Software Development

Design Patterns after Design is Done

Design Patterns are a useful tool when you are designing a system, an effective shorthand for communicating and sharing design ideas and a way to build consistency into the code – if people understand them and follow patterns properly.

I’m not interested in arguments over whether design patterns are good or not, or which patterns are good and which ones aren’t – although these are all important questions.
What I want to understand is how useful design patterns are over time. Do they still matter after the initial design is done?

Looking for Patterns in Code

The first thing to ask is whether developers working on the code can recognize the design patterns that were used, and how useful is it for them when they do.

In Design Patterns for Maintenance, Joshua Engel makes a case that when someone maintaining code recognizes a pattern, they instantly get more context, which means they can move faster and with more confidence:


“When the maintainer recognizes a pattern in a piece of code being maintained, the maintainer grasps a bit more about the code. The maintainer taps into a wealth of background material: personal experience as well as what’s read in textbooks like Design Patterns. That background can clue you in to potential pitfalls, limitations, and the intended way for the code to evolve. Or, if the code fails to completely match the patterns, you have a guide to what needs to be added to gain the benefits of that pattern.”

This is backed up by research. In Making Software, chapter 22 “The Evidence for Design Patterns” reviewes two studies by Prof. Walter Tichy showing that design patterns can be useful to developers maintaining code, provided that the people maintaining the code recognize and understand the patterns. One study of computer science students who had some training in design patterns found that students made fewer mistakes and were faster at changing code if it followed well-known and easily-understood design patterns, and if the design patterns being used in the code were clearly documented in the comments. In another study, experienced programmers were also able to make changes quicker and with fewer bugs if the code followed design patterns that they were familiar with.

But another study on design patterns in legacy code explains how difficult it is to “mine for design patterns” in code:

  • recognizing design patterns in code requires a good understanding of the code as well as common patterns;
  • some patterns are easier to recognize than others – and some patterns probably won’t be recognized at all.

Understanding and Recognizing Patterns in Code

Patterns are only valuable if they are immediately recognizable by whoever is working on the code and can be easily followed. Which means that they have to be implemented properly in the first place, and sustained over time.

Besides the canonical GoF design pattern catalog, which most developers have at least heard of, and maybe Martin Fowler’s Patterns of Enterprise Application Architecture, there are lots of other less well-known pattern collections, never mind proprietary patterns that were invented by the team that wrote the software.

You can’t expect a developer to recognize these patterns, never mind understand them, from looking at code, unless they are otherwise made explicit in the code through naming conventions and comments (including, for more obscure patterns, live links to the pattern definition). The studies above prove thjat this kind of documentation is especially important for less experienced developers.

But just because something has “Factory” or “Strategy” in the name, or comments explaining that the code is following a pattern, doesn’t mean that it actually follows that pattern properly, at least not any more.

Refactoring to Patterns

Another place where patterns come into play is in refactoring. When cleaning up the structure of code, it’s natural (for some developers at least) to think about where patterns can be applied.

Refactoring to Patterns takes refactoring to a higher level, not just correcting obvious problems and inconsistencies in the code. It describes how to bring the design inline with common patterns (not all of them from the GoF book) using multiple refactoring steps.

Some patterns are simple to understand, simple to apply, don’t require a lot of changes to implement, and result in simpler code: Factories and Prototypes. Refactoring to other patterns requires a lot more work to understand and change the code, and may not be worth the effort: Strategies and State, Observer, Visitor.

What’s the real payback for refactoring or rewriting code to patterns for the sake of patterns? There often isn’t one.

You don’t want to refactor to patterns unless:

  1. you have a good reason to refactor the code in the first place – the code is difficult to understand and change; and
  2. you know how to do refactoring properly and safely;
  3. you need the extra flexibility that most patterns offer; and
  4. you have the experience and judgement to know what patterns are needed and how to use them properly; and
  5. the people who you work with also understand patterns well enough to keep up with the changes that you want to make.

As it says in the GoF book:


Design patterns should not be applied indiscriminately. Often they achieve flexibility and variability by introducing additional levels of indirection, and that can complicate a design and/or cost you some performance. A design pattern should only be applied when the flexibility it affords is actually needed.

The Value of Patterns over Time

Refactoring to Patterns encourages more ambitious, larger-scale refactoring – which can be dangerous, because the more you refactor, the more chances there are of making mistakes and introducing bugs – and implementing patterns doesn’t always make code more maintainable and easier to understand, which defeats the purpose of refactoring.

A study on design patterns and software quality at the University of Montreal (2008) found that design patterns in practice do not always improve code quality, reusability and expandability; and often makes code harder to understand. Some patterns are better than others: Composite makes code easier to follow and easier to change. Abstract Factory makes code more modular and reusable, but at the expense of understandability. Flyweight makes code less expandable and reusable, and much harder to follow. Most developers don’t recognize or understand the Visitor pattern. Observer can be difficult to understand as well, although it does make the code more flexible and extendible. Chain of Responsibility makes code harder to follow, and harder to change or fix safely. And Singleton, of course, while simple to recognize and understand, can make code much harder to change.

For maintainability and understandability, it’s more important to recognize and sustain coding conventions so that the code base is consistent than it is to implement patterns. And to understand common refactorings and how to use your IDE’s refactoring tools, as well as Michael Feathers’ patterns for cleaning up legacy code.

Whether you’re designing and writing new code, or changing code, or refactoring code, the best advice is:

  • Don’t use patterns unless you need to.
  • Don’t use patterns that you don’t fully understand.
  • Don’t expect that whoever is going to work on the code in the future to recognize and understand the patterns that you used – stick to common patterns, and make them explicit in comments where you think it is important or necessary.
  • When you’re changing code, take some time to look for and understand the patterns that might be in place, and decide whether it is worth preserving (or restoring) them: whether doing this will really make the code better and more understandable.

 

Jim Bird

Jim is an experienced CTO, software development manager and project manager, who has worked on high-performance, high-reliability mission-critical systems for many years, as well as building software development tools. His current interests include scaling Lean and Agile software development methodologies, software security and software assurance.
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