A model .NET web service based on Domain Driven Design Part 4: the abstract Repository

Introduction

In the previous post we created a very basic domain layer with the first domain object: Customer. We’ll now see what the data access layer could look like in an abstract form. This is where we must be careful not to commit the same mistakes as in the technology-driven example of the introductory post of this series.

We must abstract away the implementation details of the data access technology we use so that we can easily switch strategies later if necessary. We cannot let any technology-specific implementation bubble up from the data access layer. These details include the object context in EntityFramework, MongoClient and MongoServer in MongoDb .NET, the objects related to the file system in a purely file based data access solution etc., you probably get the idea. We must therefore make sure that no other layer will be dependent on the concrete data access solution.

We’ll first lay the foundations for abstracting away any type of data access technology and you may find it a “heavy” process with a steep learning curve. As these technologies come in many different shapes this is not the most trivial task to achieve. We can have ORM technologies like EntityFramework, file-based data storage like MongoDb, key-value style storage such as Azure storage, and it’s not easy to find a common abstraction that fits all of them. We’ll need to accommodate these technologies without hurting the ISP principle too much. We’ll follow a couple of well-established patterns and see how they can be implemented.

Aggregate root

We discussed aggregates and aggregate roots in this post. Recall that aggregates are handled as one unit where the aggregate root is the entry point, the “boss” of the aggregate. This implies that the data access layer should only handle aggregate roots. It should not accept objects that lie somewhere within the aggregate. We haven’t yet implemented any code regarding aggregate roots, but we can take a very simple approach. Insert the following empty interface in the Infrastructure.Common/Domain folder:

public interface IAggregateRoot
{
}

Conceptually it would probably be better to create a base class for aggregate roots, but we already have one for entities. As you know an object cannot derive from two base classes so we’ll indicate aggregate roots with this interface instead. At present it is simply an indicator interface with no methods, such as the ISerializable interface in .NET. We could add common properties or methods here but I cannot think of any right now.

After consulting the domain expert we decide that the Customer domain is an aggregate root: the root of its own Customer aggregate. Right now the Customer aggregate has only one member, the Customer entity, but that’s perfectly acceptable. Aggregate roots don’t necessarily consist of at least 2 objects. Let’s change the Customer domain object declaration as follows:

public class Customer : EntityBase<int>, IAggregateRoot

The rest of the post will look at how to abstract away the data access technology and some patterns related to that.

Unit of work

The first important concept within data access and persistence is the Unit of Work. The purpose of a Unit of Work is to maintain a list of objects that have been modified by a transaction. These modifications include insertions, updates and deletions. The Unit of Work co-ordinates the persistence of these changes and also checks for concurrency problems, such as the same object being modified by different threads.

This may sound a bit cryptic but if you’re familiar with EntityFramework or Linq to SQL then the object context in each technology is a good example for an implementation of a unit of work:

DbContext.AddObject("Customers", new Customer());
DbContext.SaveChanges();
DbContext.Customers.InsertOnSubmit(new Customer());
DbContext.SubmitChanges();

In both cases the DbContext, which takes the role of the Unit of Work, first registers the changes. The changes are not persisted until the SaveChanges() – EntityFramework – or the SubmitChanges() – Linq to SQL – method is called. Note that the DB object context is responsible for registering AND persisting the changes.

The Unit of Work pattern can be represented by the following interface:

public interface IUnitOfWork
{
	void RegisterUpdate(IAggregateRoot aggregateRoot);
	void RegisterInsertion(IAggregateRoot aggregateRoot);
	void RegisterDeletion(IAggregateRoot aggregateRoot);
	void Commit();
}

Notice that we have separated the registration and commit actions. In the case of EntityFramework and similar ORM technologies the object that registers and persists the changes will often be the same: the object context or a similar object.

However, this is not always the case. It is perfectly reasonable that you are not fond of these automation tools and want to use something more basic where you have the freedom of specifying how you track changes and how you persist them: you may register the changes in memory and persist them in a file. Or you may still have a lot of legacy ADO.NET where you want to move to a more modern layered architecture. ADO.NET lacks a DbContext object so you may have to solve the registration of changes in a different way.

