This post is part of the November 2008 Pablo's Topic Of The Month (PTOM) - Design Patterns and will outline a simple Command pattern, its implementation and use.

One of the core principles of object oriented software development is the idea of Coupling, "the degree to which each program module relies on each one of the other modules" (Wikipedia). When we build software, we should strive to attain low coupling - keep the individual modules of the system as separated as possible. Of course, if there is zero coupling in a system, then the system won't really do much for us. After all, you can't write software that is very useful if you are not allowed to have any dependencies.

Setting Up Shop

Before we break down into the pattern, let's consider the context of a Point Of Sale system at a coffee shop. In this system, we have a menu where your server can punch in your order with all of the options you want and produce an order that is fulfilled somewhere else. When the server starts pressing the menu items and the system begins to compile the order, there is a connection between the menu system that they are using, the various products that have been configured in the system, and the back-end ordering system. This is a rather obvious location where coupling can quickly become high - the UI, the products, and the back-end ordering system could very quickly become a spaghetti mess of tangled dependencies and tight coupling - but we don't want that, do we?

To combat the coupling problems of this situation while still allowing dependencies, we need to introduce various forms of abstraction - simple dependencies that are not specific to any implementation, allowing us to change the implementation when we need to. In the case of a menu - be it a WinForms application, a touch screen point of sale system, or whatever else - a Command pattern is often employed to enable the system's functionality without being directly coupled to the actual menu.

The Command Pattern

Originally outlined by the infamous "Gang of Four", the Command Pattern is described as an object that represents an action - a command that will be executed. Within the context of a command, we have several parts that need to be accounted for.

• First and foremost, there is the actual command object - the action that is executed.
• Second, we have the command invoker - the object that depends on the commands existence, and knows how to execute the command.
• And lastly, we have the target of the invocation - the part of the system that needs to take action when the command is executed.

A Simple Implementation

To facilitate the decoupling of specific modules in our system, our command pattern implementations will be created with a naming convention that represents the objects as commands. For example, a very basic command implementation in C# can be represented as an interface such as this:

public interface ICommand

{

  void Execute();

}

By abstracting our command into an interface, we can provide any implementation we need at runtime. This lets us select a coffee from our point of sale system and have another part of the system actually create and handle the order. A pseudo-complete implementation of a command pattern to order a cup of coffee may look something like this:

public interface ICommand

{

   void Execute();

}

public class MenuItem

{

   private ICommand _menuCommand;

   public Text { get; set; }

   public MenuItem(string menuText, ICommand menuCommand)

   {

       Text = menuText;

       _menuCommand = menuCommand;

   }

   public void Click()

   {

       _menuCommand.Execute();

   }

}

public class RegularCoffeeCommand: ICommand

{

   private SomeOrderingSystem _orderingSystem;

   public RegularCoffeeCommand(SomeOrderingSystem orderingSystem)

   {

       _orderingSystem = orderingSystem;

   }

   public void Execute()

   {

       Product regularCoffee = new Product("RegularCoffee", 2.99);

       _orderingSystem.PlaceOrder(regularCoffee);

   }

}

//... somewhere in the application UI

MenuItem regularCoffeeMenuItem = new MenuItem("Regular Coffee", new RegularCoffeeCommand());

//... and when the menu item is clicked

regularCoffeeMenuItem.Click();

The real power of this implementation is that we have completely decoupled our menu system from any specific knowledge of the product ordering system in our coffee shop. All our menu item needs to know about is the ICommand interface. At the same time, our back-end implementation also knows about the ICommand interface - but the back-end also knows about the actual product ordering system. This allows us to create an implementation of the ICommand interface that knows how to invoke our target system. The end result is that we can independently vary the menu system for ordering coffee and our back-end product ordering system.

More Complexity And More Flexibility

Great News! Our command pattern implementations don't have to be limited to such a rigid interface. In fact, my current project has no less than 4 different ICommand interface variations. By introducing the use of generics in C#, we can create some very flexible commands. As an example, consider the following additional interface definitions:

public interface ICommand<T>

{

   T Execute();

}

public interface IParameterizedCommand<V>

{

   void Execute(V value);

}

public interface IParameterizedCommand<T, V>

{

   T Execute(V value);

}

These new interface definitions, in combination with the original definition above, can create a very flexible and very useful set of commands in a system. By creating a "parameterized command" interface, we can provide detail in the command execution that is not available at the time the command is instantiated. And by adding another non-parameterized command with a return value, we can create a system that is able to interact in more complex ways.

