Make your invalid states unrepresentable
There's a folk story - I don't remember where I read it - about a genealogy database that made it impossible to e.g. have someone be both the father and the grandfather of the same person. Which worked well until they had to put in details about a person who had fathered a child with his own daughter - and was thus both the father and the grandfather of that child. (Sad as it might be, it is something that can, in fact, happen in reality, and unfortunately does).
While that was probably just database constraints of some sort which could easily be relaxed, and not strictly "unrepresentable" like in the example in the article - it is easy to paint yourself into a corner by making a possible state of the world, which your mental model dims impossible, unrepresentable.
The critical thing with state and constraints is knowing at what level the constraint should be. This is what trips up most people, especially when designing relational database schemas.
I think the solution to that is to continuously refactor, and to spell out very clearly what your assumptions are when you are writing the code (which is an excellent use for comments).
The trick is to make the schema represent what you need - right now - and no more. Which is the point of the “Make your invalid states unrepresentable” comment.
The real world and user experience requirements have a way of intruding on these underspecified models of how the world "should" be.
Ultimately you need to make your own pragmatic decisions about where you think that state should be and how it should be managed. But the ad-hoc approach is more open to inconsistencies and therefore bugs.
Hi, can you give an example? Not sure I understand what you're getting at there.
(My tuppence: "the map is not the territory", "untruths programmers believe about...", "Those drawn with a very fine camel's hair brush", etc etc.
All models are wrong, and that's inevitable/fine, as long as the model can be altered without pain. Focus on ease of improving the model (eg can we do rollbacks?) is more valuable than getting the model "right").
An utterly trivial example is constraining the day-field in a date structure. If your constraint is at the level of the field then it can’t make a decision as to whether 31 is a good day-value or not, but if the constraint is at the record-structure level then it can use the month-value in its predicate and that allows us to constrain the data correctly.
When it comes to schema design it always helps to think about how to ‘step up’ to see if there’s a way of representing a constraint that seems impossible at ‘smaller’ schema units.