For those scenarios we need to introduce another abstraction. Insert the following interface in a new folder called UnitOfWork in the Infrastructure layer:

public interface IUnitOfWorkRepository
{
	void PersistInsertion(IAggregateRoot aggregateRoot);
	void PersistUpdate(IAggregateRoot aggregateRoot);
	void PersistDeletion(IAggregateRoot aggregateRoot);
}

Insert a new interface called IUnitOfWork in the same folder:

public interface IUnitOfWork
{
	void RegisterUpdate(IAggregateRoot aggregateRoot, IUnitOfWorkRepository repository);
	void RegisterInsertion(IAggregateRoot aggregateRoot, IUnitOfWorkRepository repository);
	void RegisterDeletion(IAggregateRoot aggregateRoot, IUnitOfWorkRepository repository);
	void Commit();
}

The above Unit of Work pattern abstraction can be extended as above to give way for the total separation between the registration and persistence of aggregate roots. Later on, as we see these elements at work and as you get more acquainted with the structure of the solution, you may decide that this is overkill and you want to go with the more simple solution, it’s up to you.

Repository pattern

The repository pattern is used to declare the possible data access related actions you want to expose for your aggregate roots. The most basic of those are CRUD operations: insert, update, delete, select. You can have other methods such as insert many, select by ID, select by id and date etc., but the CRUD operations are probably the most common across all aggregate roots.

It may be beneficial to divide those operations into two groups: read and write operations. You may have a read-only policy for some aggregate roots so you don’t need to expose all of those operations. For read-only aggregates you can have a read-only repository. Insert the following interface in the Domain folder of the Infrastructure project:

public interface IReadOnlyRepository<AggregateType, IdType> where AggregateType : IAggregateRoot
{
	AggregateType FindBy(IdType id);
	IEnumerable<AggregateType> FindAll();
}

Here again we only allow aggregate roots to be selected. Finding an object by its ID is such a basic operation that it just has to be included here. FindAll can be a bit more sensitive issue. If you have a data table with millions of rows then you may not want to expose this method as it will bog down your data server, so use it with care. It’s perfectly OK to omit this operation from this interface. You will be able to include this method in domain-specific repositories as we’ll see in the next post. E.g. if you want to enable the retrieval of all Customers from the database then you can expose this method in the CustomerRepository class.

The other data access operations can be exposed in an “actionable” interface. Insert the following interface in the folder of the Infrastructure project:

public interface IRepository<AggregateType, IdType> 
		: IReadOnlyRepository<AggregateType, IdType> where AggregateType 
		: IAggregateRoot
{
	void Update(AggregateType aggregate);
	void Insert(AggregateType aggregate);
	void Delete(AggregateType aggregate);
}

Keep in mind that these interfaces only expose the most common actions that are applicable across all aggregate roots. You’ll be able to specify domain-specific actions in domain-specific implementations of these repositories.

We’ll look at how these elements can be implemented for the Customer object in the next post.

View the list of posts on Architecture and Patterns here.

A model .NET web service based on Domain Driven Design Part 3: the Domain

Introduction

In the previous post we laid the theoretical foundation for our domains. Now it’s finally time to see some code. In this post we’ll concentrate on the Domain layer and we’ll also start building the Infrastructure layer.

Infrastructure?

Often the word infrastructure is taken to mean the storage mechanism, like an SQL database, or the physical layers of a system, such as the servers. However, in this case we mean something different. The infrastructure layer is a place for all sorts of cross-cutting concerns and objects that can be used in any project. They are not specific to any single project or domain. Examples: logging, file operations, security, caching, helper classes for Date and String operations etc. Putting these in a separate infrastructure layer helps if you want to employ the same logging, caching etc. policy across all your projects. You could put these within the project solution but then when you start your next project then you may need to copy and paste a lot of code.

Infrastructure

The Entities we discussed in the previous post will all derive from an abstract EntityBase class. We could put it directly into the domain layer. However, think of this class as the base for all entities across all your DDD projects where you put all common functionality for your domains.