With these new command interfaces in mind, let's take another look at our RegularCoffeeCommand. Instead of hard coding the price of the coffee into the command, let's push that knowledge off to another part of the system.

public class RegularCoffeeCommand: IParameterizedCommand<Price>

{

   private SomeOrderingSystem _orderingSystem;

   public RegularCoffeeCommand(SomeOrderingSystem orderingSystem)

   {

       _orderingSystem = orderingSystem;

   }

   public void Execute(Price coffeePrice)

   {

       Product regularCoffee = new Product("RegularCoffee", coffeePrice);

       _orderingSystem.PlaceOrder(regularCoffee);

   }

}

By providing an interface that accepts a parameter, we can move the knowledge of the coffee's price out to another part of the system and provide it at runtime - a database call, a web services call, or anything else we want.

But Wait! There's More!

As you can see, the command pattern can be very useful in helping us decouple our coffee shop's point of sale system from the back-end product ordering system. Some very simple interface definitions can provide a lot of flexibility in how we compose our systems, as well.

What's more - we aren't actually limited to interfaces or base classes for abstracting our commands in .NET. The built in delegate system in .NET provides a great way to encapsulate commands with method pointers. I've previously talked about The Point of Delegates in .NET where I mentioned that delegates provide us with a way of delaying the execution of code. Though it's not strictly an "object" as the command pattern describes, a delegate certainly sounds like a command pattern implementation just waiting to break out of it's skin. In fact, I have created a few command pattern implementations using nothing more than the built in delegates in .NET, several times.

Whether you decide to use interfaces, delegates, abstract classes, or any other implementation method that you can come up with, I hope that you will think about including a command pattern implementation in your systems. It is an easy way of conquering the problems of high coupling between user interfaces and back-ends of the system.

In my last post, I talked about the idea of encapsulation and using it to ensure that our business rules were enforced correctly. What I didn't talk about, though, was the second half of the conversation that my coworker and I had, concerning the patent -> consultation relationship. It turns out that we had the relationship wrong. That's not to say that patients don't have consultations, but that the logical model we were traveling with had an incorrect perspective and was causing us to create some very ugly workarounds in various parts of the system. What really stuck out in my mind, though, was not the idea that we had the model wrong, but how we came to the conclusion of the model being wrong. It has become apparent to me, upon reflection of the conversations and situation as a whole, that design smells are not always evidenced by design related activities, if ever.

A Persistent Problem - Duplicate Redundancy

After some initial coding of the patient -> consultation relationship, we start working on the persistence model via NHibernate. What we have is a patient with a collection of consultations - this is easy to map with NHibernate's one-to-many capabilities. We also have a CurrentConsultation property which needs to be mapped. This property is mapped to the same Consultation table, but only pull one specific consultation based on the business rules that state the current consultation is chronologically the most recent and has not ending date set.

After some thought, we found that there were a few possibilities for handling the CurrentConsultation property in our current model:

1. Create a "CurrentConsultation" object that is mapped to the Consultation table and use a "where" class attribute in the NHibernate mapping that would limit the returned result
2. Create a "CurrentConsultation" object that is mapped to a CurrentConsultation view and have the view coded to return the correct consultation object
3. Add a CurrentConsultationId field to the Patient table, as a foreign key to the Consultations table, and map to the existing Consultation object

After some additional thought, though, we found that each of these solutions has a few significant problems that were going to cause a lot of trouble.

Options 1 and 2

Both of these options have the problem of duplicating business rules into more than one language and location. We would either have the business rules of what constitutes the current consultation in the NHibernate mapping (the 'where' attribute) or in a database view, in addition to the already existing code. Changing the rule would mean changing a minimum of two locations where that rule is handled. This is a bad idea no matter how you look at it.

Both of the options have also created a duplication of knowledge from the concept of a Consultation by creating a "CurrentConsultation" class and a separate NHibernate map for it. We would have the original Consultation class and the new CurrentConsultation class both representing the same data, making an artificial distinction in our code. Again, this is a bad idea. We don't want duplication of these logical concepts. We're also not dealing with a bounded context or any other logical separation of concerns at this point, so there is no need to separate the concept of a consultation into multiple classes.

Option 3

This doesn't appear to have the duplication issue in code, but there is a potential for duplication of data. When we get down to the implementation of NHibernate, we could easily cause duplicate data in the consultation table by saving the current consultation class. We might be able to get around this by not cascading the saves of the current consultation property, but then we'd be forced to ensure the consultation collection was persisted prior to the patient so that we could update the current consultation object's id before saving the patient. Both of these problems sound like a serious pain to me. I'm betting it's possible, but I'm also betting that it would be a nightmare of trial and error to get it right and a lot more code than we should really have to write.

