CREDIT: Although this article is my own work, it is based on ideas I got from a very different but interesting early draft from Practicing Ruby reader Mike Subelsky. I owe him a huge hat tip for suggesting that we cover this topic and for helping me get started with it.

The challenge of sensibly connecting a set of objects together to perform a complex task is one that confounds programmers of all skill levels. In fact, it is hard to reason about the relationships between objects without getting trapped by analysis paralysis. With that in mind, it is no surprise that so many of us struggle with this particular aspect of object-oriented programming.

But like so many other problems we encounter in our work, this one can be simplified greatly by introducing a common vocabulary and some rough heuristics that make thinking and communicating about our code easier. For reasoning about this particular design challenge, the “Object Peer Stereotypes” described in Growing Object-Oriented Software, Guided by Tests give us some very useful conceptual tools to work with.

In this article, we will explore the three stereotypical relationships between an object and its peers that were described in GOOS: dependencies, notifications, and adjustments. Taken together, these rough categorizations do a good job of identifying the kinds of connections that exist between objects, which makes it easier to develop a more nuanced view of how they communicate with each other.

The specific examples in this article are based on code from Newman (my experimental email-based microframework), but the general concepts that we’ll discuss are relevant to all object-oriented software. If you keep your own projects in the back of your mind as you read on, you’ll easily find similarities between Newman’s design challenges and your own.


Services that the object requires from its peers so it can perform its responsibilities. The object cannot function without these services. It should not be possible to create the object without them. (GOOS, pg. 52)

Whether they are internal or external, dependency relationships need to be carefully managed in order to prevent brittleness. Alistair Cockburn’s ports and adapters pattern provides one way of dealing with this problem: define abstract ports in the application’s domain language that covers slices of functionality, and then build implementation-specific adapters with compatible interfaces. This approach allows dependencies to be reasoned about at a higher level of abstraction and makes it so that systems can be easily changed.

We applied this pattern (albeit without recognizing it by name) when thinking through how Newman should handle its email dependency. We knew from the outset that we’d need to support some sort of test mailer and that it should be a drop-in replacement for its real mailer. We also anticipated that down the line we might want to support delivery mechanisms other than the mail gem and figured that some sort of adapter-based approach would be a good fit.

Constructing a port involves thinking through the various ways a subsystem will be used within your application and then mapping a protocol to those use cases. In Newman, we expected that our email dependency would need to support the following requirements:

1) Read configuration data from a Newman::Settings object if necessary.

mailer =

2) Retrieve all messages from an inbox, deleting them from the server in the process.

mailer.messages.each do |message|

3) Construct a complete message and deliver it immediately.

mailer.deliver_message(:to      => "[email protected]",
                       :from    => "[email protected]",
                       :subject => "A special offer for you!!!",
                       :body    => "Send me your credit card number, plz!")

4) Construct a message incrementally and then deliver it later, if at all.

message = mailer.new_message(:to   => "[email protected]",
                             :from => "[email protected]")

if bank_account.balance < 1_000_000_000
  message.subject = "Can I interest you in some prescription painkillers?"
  message.body    = "Best prices anywhere on the internets!!!"

Although you can make an educated guess about how to implement adapters for this port based on the previous examples, there are many unanswered questions lurking just beneath the surface. This is where the difference between interfaces and protocols becomes important:

An interface defines whether two things can fit together, a protocol defines whether two things can work together (GOOS, pg. 58)

If you revisit the code examples shown above, you’ll notice that the interface requirements for a Newman-compatible mail adapter are roughly as follows:

  • The constructor accepts one argument (the settings object).
  • The messages method returns an collection that responds to each and yields an object for each message in the inbox.
  • The deliver_message accepts one argument (a parameters hash).
  • The new_message method accepts a parameters hash and returns an object representing the message. At a minimum, the object allows certain fields to be set (i.e., subject and body) and responds to a deliver method.

Building an object that satisfies these requirements is trivial, but there is no guarantee that doing so will result in an adapter that conforms to the protocol that Newman expects. Unfortunately, protocols are much harder to reason about and define than interfaces are.

Like many Ruby libraries, Newman relies on loose duck typing rather than a formal behavioral contract to determine whether one adapter can serve as a drop-in replacement for another. The Newman::Mailer object is used by default, so it defines the canonical implementation that other adapters are expected to mimic at the functional level – even if they handle things very differently under the hood. This implicit contract makes it possible for Newman::TestMailer to stand in for a Newman::Mailer object, even though it stores all incoming and outgoing messages in memory rather than relying on SMTP and IMAP. Because the two objects respond to the same messages in similar ways, the systems that depend on them are unaware of their differences in implementation – they are just two different adapters that both fit in the same port.

If you read through the source of the Newman::Mailer and Newman::TestMailer objects, you will find that several compromises have been made for the sake of convenience:

  1. Arguments for the new_message and deliver_message methods on both adapters are directly delegated to the Mail::Message constructor, and the return value of messages on both adapters is a collection of Mail::Message objects. This design implicitly ties the interface of those methods to the mail gem; it’s what GOOS calls a hidden dependency.

