Diving Deep on Coupling

Last time, I described how Cohesion applies to everything from writing a single line of code all the way up to designing a remote service. Now, let’s consider the same thing for Coupling.

Recall that Coupling is the mental load required to understand how a particular component relates to another compoent. If we take a line of code as a single component, then what defines how it is connected to the lines around it? For a start: the local variables it uses, methods it calls, conditional statements it is part of, the method it is contained in, and exceptions it catches or throws. The more of these things a single line of code involves, the more coupled it is to the rest of the system.

As an example, consider a line of code which uses a few local variables to call a method and store the result. This could be more or less coupled depending upon a number of factors. How many local variables are needed? Are any of the variables static or global variables? Is the method call private to the class, a public method on another class, or a static method defined somewhere? Is the result being stored in a local variable, an instance variable, or a static/global variable? Depending upon the answers to these questions, that one line may be more or less coupled to the other lines around it.

The implication of having coupling which is too tight for a single line of code is that you have to understand a lot of other lines in order to understand that one. If it uses global variables, then you have to also understand what other code modifies the state of those variables. If it uses many local variables, then you have to understand the code which sets their values. If it calls a method on another object, then you have to understand what impact that method call will have. All of these things increase the amount of information you need to keep in mind to understand that line of code.

Now, consider what coupling would mean for a remote service which is part of a large distributed system (e.g. Amazon.com). The connections such a service has are defined by the API it offers, the other services it consumes, and how their APIs are defined. For the service’s own API, consider the following: does the API respond to many service calls or just a few? Do the service calls require a lot of structured data to be passed in? How easy is it for a caller to obtain all the necessary information? How much is the service’s internal implementation attached to the API it presents? How common is the communication protocol clients must implement? For the other services it consumes, consider: how many other services does it use? How are their APIs defined (considering the questions above)? Just as with a single line of code, the answers to these questions will define how tightly coupled a service is to the rest of the system around it.

Having coupling which is too tight for a remote service carries troubles, too. Changes to downstream systems may force the service to need an update. Any change to the API may require upstream services to change as well. It may be impossible to change the service’s implementation if it is too tightly coupled to its own API. Finally, it may be difficult to break the service into separate services as it grows in scope. It can be a costly and painful mistake down the road to allow too much coupling between services in a distributed environment.

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