Changing Perspectives

As Joe Ocampo pointed out in the comments of my original post, we had a problem in our system that was really caused by our lack of correct perspective in the situation. Rather than forcing the idea of a patient being the root aggregate in this situation, causing us a lot of headache and frustration in trying to model our persistence layer, a simple change in how we looked at the situation helped us solve the persistence problem and greatly simplified how the application worked.

Joe's comment (with some formatting added):

"One thing I like to challenge developers with when I teach DDD is to flip the aggregate to determine if the model is sound.

I know this is only an example but work with me here.  You indicated you are dealing with a medical system.  We can assume there are certain entities such as Patient, Consultations, Doctor and Practice. In your example you created a model where the patient is the aggregate root for consultations but what if the Doctor simply asked what consultations do I have today?  In this paradigm the Practice is the aggregate root and Consultations are aggregate within where Patient is an aspect of the consultation.  The code would look something like this.

consultations = practiceService(IConsultationService).GetConsultationsFor(doctor);

This also allows the consultation service to encapsulate its own logic for creating a consultation for creating a consultation. You can’t get any closer than that

consultationService.CreateConsultationFor(patient).with(doctor).at(date);

The point I am trying to make is be careful of aggregate roots.  Once you go down that path it is really difficult to back the train up and break it apart."

Though our actual implementation was different, this was the same basic conclusion that we had come to - our perspective on the situation was simply wrong. When we stepped back from the problem and realized that the consultation was the primary focus of the situation, and that a nurse or doctor would be the primary user of that portion of the system, it became rather obvious that our aggregate was in dire need of rework.

A Reflective Perspective

What we ended up with was a Patient object that dealt with all of it's demographics information, billing information, etc, without a CurrentConsultation property or even a Consultations list. Then, on the the separated Consultation object, we added a child property of Patient. Once we realized that our Consultation object was the primary focus and made this distinction in our code, we also realized that the Patient object was carrying far too much information around the system. We found that we actually had two very distinct concepts of a patient, determined by two very distinct bounded contexts.

• In the 'Billing' context, we needed all of the address , billing, and other demographics information about the patient - who they are, where they live, what their insurance is, etc. The existing Patient class filled this need.
• In the 'Consultations' context, we did not need anything from the Billing context, except for the person's name and patient id. What we really care about in the consultations is medical information about the patient - their current prescriptions, allergies, past medical care, etc. So, we created a ' patient' class to represent these needs.

These changed allowed for a much more clearly defined model that was truly reflective of the systems needs. We could easily see the difference between a 'billing' patient and a 'medical' patient, and we were able to code each of these areas of the system without the concerns bleeding into each other. Essentially, we decoupled the system at a module level, not just at a class level.

We also found that the NHibernate mapping problems suddenly went away. Since the Consultation class had a child of Patient, it was a simple many-to-one mapping with no strange sequencing or duplicate data issues. In the screens that deal with the consultation directly, we load the consultation as the aggregate root and go from there. In the screens that need to show patient consultation history, we did a simple query and returned all of the consultations for the given patient. Again, we found a way to decouple our system - this time, at the persistence model.

Design Smells: Not Just A Design Problem

In the end, we were able to recognize a serious design smell in our system - not by the design itself, though. After all, the original code had encapsulated the needs quite well. But, as it turns out, it was a bad encapsulation at a higher level. It wasn't until we started working with the model we had created, specifically trying to persist the model, that we realized our design was not right.

This change was a huge breakthrough for us, not necessarily in the code or the system that was being built, but in how we look at our systems and our domain models. The realization that design smells are often evidenced not by the design itself, but by how the design is used in the infrastructure and other supporting roles of the system, has had a profound impact on how we look at system design. I'm now seeing areas of different systems that are encapsulated incorrectly, at a higher level than class design. Recognizing the problem is the first step - and we're now working to rearrange and invert these models to more accurately reflect reality.

Pay attention to the pain that your application, infrastructure and other supporting services are causing you. You may be staring at evidence of a design problem, without realizing it.

Yesterday, I was involved two very separate yet very related conversations. One was via twitter with Colin Jack and Jimmy Bogard (which I was only a partial contributor to - mostly just reading their conversation) and another after work with a coworker. The short version of both conversations can be boiled down to encapsulation of logic surrounding collections that are held by entities. Rather than rehash all of the conversations, I wanted to specifically address a violation of encapsulation that I've seen many times when dealing with collections and business rules.

