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This chapter is from the book

## Managing Dependency Direction

Dependencies always have a direction; earlier in this chapter it was suggested that one way to manage them is to reverse that direction. This section delves more deeply into how to decide on the direction of dependencies.

### Reversing Dependencies

Every example used thus far shows Gear depending on Wheel or diameter, but the code could easily have been written with the direction of the dependencies reversed. Wheel could instead depend on Gear or ratio. The following example illustrates one possible form of the reversal. Here Wheel has been changed to depend on Gear and gear_inches. Gear is still responsible for the actual calculation but it expects a diameter argument to be passed in by the caller (line 8).

````1` `class` `Gear`
`2`   attr_reader `:chainring`, `:cog`
`3`   `def` `initialize`(chainring, cog)
`4`     `@chainring` = chainring
`5`     `@cog`       = cog
`6`   `end`
`7`
`8`   `def` `gear_inches`(diameter)
`9`     ratio * diameter
`10`   `end`
`11`
`12`   `def``ratio`
`13`     chainring / cog.to_f
`14`   `end`
`15` `#  ...`
`16` `end`
`17`
`18` `class` `Wheel`
`19`   attr_reader `:rim`, `:tire`, `:gear`
`20`   `def` `initialize`(rim, tire, chainring, cog)
`21`     `@rim`       = rim
`22`     `@tire`      = tire
`23`     `@gear`      = `Gear`.new(chainring, cog)
`24`   `end`
`25`
`26`   `def` `diameter`
`27`     rim + (tire * `2`)
`28`   `end`
`29`
`30`   `def` `gear_inches`
`31`     gear.gear_inches(diameter)
`32`   `end`
`33` `#  ...`
`34` `end`
`35`
`36` `Wheel`.new(`26`, 1.5, `52`, `11`).gear_inches```

This reversal of dependencies does no apparent harm. Calculating gear_inches still requires collaboration between Gear and Wheel and the result of the calculation is unaffected by the reversal. One could infer that the direction of the dependency does not matter, that it makes no difference whether Gear depends on Wheel or vice versa.

Indeed, in an application that never changed, your choice would not matter. However, your application will change and it’s in that dynamic future where this present decision has repercussions. The choices you make about the direction of dependencies have far reaching consequences that manifest themselves for the life of your application. If you get this right, your application will be pleasant to work on and easy to maintain. If you get it wrong then the dependencies will gradually take over and the application will become harder and harder to change.

### Choosing Dependency Direction

Pretend for a moment that your classes are people. If you were to give them advice about how to behave you would tell them to depend on things that change less often than you do.

This short statement belies the sophistication of the idea, which is based on three simple truths about code:

• Some classes are more likely than others to have changes in requirements.
• Concrete classes are more likely to change than abstract classes.
• Changing a class that has many dependents will result in widespread consequences.

There are ways in which these truths intersect but each is a separate and distinct notion.

#### Understanding Likelihood of Change

The idea that some classes are more likely to change than others applies not only to the code that you write for your own application but also to the code that you use but did not write. The Ruby base classes and the other framework code that you rely on both have their own inherent likelihood of change.

You are fortunate in that Ruby base classes change a great deal less often than your own code. This makes it perfectly reasonable to depend on the * method, as gear_inches quietly does, or to expect that Ruby classes String and Array will continue to work as they always have. Ruby base classes always change less often than your own classes and you can continue to depend on them without another thought.

Framework classes are another story; only you can assess how mature your frameworks are. In general, any framework you use will be more stable than the code you write, but it’s certainly possible to choose a framework that is undergoing such rapid development that its code changes more often than yours.

Regardless of its origin, every class used in your application can be ranked along a scale of how likely it is to undergo a change relative to all other classes. This ranking is one key piece of information to consider when choosing the direction of dependencies.

#### Recognizing Concretions and Abstractions

The second idea concerns itself with the concreteness and abstractness of code. The term abstract is used here just as Merriam-Webster defines it, as “disassociated from any specific instance,” and, as so many things in Ruby, represents an idea about code as opposed to a specific technical restriction.

This concept was illustrated earlier in the chapter during the section on injecting dependencies. There, when Gear depended on Wheel and on Wheel.new and on Wheel.new(rim, tire), it depended on extremely concrete code. After the code was altered to inject a Wheel into Gear, Gear suddenly begin to depend on something far more abstract, that is, the fact that it had access to an object that could respond to the diameter message.

Your familiarity with Ruby may lead you to take this transition for granted, but consider for a moment what would have been required to accomplish this same trick in a statically typed language. Because statically typed languages have compilers that act like unit tests for types, you would not be able to inject just any random object into Gear. Instead you would have to declare an interface, define diameter as part of that interface, include the interface in the Wheel class, and tell Gear that the class you are injecting is a kind of that interface.

