Causes of Decay: Mutating Design

AKA “Partial Refactor”

AKA “Good Ideas”

I have discussed in the past a phenomenon I call “Architecture by Accident”, in which the clarity of the design of a system may be ruined by rampant inconsistencies caused by a lack of attention for standards and reuse as the system evolves. But you don’t have to rely on chance to get there – we can achieve the same results absolutely intentionally.

Let’s say you have a system with a catalog of products, and that each of these products has a listing of parts. It’s probably a common pattern in the system to do something with the product itself, then go through the parts one by one and do a related activity. For example, the web page for the product probably lists the product’s name, code, and a description, and then shows each of the parts one by one in a similar fashion. The printed-out invoice may do the same. And let’s say the order fulfillment workflow does all sorts of funky calculations based on summing up the individual parts for things like calculating shipping weight, checking inventories, provisioning, whatever.

So the system designer goes ahead and says, “Hey everybody! Let’s create an iterator for products and their parts. From now on, whenever you need to do something to products, use a loop with the iterator.” Great. So, the team goes ahead and implements the web page and the invoice sheet using the really fancy iterator, with just a slight change to the contents of the “while” statement. So far, so good.

After a while, this “slight change to the contents” starts giving off a distinct copy-paste smell to the designer. So, one bright day, while browsing through their dog-eared copy of the GoF, they come across the Visitor pattern. “Aha! THIS is what we need!” exclaims our designer. The team has just been asked to implement that product-is-the-sum-of-its-parts weight algorithm I mentioned, and the designer decides it’s a good time to try out the pattern. What do you know?! It’s a fantastic improvement to the way they do things. “From now on, team, we use the Visitor pattern!” And it was so.

Time passes, and after a lot of summing up product parts in all sorts of incredibly meaningful ways, the designer starts to realize that their code base is lousy with one-hit-wonder Visitor classes that are created for some special purpose and are never used again. Fortunately, they are reading a book on the wonders of closures in Groovy. “Aha! THIS is what we need! We can just pass the code to be executed, without having to create a whole new class every time!” The team is all for it (all except one member, who’s forced to quit due to some unfortunate flashbacks to the 60’s inspired by the new language – especially tragic to happen to a young man of only 25), and goes about messing around with their products in Groovy.

Eventually, the team is able to hire a Groovy-compatible replacement for their fallen comrade. On the newbie’s first day on the job, she turns to one of her new coworkers and says, “Hey! I thought you said there was a full-time architect on this system.” Confused, he responds, “There is! Why?” “Well, then, why is this system such a mess? You said I’m supposed to be coding this product stuff in Groovy, but there’s a ton of these Visitor classes, brute-force loops, and all this other copy-pasted code. What up?”

From an outsider’s perspective, there’s little difference between “Architecture by Accident” (a lack of standards) and “Mutating Design” (too many standards). The result is pretty much the same: a patchwork quilt of approaches to solving the same problem in myriad ways. An architect or designer (or team) should strive for clarity in their designs. A system should speak for itself, but not if it’s going to say something different every time it opens its mouth.

So how does one avoid creating a system with a Mutating Design? There are only a few things you can do:

  1. Never change your design. Once you make a decision, write it in stone. This way, it will be easy for everyone to know how things are meant to be done. If anyone strays from the beaten path, it should be easy to identify and put things back on track. Unfortunately, this puts quite a burden on you to get things right from the beginning. This is basically synonymous with “waterfall methodology”, and has about the same chances of succeeding. However, it is worth noting that there may be times where the gain to be had by improving a design is outweighed by the damage the change would do to the clarity of the system.
  2. Refactor everything. The devil in a Mutating Design lies in inconsistency. You can exorcise it by going through a rigorous ritual of refactoring everything that had previously been implemented so that the whole system reflects the new design. This could mean a whole lot of work (and risk of introducing new bugs into previously working code) in the name of clarity.
  3. Isolate the changes. Again, the problem is with clarity, which can be occluded by inconsistency. So is there a way to provide clarity even when the design is incosistent? There is… if you’re clear about scope, and you provide a roadmap.

This last point is not obvious, but worth trying to understand and put into practice. The question you should ask yourself is: if the design keeps changing, how can developers know which pattern to use, and where? Ideally, the system should “speak for itself”, which means developers should be able to infer the design from existing implementations. Therefore, if you wish to change the design, do it in a way that can be consistent within the scope in which developers tend to work. If development teams are divided up by ownership of subsystems, for example, you can experiment with a new design in one of the subsystems – but then change the design for that whole subsystem. It may be inconsistent across the whole system, but in general, developers won’t feel the pain. Even if developers work on the whole system, it may be possible to choose a scope that makes sense to them. If the system is divided by modules, you can choose to change the design for one (entire) module. But then you must make it clear to developers that they should use whichever pattern is appropriate for the particular module they are working on.

This last approach can go really wrong if you don’t provide clear signals to developers as to where they are in the design. Because of this, I am working on a series of techniques (and blog posts) that I call “Visible Architecture”. The idea here is that the development team should be able to see the architecture relative to their code at any time. So, for example, if they are working on a module in which the Visitor pattern must be implemented to work with products, a document on this technique should “present itself” to the developers from within their IDE. If they then switch to a module using the new Groovy approach, the document will switch as well.

There aren’t very many tools that provide this type of functionality. I’m working with one called Structure101 which lets you do just that for layer diagrams. You can define dependency rules for a project, and they will actually show up as diagrams (with enforcement via compilation errors) in either an Eclipse or an IntelliJ IDE. You can publish a different set of diagrams for each Eclipse or IntelliJ project, which means if you wish to change these rules, it’s easy to do it for one project, and leave the old rules in effect everywhere else. I have also written a plug-in of my own for these two browsers called “Doclinks” which doesn’t enforce any rule, but allows you to link URLs to source code based on a wide variety of rules. This, together with a wiki-based architectural documentation, is another way to provide a context-specific roadmap to developers, reducing the confusion that can be caused by a Mutating Design.

I’ve previously shown you how a system can lose its clarity due to a lack of architecture. Now I’ve presented how the same thing can happen when it has too much architecture. As an architect or designer, you need to recognize the importance of standardization, but you also shouldn’t freeze your design in time. What’s important is to recognize that the evolution of the system is best done in stages, rather than through kaleidoscoping changes with no regard to what came before. Before you know it, your code may look like it’s from a B-Movie: The Attack of the Mutating Design!


One Response to Causes of Decay: Mutating Design

  1. […] Well, I am proud to say that I contributed 4 of those 97 things, or “axioms” as they’re called, and now am happy to announce that the book was finally released! You can buy a copy yourself via O’Reilly,, or elsewhere. Or, if you prefer burning fossil fuels over killing trees, you can read the axioms for free (minus electric and internet fees) on the official web site. You’ll also find other nuggets of wisdom in the section entitled “Other Things Software Architects Should Know”, and can even contribute your own expertise via the “Community Axioms” page (I have two more out there, including one that I think I expressed better in a recent blog post). […]

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