Create a new blank solution in VS and call it DDDSkeletonNET.Portal. Add a new C# class library called DDDSkeletonNET.Infrastructure.Common. Remove Class1 and add a new folder called Domain. In that folder add a new class called EntityBase:

public abstract class EntityBase<IdType>
{
	public IdType Id { get; set; }

	public override bool Equals(object entity)
	{
		return entity != null
		   && entity is EntityBase<IdType>
		   && this == (EntityBase<IdType>)entity;
	}

	public override int GetHashCode()
	{
		return this.Id.GetHashCode();
	}

	public static bool operator ==(EntityBase<IdType> entity1, EntityBase<IdType> entity2)
	{
		if ((object)entity1 == null && (object)entity2 == null)
		{
			return true;
		}

		if ((object)entity1 == null || (object)entity2 == null)
		{
			return false;
		}

		if (entity1.Id.ToString() == entity2.Id.ToString())
		{
			return true;
		}

		return false;
	}

	public static bool operator !=(EntityBase<IdType> entity1, EntityBase<IdType> entity2)
	{
		return (!(entity1 == entity2));
	}
}

We only have one property at this point, the ID, whose type can be specified through the IdType type parameter. Often this will be an integer or maybe a GUID or even some auto-generated string. The rest of the code takes care of comparison issues so that you can compare two entities with the ‘==’ operator or the Equals method. Recall that entityA == entityB if an only if their IDs are identical, hence the comparison being based on the ID property.

Domains need to validate themselves when insertions or updates are executed so let’s add the following abstract method to EntityBase.cs:

protected abstract void Validate();

We can describe our business rules in many ways but the simplest format is a description in words. Add a class called BusinessRule to the Domain folder:

public class BusinessRule
{
	private string _ruleDescription;

	public BusinessRule(string ruleDescription)
	{
		_ruleDescription = ruleDescription;
	}

	public String RuleDescription
	{
		get
		{
			return _ruleDescription;
		}
	}
}

Coming back to EntityBase.cs we’ll store the list of broken business rules in a private variable:

private List<BusinessRule> _brokenRules = new List<BusinessRule>();

This list represents all the business rules that haven’t been adhered to during the object composition: the total price is incorrect, the customer name is empty, the person’s age is negative etc., so it’s all the things that make the state of the object invalid. We don’t want to save objects in an invalid state in the data storage, so we definitely need validation.

Implementing entities will be able to add to this list through the following method:

protected void AddBrokenRule(BusinessRule businessRule)
{
	_brokenRules.Add(businessRule);
}

External code will collect all broken rules by calling this method:

public IEnumerable<BusinessRule> GetBrokenRules()
{
	_brokenRules.Clear();
	Validate();
	return _brokenRules;
}

We first clear the list so that we don’t return any previously stored broken rules. They may have been fixed by then. We then run the Validate method which is implemented in the concrete domain classes. The domain will fill up the list of broken rules in that implementation. The list is then returned. We’ll see in a later post on the application service layer how this method can be used from the outside.

We’re now ready to implement the first domain object. Add a new C# class library called DDDSkeleton.Portal.Domain to the solution. Let’s make this easy for us and create the most basic Customer domain. Add a new folder called Customer and in it a class called Customer which will derive from EntityBase.cs. The Domain project will need to reference the Infrastructure project. Let’s say the Customer will have an id of type integer. At first the class will look as follows:

public class Customer : EntityBase<int>
{
	protected override void Validate()
	{
		throw new NotImplementedException();
	}
}

We know from the domain expert that every Customer will have a name, so we add the following property:

public string Name { get; set; }

Our first business rule says that the customer name cannot be null or empty. We’ll store these rule descriptions in a separate file within the Customer folder:

public static class CustomerBusinessRule
{
	public static readonly BusinessRule CustomerNameRequired = new BusinessRule("A customer must have a name.");
}

We can now implement the Validate() method in the Customer domain:

protected override void Validate()
{
	if (string.IsNullOrEmpty(Name))
	{
		AddBrokenRule(CustomerBusinessRule.CustomerNameRequired);
	}
}

Let’s now see how value objects can be used in code. The domain expert says that every customer will have an address property. We decide that we don’t need to track Addresses the same way as Customers, i.e. we don’t need to set an ID on them. We’ll need a base class for value objects in the Domain folder of the Infrastructure layer:

public abstract class ValueObjectBase
{
	private List<BusinessRule> _brokenRules = new List<BusinessRule>();

	public ValueObjectBase()
	{
	}

	protected abstract void Validate();

	public void ThrowExceptionIfInvalid()
	{
		_brokenRules.Clear();
		Validate();
		if (_brokenRules.Count() > 0)
		{
			StringBuilder issues = new StringBuilder();
			foreach (BusinessRule businessRule in _brokenRules)
			{
				issues.AppendLine(businessRule.RuleDescription);
			}

			throw new ValueObjectIsInvalidException(issues.ToString());
		}
	}

	protected void AddBrokenRule(BusinessRule businessRule)
	{
		_brokenRules.Add(businessRule);
	}
}