Rubists are justifiably grateful to avoid these gyrations, but languages that force you to be explicit about this transition do offer a benefit. They make it painfully, inescapably, and explicitly clear that you are defining an abstract interface. It is impossible to create an abstraction unknowingly or by accident; in statically typed languages defining an interface is always intentional.

In Ruby, when you inject Wheel into Gear such that Gear then depends on a Duck who responds to diameter, you are, however casually, defining an interface. This interface is an abstraction of the idea that a certain category of things will have a diameter. The abstraction was harvested from a concrete class; the idea is now “disassociated from any specific instance.”

The wonderful thing about abstractions is that they represent common, stable qualities. They are less likely to change than are the concrete classes from which they were extracted. Depending on an abstraction is always safer than depending on a concretion because by its very nature, the abstraction is more stable. Ruby does not make you explicitly declare the abstraction in order to define the interface, but for design purposes you can behave as if your virtual interface is as real as a class. Indeed, in the rest of this discussion, the term “class” stands for both class and this kind of interface. These interfaces can have dependents and so must be taken into account during design.

The final idea, the notion that having dependent-laden objects has many consequences, also bears deeper examination. The consequences of changing a dependent-laden class are quite obvious—not so apparent are the consequences of even having a dependent-laden class. A class that, if changed, will cause changes to ripple through the application, will be under enormous pressure to never change. Ever. Under any circumstances whatsoever. Your application may be permanently handicapped by your reluctance to pay the price required to make a change to this class.

#### Finding the Dependencies That Matter

Imagine each of these truths as a continuum along which all application code falls. Classes vary in their likelihood of change, their level of abstraction, and their number of dependents. Each quality matters, but the interesting design decisions occur at the place where likelihood of change intersects with number of dependents. Some of the possible combinations are healthy for your application; others are deadly.

Figure 3.2 summarizes the possibilities.

The likelihood of requirements change is represented on the horizontal axis. The number of dependents is on the vertical. The grid is divided into four zones, labeled A through D. If you evaluate all of the classes in a well-designed application and place them on this grid, they will cluster in Zones A, B, and C.

Classes that have little likelihood of change but contain many dependents fall into Zone A. This Zone usually contains abstract classes or interfaces. In a thoughtfully designed application this arrangement is inevitable; dependencies cluster around abstractions because abstractions are less likely to change.

Notice that classes do not become abstract because they are in Zone A; instead they wind up here precisely because they are already abstract. Their abstract nature makes them more stable and allows them to safely acquire many dependents. While residence in Zone A does not guarantee that a class is abstract, it certainly suggests that it ought to be.

Skipping Zone B for a moment, Zone C is the opposite of Zone A. Zone C contains code that is quite likely to change but has few dependents. These classes tend to be more concrete, which makes them more likely to change, but this doesn’t matter because few other classes depend on them.

Zone B classes are of the least concern during design because they are almost neutral in their potential future effects. They rarely change and have few dependents.

Zones A, B, and C are legitimate places for code; Zone D, however, is aptly named the Danger Zone. A class ends up in Zone D when it is guaranteed to change and has many dependents. Changes to Zone D classes are costly; simple requests become coding nightmares as the effects of every change cascade through each dependent. If you have a very specific concrete class that has many dependents and you believe it resides in Zone A, that is, you believe it is unlikely to change, think again. When a concrete class has many dependents your alarm bells should be ringing. That class might actually be an occupant of Zone D.

Zone D classes represent a danger to the future health of the application. These are the classes that make an application painful to change. When a simple change has cascading effects that force many other changes, a Zone D class is at the root of the problem. When a change breaks some far away and seemingly unrelated bit of code, the design flaw originated here.

As depressing as this is, there is actually a way to make things worse. You can guarantee that any application will gradually become unmaintainable by making its Zone D classes more likely to change than their dependents. This maximizes the consequences of every change.

Fortunately, understanding this fundamental issue allows you to take preemptive action to avoid the problem.

Depend on things that change less often than you do is a heuristic that stands in for all the ideas in this section. The zones are a useful way to organize your thoughts but in the fog of development it may not be obvious which classes go where. Very often you are exploring your way to a design and at any given moment the future is unclear. Following this simple rule of thumb at every opportunity will cause your application to evolve a healthy design.