fundamentally important about your domain. If it does, you refactor the model to explicitly represent that new understanding. Sometimes these refactorings will be small. Other times they will be big and cost a lot. It doesn't matter, you do them anyway.

If you don't your model will lose its expressive character and become more and more brittle. More and more complex. Harder and harder to understand. So you have to fight to always keep your model as simple and expressive and accurate as you possibly can. If you're lucky, these refactorings can lead to what Eric Evans calls a Breakthrough, where new possibilities or insights suddenly appear that would have been impossible before. That may take some real luck. If you're not that lucky, these refactorings will at least lead to a model that is flexible in the places where the domain requires flexibility. That means it will be easier to handle future insights and refactorings.

The really really cool thing about this is these two concepts form a cycle and feed each other.
The more you Refactor the more Explicit your model becomes. The more Explicit your model, the easier it is to Refactor!

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