…where ValueObjectIsInvalidException looks as follows:

public class ValueObjectIsInvalidException : Exception
{
     public ValueObjectIsInvalidException(string message)
            : base(message)
        {}
}

You’ll recognise the Validate and AddBrokenRule methods. Value objects can of course also have business rules that need to be enforced. In the Domain layer add a new folder called ValueObjects. Add a class called Address in that folder:

public class Address : ValueObjectBase
{
	protected override void Validate()
	{
		throw new NotImplementedException();
	}
}

Add the following properties to the class:

public string AddressLine1 { get; set; }
public string AddressLine2 { get; set; }
public string City { get; set; }
public string PostalCode { get; set; }

The domain expert says that every Address object must have a valid City property. We can follow the same structure we took above. Add the following class to the ValueObjects folder:

public static class ValueObjectBusinessRule
{
	public static readonly BusinessRule CityInAddressRequired = new BusinessRule("An address must have a city.");
}

We can now complete the Validate method of the Address object:

protected override void Validate()
{
	if (string.IsNullOrEmpty(City))
	{
		AddBrokenRule(ValueObjectBusinessRule.CityInAddressRequired);
	}
}

Let’s add this new Address property to Customer:

public Address CustomerAddress { get; set; }

We’ll include the value object validation in the Customer validation:

protected override void Validate()
{
	if (string.IsNullOrEmpty(Name))
	{
		AddBrokenRule(CustomerBusinessRule.CustomerNameRequired);
	}
	CustomerAddress.ThrowExceptionIfInvalid();
}

As the Address value object is a property of the Customer entity it’s practical to include its validation within this Validate method. The Customer object doesn’t need to concern itself with the exact rules of an Address object. Customer effectively tells Address to go and validate itself.

We’ll stop building our domain layer now. We could add several more domain objects but let’s keep things as simple as possible so that you will be able to view the whole system without having to track too many threads. We now have an example of an entity, a value object and a couple of basic validation rules. We have missed how aggregate roots play a role in code but we’ll come back to that in the next post. You probably want to see how the repository, service and UI layers can be wired together.

We’ll start building the repository layer in the next post.

View the list of posts on Architecture and Patterns here.

A model .NET web service based on Domain Driven Design Part 2: DDD basics

Introduction

In the previous post we discussed how a traditional data access based layering can cause grief and sorrow. We’ll now move on to a better design and we’ll start with – what else – the domain layer. It is the heart of software, as Eric Evans put it, which should be the centre of the application. It should reflect our business entities and rules as close as possible. It will be an ever-evolving layer where you add, modify and remove bits of code as you get to know the domain better and better. The initial model will grow to a deep model with experimenting, brainstorming and knowledge crunching.

Before we dive into any code we have to discuss a couple of important terms. The domain layer is so important that an entire vocabulary has evolved around it. I promise to get to some real C# code after the theory.

Entities and value objects

Domain objects can be divided into entities and value objects.

An entity is an object with a unique ID. This unique ID is the most important property of an entity: it helps distinguish between two otherwise identical objects. We can have two people with the same name but if their IDs are different then we’re talking about two different people. Also, a person can change his/her name, but if the ID is the same then we know we’re talking about the same person. An ID is typically some integer or a GUID or some other string value randomly generated based on some properties of the object. Once the entity has been persisted, its ID should never change otherwise we lose track of it. In Sweden every legal person and company receives a personal registration number. Once you are given this ID it cannot be changed. From the point of view of the Swedish authorities this ID is my most important “property”. EntityA == EntityB if and only if EntityA.ID == EntityB.ID. Entities should ideally remain very clean POCO objects without any trace of technology-specific code. You may be tempted to add technology specific elements such s MVC attributes in here, e.g. [Required] or [StringLength(80)]. DON’T DO THAT. EVER! We’ll see later where they belong.