Let's look at a small example where we have a medical system that deals with Patients that are having Consultations with doctors. There is a need to keep track of the historic consultations and also the current consultation, if any. For simplicity we'll say that the current consultation is identified as being the most recent, based on a starting date, and that any previous consultation must have an ending date. A very simplistic implementation of an object model to represent patients and consultations may look something like this:

public class Patient

{

  private IList<Consultation> _consultations = new List<Consultation>();

  public IList<Consultation> Consultations { get { return _consultations; } }

  public Consultation CurrentConsultation { get; set; }

}

public class Consultation

{

  public DateTime StartingDate { get; set; }

  public DateTime EndingDate { get; set; }

}

Then, when the time comes to add a new consultation to the patient, making it the current one and closing a previous consultation, code may get called from somewhere in the application (like a code behind of a form, or if you're lucky, in the Presenter or Controller of an MVP/C setup), like this:

Consultation consultation = new Consultation{ StartingDate = DateTime.Now };

patient.Consultations.Add(consultation);

if (patient.CurrentConsultation != null)

  patient.CurrentConsultation.EndingDate = DateTime.Now;

patient.CurrentConsultation = consultation;

From a purely technical standpoint, there is nothing wrong with this code. It implements the business rule as defined. However, this code misses out on some great opportunities to encapsulate the rules we have into a process that can be called from anywhere that the system needs it - whether or not the code is in the specific presenter / controller that creates a new consultation or not. The very same code that comprises this implementation could easily be placed in the Patient object, abstracting the rules and process of creating a new consultation into a simple, single method call.

Before I show how I would approach that solution, though, there is one other implementation that I've seen recently that not only breaks encapsulation, but has to compensate for the lack of rules enforcement with logic in the wrong place. Instead of storing the current consultation as a set value, the CurrentConsultation property may have some logic in it to dynamically determine which consultation is the current one.

public class Patient

{

  private IList<Consultation> _consultations = new List<Consultation>();

  public IList<Consultation> Consultations { get { return _consultations; } }

  public Consultation CurrentConsultation 

  {

      get 

      {

          Consultation currentConsultation;

          DateTime mostRecent = DateTime.MinValue;

          foreach(Consultation consultation in _consultations)

          {

              if (consultation.StartingDate > mostRecent)

              {

                  mostRecent = consultation.StartingDate;

                  if (consultation.EndingDate == DateTime.MinValue)

                  {

                      currentConsultation = consultation;

                  }

              }

          }

      }

  }

}

This type of code is a huge encapsulation violation smell. Since our Patient object has no enforcement of the consultations that it holds, there is no way for us to really know which consultation is the current one. Because of this, the retrieval of the current consultation has to process the entire consultation collection and try to find the most recent consultation that has no ending date.

On top of the encapsulation issue, we have lost a great deal of performance. We now have to loop through the list every time we need the current consultation. If the list is small, this might not be such a bad problem, but as the list grows and as this code is used more and more, the performance problem may have a serious impact on the system.

Fortunately, the solution to the encapsulation violation, the enforcement of the business rules and the performance problem can all be wrapped up in to some very simple code. The first thing we want to do is prevent the ad-hoc addition of consultations to the patient. We still need to access the list of consultations, but we don't really have a need to modify it outside of the patient class itself. This can be done with a one-line code change to the Patient class's Consultations property:

public class Patient

{

  private IList<Consultation> _consultations = new List<Consultation>();

  public IEnumerable<Consultation> Consultations { get { return _consultations as IEnumerable; } }

  //ignoring other implementation details for the sake of illustrating the IEnumerable change

}

Now that we have prevented the ability to do ad-hoc consultation additions, we need a way to actually add consultations. While we are doing this, we also want to enforce the business rules of the current consultation as described earlier. This is where we are going to take much of the original code that we found in the presenter / controller and place it into the patient class directly.

public class Patient

{

  private IList<Consultation> _consultations = new List<Consultation>();

  public IEnumerable<Consultation> Consultations { get { return _consultations as IEnumerable; } }

  public Consultation CurrentConsultation { get; private set; }

  public void StartConsultation()

  {

      Consultation newConsultation = new Consultation{ StartingDate = DateTime.Now };

      if (CurrentConsultation != null)

          CurrentConsultation.EndingDate = DateTime.Now;

      CurrentConsultation = newConsultation;

      Consultations.Add(newConsultation);

  }

}

In the end, this code shows a better encapsulation of the business rules and logic that surrounds the need to maintain a list of consultations and a current consultation. With this code in place, we could simplify the presenter / controller that we talked about initially. Rather than being forced to know all of that logic in the presenter, we can make one simple method call:

 patient.StartConsultation();

With this one simple call, we have a guaranteed execution of the business rules that we need. This will allow us to recreate the ability to add a new consultation at any point in the application that we need, not just in the original presenter / controller that we were working with.