  2. The Newman::TestMailer object is a singleton object, but it implements a fake constructor in order to maintain interface compatibility with Newman::Mailer. This is an example of how constraints from dependencies can spill over into client code.

  3. Configuration data is completely ignored by Newman::TestMailer. Because all of its operations are done in memory, it has no need for SMTP and IMAP settings, but it needs to accept the settings object anyway for the sake of maintaining interface compatibility.

All of these warts stem from protocol issues. The first issue is due to underspecification: Newman has a clear protocol for creating, retrieving, and sending messages, but it does not clearly define what it expects the messages themselves to look like. The coupling between the interface of Newman::Mailer and that of Mail::Message makes it so that other adapters must also inherit this hidden dependency. Because Newman::TestMailer also explicitly depends upon Mail::Message, this constraint does not complicate its implementation, but it certainly does make it harder to build adapters that aren’t dependent on the mail gem.

On the flip side, the second and third issues are a result of overspecification. We didn’t want to make Newman::TestMailer a singleton, but because the underlying Mail::TestMailer is implemented that way, we didn’t have much of a choice. Our decision to implement a fake constructor in order to maintain compatibility with Newman::Mailer is something I was never happy with, but I also couldn’t think of a better alternative. I am somewhat less concerned about Mailer::TestMailer having to accept a settings object that it doesn’t actually use, but it does feel like one extra hoop to jump through simply for the sake of consistency.

Despite these rough edges, Newman’s way of handling its email dependency is a good example of the ports and adapters pattern in the wild. If anything, it serves as a reminder that the hard part of writing loosely coupled code is not in the creation of duck-typed adapters, but in clearly defining the protocol for our ports. This concept takes us beyond the idea of “coding to an interface rather than an implementation” and is worth ruminating over.


Peers that need to be kept up to date with the object’s activity. The object will notify interested peers whenever it changes state or performs a significant action. Notifications are ‘fire and forget’; the object neither knows nor cares which peers are listening. (GOOS, pg. 52)

Because Ruby is a message-oriented programming language, it is easy to model many kinds of object relationships as notifications. Doing so greatly reduces the coupling between objects and helps establish a straight-line flow from a system’s inputs to its outputs.

Notification-based modeling is especially useful when designing framework code, because it is important for frameworks to know as little as possible about the applications that are built on top of them. The general design of the extremely popular rack web server interface leverages these ideas to great effect; it assumes that its applications implement a meaningful call method, but otherwise remains blissfully ignorant of their behaviors.

We have designed Newman using a similar strategy, and the general idea can be understood by tracing the execution of the Newman::Server#tick method:

module Newman
  class Server
    # NOTE: the mailer, apps, logger, and settings dependencies
    # are initialized when a Server instance is instantiated

    def tick
      mailer.messages.each do |request|
        response = mailer.new_message(:to   => request.from,
                                      :from => settings.service.default_sender)

        process_request(request, response) && response.deliver

      # ... error handling code omitted

    def process_request(request, response)
      apps.each do |app|  => request,
                 :response => response,
                 :settings => settings,
                 :logger   => logger)

      return true

      # ... error handling code omitted

Did you figure out how it works? Let’s walk through the process step by step to confirm:

  1. The tick method walks over each incoming message currently queued by the mailer object (i.e., the request).

  2. A response message is constructed and addressed to the sender of the request.

  3. The process_request method is called, which iterates over a collection, executing the call method on each element and passing along several dependencies that can be used to finish building a meaningful response message.

  4. Once process_request completes successfully, the response is delivered.

Because Newman::Server has a notification-based relationship with its apps collection, it does not know or care about the structure of those objects. In fact, the contract is so simple that a trivial Proc object can serve as a fully functioning Newman application:

Greeter = ->(params) { |params| params[:response].subject = "Hello World!" }

server.apps = [Greeter]

If we wanted to make things a bit more interesting, we could add request and response logging into the mix, using Newman’s built-in features:

Greeter = ->(params) { |params| params[:response].subject = "Hello World!" }

server.apps = [Newman::RequestLogger, Greeter, Newman::ResponseLogger]

These objects make use of a mixin that simplifies email logging, but as you can see from the following code, they have no knowledge of the Newman::Server object and rely entirely on the parameters being passed into their #call method:

module Newman
  class << (RequestLogger =
    include EmailLogger

    def call(params)
      log_email(params[:logger], "REQUEST", params[:request]) 

  class << (ResponseLogger =
    include EmailLogger

    def call(params)
      log_email(params[:logger], "RESPONSE", params[:response])

Taken together, these four objects combined form a cohesive workflow:

  1. The server receives incoming emails and passes them on to its apps for processing, along with a placeholder response object.

  2. The request logger inspects the incoming email and records debugging information.

  3. The greeter sets the subject of the outgoing response to “Hello World”.

  4. The response logger inspects the outgoing email and records debugging information.

  5. The server sends the response email.

The remarkable thing is not this semimundane process, but that the objects involved know virtually nothing about their collaborators and are unaware of their position in the sequence of events. Context-independence (GOOS, pg. 54) is a powerful thing, because it allows each object to be reasoned about, tested, and developed in isolation.