A value object on the other hand lacks any sort of ID. E.g. an office building may have 100 windows that look identical. Depending on your structure of the building you may not care which exact window is located where. Just grab whichever and mount it in the correct slot. In this case it’s futile to assign an ID to the window, you don’t care which one is which. Value objects are often used to group certain properties of an Entity. E.g. a Person entity can have an Address property which includes other properties such as Street and City. In your business an Address may well be a value object. In other cases, such as a postal company business, an Address will almost certainly be an Entity. A value object can absolutely have its own logic. Note that if you save value objects in the database it’s reasonable to assume that they will be assigned an automatic integer ID, but again – that’s an implementation detail that only concerns how our domain is represented in the storage, the domain layer doesn’t care, it will ignore the ID assigned by the data storage mechanism.

Sometimes it’s not easy to decide whether a specific object is an entity or a value object. If two objects have identical properties but we still need to distinguish between them then it’s most likely an entity with a unique ID. If two objects have identical properties and we don’t care which one is which: a value object. If the same object can be shared, e.g. the same Name can be attached to many Person objects: most likely a value object.

Aggregates and aggregate roots

Objects are seldom “independent”: they have other objects attached to them or are part of a larger object graph themselves. A Person object may have an Address object which in turn may have other Person objects if more than one person is registered there. It can be difficult to handle in software: if we delete a Person, then do we delete the Address as well? Then other Person objects registered there may be “homeless”. We can leave the Address in place, but then the DB may be full of empty, redundant addresses. Objects may therefore have a whole web of interdependency. Where does an object start and end? Where are its boundaries? There’s clearly a need to organise the domain objects into logical groups, so-called aggregates. An aggregate is a group of associated objects that are treated as a unit for the purpose of data changes. Every aggregate has a root and clear boundaries. The root is the only member of an aggregate that outside objects are allowed to hold references to.

Example

Take a Car object: it has a unique ID, e.g. the registration number to distinguish it from other cars. Each tire must also be measured somehow, but it’s unlikely that they will be treated separately from the car they belong to. It’s also unlikely that we make a DB search for a tire to see which car it belongs to. Therefore the Car is an aggregate root whose boundary includes the tires. Therefore consumers of the Car object should not be able to directly change the tire settings of the car. You may go as far as hiding the tires entirely within the Car aggregate and only let outside callers “get in touch with them” through methods such as “MoveCarForward”. The internal logic of the Car object may well modify the tires’ position, but to the outside world that is not visible.

An engine will probably also have a serial number and may be tracked independently of the car. It may happen that the engine is the root of its own aggregate and doesn’t lie within the boundaries of the Car, it depends on the domain model of the application.

Car aggregate root

An important term in conjunction with Aggregates is invariants. Invariants are consistency rules that must be maintained whenever data changes, so they represent business rules.

General guidelines for constructing the domain layer

Make sure that you allocate the best and most experienced developers available at your company to domain-related tasks. Often experienced programmers spend their time on exploring and testing new technologies, such as WebSockets. Entry-level programmers are then entrusted to construct the domain layer as technologically it’s not too difficult: write abstract and concrete classes, interfaces, methods, properties, that’s it really. Every developer should be able to construct these elements after completing a beginners’ course in C#. So people tend to think that this is an entry-level task. However, domain modelling and writing code in a loosely coupled and testable manner are no trivial tasks to accomplish.

Domains are the most important objects in Domain Driven Design. They are the objects that describe our business. They are so central that you should do your utmost to keep them clean, well organised and testable. It is worth building a separate Domain layer even during the mockup phase of a new project, even if you ignore the other layers. If you need to allocate time to maintain each layer within your solution then this layer should be allocated the most. This is important to keep in mind because you know how it usually goes with test projects – if management thinks it’s good then you often need to continue to build upon your initial design. There’s no time to build a better application because suddenly you are given a tight deadline. Then you’re stuck with a domain-less solution.

Domain objects should always be the ones that take priority. If you have to change the domain object to make room for some specific technology, then you’re taking the wrong direction. It is the technology that must fit the domain objects, not vice versa.

Domain objects are also void of persistence-related code making them technology agnostic or persistence ignorant. A Customer object will not care how it is stored in a database table, that is an irrelevant implementation detail.

