Eric Evans talked about Domain-Driven Design at our Portland SPIN meeting Wednesday. Eric’s thesis is that unless you capture the “ubiquitous language”that people use to talk about the functions of the business and create a domain model representing object concepts, you are developing software at wrong level of detail. Instead of talking about Shipping Routes, Legs, and Itinerary, you’ll be talking about “creating rows in the stop table” for each port along a shipping route. Why create Itinerary and Leg objects when you can get by stuffing a database table with “stop”records? Because it makes other parts of the system easier to program. Re-routing cargo gets easier if you can remove all Legs after a particular destination and splice one Itinerary onto another one. Lack of a domain model can severely limit the effectiveness of software (and make it hard to maintain systems and add new functionality).

Creating a domain model is more complicated than just capturing the language people use to talk about system functionality and creating software objects with appropriate names. In complex software, development teams often work on different sub-problems. Each subsystem may need its own model. Meanwhile, subsystems and teams still need to define appropriate ways to communicate with each other. In addition to ubiquitous languages, you need to define the appropriate common languages for inter-system/inter-team communication. Nothing is ever easy!

Eric’s masterful talk motivated me to ponder about why developers often end up with muddy models instead of ones that more clearly incorporate domain concepts. Eric says that domain modeling isn’t looking for a perfect model, only ones that are “good enough” to support the hardest problem well. Why don’t more development teams end up with “good enough” models? I suspect there are many reasons. What constitutes “good enough” can be so subjective that people don’t want to get bogged down. They give up and take the easiest paths, not the simplest ones. For lack of a good object to relational mapping tool, some developers may compromise on database tables being “good enough” approximations to classes. And their models get compromised. There are many reasons why software falls short of capturing “ubiquitous language” in a domain model. I suspect that a big reason is that it isn’t always obvious that a model is needed. If your code shuffles data back and forth from the UI to a database with few edits, why create a model? Only when there is significant behavior and computation, does a model pay off. Now if we all could agree on what “significant” means. If you have ideas about what constitutes significant enough behavior to warrant a model, I’d like to hear your thoughts.