The implications of notification-based modeling extend far beyond context independence, but it wouldn’t be easy to summarize them in a few short sentences. Fortunately, this topic has been covered extensively in other Practicing Ruby articles, particularly in Issue 4.11 and Issue 5.2. Be sure to read those articles if you haven’t already; they are among the finest in our collection.


Peers that adjust the object’s behavior to the wider needs of the system. This includes policy objects that make decisions on the object’s behalf . . . and component parts of the object if it’s a composite. (GOOS, pg. 52)

Adjustment relationships are hard to summarize, because they can exist in so many forms. But regardless of the form they take on, adjustments tend to be used to bridge the gap between different levels of abstraction. Some are used to raise the level of abstraction by wrapping a specific object in a more generic interface, and others are designed to do the opposite.

For an example of climbing down the ladder of abstraction, consider Newman::EmailLogger. It is implemented as a module in Newman for convenience, but it could easily be reimagined as a stateless peer object of RequestLogger and ResponseLogger. Such a redesign would yield something similar to the following code:

module Newman
  class << (EmailLogger =
    def log_email(logger, prefix, email)
      logger.debug(prefix) { "\n#{email}" } { email_summary(email) }


    def email_summary(email)
      { :from     => email.from,
        :to       =>,
        :bcc      => email.bcc,
        :subject  => email.subject,
        :reply_to => email.reply_to }

  RequestLogger = ->(params) {  
    EmailLogger.log_email(params[:logger], "REQUEST", params[:request])

  ResponseLogger = ->(params) {
    EmailLogger.log_email(params[:logger], "RESPONSE", params[:response])

Though this is a subtle change, it lifts up and centralizes the concept of “email logging” into a single object, rather than mixing helper methods into various objects that need that functionality. This adjustment helps define the borders between distinct concepts within the code and establishes EmailLogger as an adjustment to the much more general Logger object it depends upon.

The philosophical distinction between these two objects is what matters here. A Logger has very abstract responsibilities: it must record arbitrary strings at various levels of severity and then format and output them to various streams. EmailLogger, on the other hand, is extremely concrete in its responsibilities: it uses a Logger to report debugging information about an email message. The details of how the actual logging happens are hidden from EmailLogger’s clients, making it easier to treat as a black box.

Simple designs can also emerge from climbing the ladder of abstraction, that is, moving from a very specific context to a much more general one. For example, it might not be a bad idea to introduce an object into Newman that encapsulates the concept of an email message but leaves the exact delivery mechanism up to the individual adapters:

# this code would be in an adapter or application code
message = { |params| }

# elsewhere, no knowledge of the dependency on the mail gem would be necessary:      = "[email protected]"
message.from    = "[email protected]"
message.subject = "You have won twenty bazillion dollars!"
message.body    = "Please send us a hair sample to confirm your ID"


This kind of object is trivial to implement because it is nothing more than a value object with a simple callback mechanism bolted on top of it:

module Newman 
  class Message
    def initialize(&delivery_callback)
      self.delivery_callback = delivery_callback

    attr_accessor :to, :from, :subject, :body

    def deliver
      raise NotImplementedError unless delivery_callback

      delivery_callback.(:to      => to,      :from => from, 
                         :subject => subject, :body => body)


    attr_accessor :delivery_callback

Despite its simplicity, this object provides a useful benefit: it explicitly separates the protocol of message delivery from its implementation. If all mail adapters for Newman were expected to return only Newman::Message objects, then any message-processing code within Newman (either in the server or in application code) would have a well-defined interface to work against. Although this requirement would make adapters slightly more cumbersome to write, it would completely eliminate the hidden dependency issue discussed earlier.

Regardless of which direction they are pointed in, adjustment relationships are very closely related to the concept of object composition in general. With that in mind, the authors of GOOS have a useful rule to consider when designing composite objects:

The API of a composite object should not be more complicated than that of any of its components. (GOOS, pg. 54)

Notice that in both the Newman::EmailLogger example and the Newman::Message object, the result of composition is that a more complex system is being wrapped by something with fewer methods and concepts to worry about. When applied repeatedly, this kind of design causes software to become more simple as it grows.


The benefit I have gained from being able to explicitly label various object relationships as dependencies, notifications, and adjustments is that it forces me to think about my code in a more fine-grained way. Each kind of object relationship comes with benefits and costs that are easier to reason about when you recognize them for what they are.

As with most ideas from Growing Object-Oriented Software, Guided by Tests, I have not yet had a chance to apply this particular set of heuristics frequently enough to know the full extent of their usefulness. However, it never hurts to have specific words to describe ideas that previously were hard for me to express without relying heavily on intuition.

I would love to hear from you if you can think of ways to connect these ideas back to your own projects or to the open source projects you’ve worked with. If you have an interesting story to share, please leave a comment!