Side Note:

Part of the conversation via twitter revolved around where this type of logic should be encapsulated. From what I gathered, Colin tends to place this logic in custom collection objects, which would allow him to call patient.Consultations.Add() and still encapsulate the same business rules into that method. Like everything else in software development, there are multiple ways to solve the same problem. What does your specific situation, project, team, and business context need? Whatever your implementation needs are, though, we need to keep this type of logic and business rules enforcement well encapsulated in our systems.

A coworker recently asked if we should always abstract every object into an interface in order to fulfill the Dependency Inversion Principle (DIP). The question stunned me at first, honestly. I knew in my head that this was a bad idea - abstracting into interfaces for the sake of abstraction leads down the path of needless complexity. However, I wasn't able to clearly answer his question with specific examples of when you would not want to do this, at the time. I've been thinking about this for a few days now and I think I have a good, albeit very long winded, answer.

Before the question is answered, though, we need to step back and look at what DIP is all about. I've previously shown how to implement DIP and talked about why it's beneficial, so I won't be repeating that here. Rather, I want to talk about the language that describes DIP and what it really means.

Robert Martin's original definition of DIP is this:

A. High level modules should not depend upon low level modules. Both should depend upon abstractions.
B. Abstractions should not depend upon details. Details should depend upon abstractions.

The word 'abstraction' is used three times in the definition for DIP. So, in order to understand DIP, we have to first understand some of the basics of Abstraction.

Some Background On Abstraction

From Wikipedia (emphasis mine):

"In computer science, abstraction is a mechanism and practice to reduce and factor out details so that one can focus on a few concepts at a time"

I can't say it any better than this.

Abstraction can very directly lead to a system that is more understandable by helping us ignore the detail and implementation specifics, allowing us to focus on something at a higher level. This reduction in cognitive load can benefit someone that is reading the code by not forcing them to know the detail immediately. Additionally, abstraction is a form of encapsulation or information hiding, which again helps us to reduce cognitive load and produce better systems. From Wikipedia's entry on Information Hiding:

"In computer science, the principle of information hiding is the hiding of design decisions in a computer program that are most likely to change, thus protecting other parts of the program from change if the design decision is changed."

At the heart of abstraction and information hiding, we find the ability to change the system. The ability to change is an absolute requirement in software development and produces good design that is easier to work with, modify, and put back together as needed. The inability to change is directly called "bad design" by Robert Martin, in the DIP article.

Applying Abstraction And Encapsulation To DIP

So how does our knowledge of abstraction and information hiding play into DIP?

First and foremost, DIP never states that we should depend on explicit interfaces. Yes, in C# we have an explicit Interface as a form of abstraction. It is a separation of the implementation detail from the publicly available methods, properties, etc, of a class. Some languages, such as C++, don't have an explicit construct for interfaces, though. From Robert Martin's original DIP article, again:

"In C++ however, there is no separation between interface and implementation. Rather, in C++, the separation is between the definition of the class and the definition of its member functions."

A String As An Abstraction

Abstraction does always mean explicit interface constructs, as evidenced in C++. Nor does it always mean an abstract base class, which we also have available in .NET. In fact, languages such as Ruby don't really need either of these constructs. The duck-type nature of Ruby allows an implementation to be replaced at any point, without any special constructs. In .NET, though, there are a number of abstraction forms that we can rely on, explicitly. We have the obvious interfaces and base classes (abstract or not) - but we also have constructs like delegates and lambda expressions, and even the simple types that are built into the base class library.

Let's look at a simple string to illustrate abstraction. As I said in my SOLID presentation at ADNUG, we can invert our dependency on database connection information.  Rather than putting a connection string directly into our code that calls the database, we can use the string as our dependency and our abstraction. All we need to do is follow the basic DIP principle and provide the string as a parameter to the class that calls the database. We certainly don't need (or want, for that matter) to introduce a new interface or base class at this point. Our abstraction is simple enough to use a common type