Friday, March 07, 2008 

Problem frames and the DNC

If you've read any of my posts before, you probably know I'm not a fan of pre-packaged, one-size-fits-all ideas. Methods, technology, languages, models, even specific values (design values; business values; etc.) must always be considered in context.

With this background, it's hardly surprising that I've always found the notion of a Domain Neutral Component quite uncomfortable. It really sounded like an attempt to shoehorn the world into a predefined model, while we should carefully look for the relevant portion of the world we want to represent into our model.

Still, in many cases (especially for a junior analyst) starting with the DNC might be better than starting with a blank page. How could this be? Does it work all the time? If not, when? Honestly, in the past years I haven't spent too much time trying to answer those questions. The DNC was part of my bag of tricks, but I didn't use it often.

Recently, however, I was thinking (once more :-) about colors and UML, and while looking into some of Peter Coad's works for a specific reference, I stumbled on the DNC again. So I thought, maybe I've learnt something in the past few years that could shed some light on the inner quality of the DNC, and its suitability in any (?) given context.

The DNC can be considered as an overengineered "standard" model representing something (an event / moment / interval) happening somewhere (a place) involving one party or more (originally an actor), usually exchanging or dealing with some good (a thing). The party plays a role, hence the later shift from actor to party + role. Indeed, you can start with a very simple model, and "derive" the DNC by following a very reasonable line of reasoning: see From Associations To Domain Neutral Component for the full story.

Of course, in many cases, the DNC might be overengineered. But you can always simplify the unnecessary parts. The real question, however, is when the DNC can give you a head start, and when it won't (context, context, context :-).

That's where Problem Frames Patterns can shed some light. I recommend that you keep the PFP paper at hand while reading what follows.

Consider, for instance, the Commanded Behavior problem frame. Shortly, the problem is stated as:
There is some part of the world whose behavior is to be controlled in accordance with commands issued by
an operator. The problem is to build a machine that will accept the operator's commands and impose the
control accordingly.

and the frame concerns are:
1. When the Operator issues a Command
2. AND the Machine rejects invalid Commands
3. AND the Machine either ignores it if unviable, OR issues Control Events
4. AND the Control Events change the Controlled Domain
5. ENSURE the changed state meets the Commanded Behavior in every case.

That's not at odds with the DNC. Control Events map nicely to moment-interval; moreover, the text above suggests that multiple events might be issued for a single command (MomentInterval-MomentIntervalDetails). The Control Events change the Controlled Domain. Therefore, they must describe external entities (each probably having a Role) that must somehow influence internal entities (Party, having a Role, or Places, having a Role).
Using the Email Client example, "Email Retrieval" is an event, composed of individual retrieval events (one for each email message). Each Message is a Thing, although with a dubious Role. Retrieval needs (at least) an Account, which is a Party playing a specific Role (Receiver). Retrieval takes place on a specific Server, playing a Role (POP3 or IMAP server). Not so bad.

What if we look into another problem frame? Let's try Transformation:
There are some given inputs which must be transformed to give certain required outputs. The output data
must be in a particular format, and it must be derived from the input data according to certain rules. The
problem is to build a machine that will produce the required outputs from the inputs.

Concerns:
1. BY traversing the input in sequence, and simultaneously traversing the outputs in sequence
2. AND finding values in the input domain, and creating values in the output domain
3. AND that the input values produce the correct output values
4. ENSURES the I/O relation is satisfied.

Hmmm. Doesn't map so nicely, but the text is really too abstract. Let's try the actual problem: an HTML email to be converted in plain text to be shown on a limited device (I added some context to the equally abstract problem described in the original paper). Well, there is hardly a dominant MomentInterval here. Hardly a party, place, thing triad gravitating around the central MI. Hardly any value in adopting the DNC as a starting point. What can be helpful here? Concepts from grammars, taxonomies, language theory. We're basically modeling a translator, and language theory will give you the head start.

So here it is. The DNC is an interesting concept because it maps nicely to some recurring problem frames (if you got time to spare, you may want to investigate which frames are a good fit for the DNC). Some problem frames, however, just don't match with the DNC. It's not just about individual problems: it's about a whole class of problems, all those within the mismatched problem frames.

For me, this is actually good news. Once we know which problem frames map nicely to the DNC, I would say the DNC itself becomes a more powerful tool, one that can be applied wisely and not blindly.

Winding down: since it all began with colors, it's interesting to see how people used the DNC to reason about more general issues. For instance, in Whole Part Relationships in Color Models, David J. Anderson starts with the DNC and ends up recommending that we avoid some whole-part colors, like a green whole with a yellow part. There is probably more to investigate along those lines. Next time I get back to my idea of coloring associations and dependencies, I'll give it a deeper thought.

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Comments:
Coming from just now learning about DNC and color, this is an interesting and educational post for me - thanks!
 
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