Domain objects should be POCO and void of technology-specific attributes, such as the ones available in standard MVC, e.g. [Required]. Domain objects should be clear of all such ‘pollution’. Also, all logic specific to a domain must be included in the domain. These business rules contain validation rules as well, such as “the quantity should not be negative” or “a customer must not buy more than 5 units of this product”. Resist the temptation to write external files, such as CustomerHelper etc. where you put domain-specific logic, that’s not right. A domain is responsible to implement its specific domain logic. Example: in a banking application we may have an Account domain with a rule saying that the balance cannot be negative. You must include this validation logic within Account.cs, not in some other helper class. If the Account class has a complex validation logic then it’s fine to factor out the IMPLEMENTATION of the validation. i.e. the method body to a separate helper class. However, having a helper class that totally encapsulates domain validation and other domain-specific logic is the incorrect approach. Consumers of the domain will not be aware that there is some external class that they need to call. If domain specific logic is placed elsewhere then not even a visual inspection of the class file will reveal the domain logic to the consumer.

Make sure to include logic specific to a single domain object. Example: say you have an object called Observation with two properties of type double: min and max. If you want to calculate the average then Observation.cs will have a method called CalculateAverage and return the average of min and max, i.e. it performs logic on the level of a single domain object.

In the next post we’ll look at how these concepts can be written in code.

View the list of posts on Architecture and Patterns here.

A model .NET web service based on Domain Driven Design Part 1: introduction

Introduction

Layered architecture has been the norm in enterprise projects for quite some time now. We layer our solutions into groups of responsibilities: UI, services, data access, infrastructure and others. We can connect these layers by setting references to them from the consuming layer. There are various ways to set these layers and references. The choices you make here depend on the project type – Web, WPF, WCF, games etc. – you’re working on and the philosophy you follow.

On the one hand you may be very technology driven and base your choices primarily on the technologies available to build your project: Entity Framework, Ajax, MVC etc. Most programmers are like that and that’s natural. It’s a safe bet that you’ve become a developer because you’re interested in computers and computer-related technologies like video games and the Internet. It’s exciting to explore and test new technologies as they emerge: .NET, ORM, MVC, WebAPI, various JavaScript libraries, WebSockets, HighCharts, you name it. In fact, you find programming so enthralling that you would keep doing it for free, right? Just don’t tell your boss about it in the next salary review… With this approach it can happen in a layered architecture that the objects in your repository layer, i.e. the data access layer, such as an SQL Server database, will receive the top focus in your application. This is due to the popular ORM technologies available in .NET: EntityFramework and Linq to SQL. They generate classes based on some database representation of your domain objects. All other layers will depend on the data access layer. We’ll see an example of this below.

On the other hand you may put a different part of the application to the forefront: the domain. What is the domain? The domain describes your business. It is a collection of all concepts and logic that drive your enterprise. If you follow this type of philosophy, which is the essence of Domain Driven Design (DDD), then you give the domain layer the top priority. It will be the most important ingredient of the application. All other layers will depend on the domain layer. The domain layer will be an entirely independent one that can function on its own. The most important questions won’t be “How do we solve this with WebSockets?” or “How does it work with AngularJs?” but rather like these ones:

  • How does the Customer fit into our domain?
  • Have we modelled the Product domain correctly?
  • Is this logic part of the Product or the OrderItem domain?
  • Where do we put the pricing logic?

Technology-related questions will suddenly become implementation details where the exact implementation type can vary. We don’t really care which graph package we use: it’s an implementation detail. We don’t really care which ORM technology we use: it’s an implementation detail.

Of course technology-related concerns will be important aspects of the planning phase, but not as important as how to correctly represent our business in code.

In a technology-driven approach it can easily happen that the domain is given low priority and the technology choices will directly affect the domain: “We have to change the Customer domain because its structure doesn’t fit Linq to SQL”. In DDD the direction is reversed: “An important part of our Customer domain structure has changed so we need to update our Linq to SQL classes accordingly.”. A change in the technology should never force a change in your domain. Your domain is an independent entity that only changes if your business rules change or you discover that your domain logic doesn’t represent the true state of things.

Keep in mind that it is not the number of layers that makes your solution “modern”. You can easily layer your application in a way that it becomes a tightly coupled nightmare to work with and – almost – impossible to extend. If you do it correctly then you will get an application that is fun and easy to work with and is open to all sorts of extensions, even unanticipated ones. This last aspect is important to keep in mind. Nowadays customers’ expectations and wishlists change very often. You must have noticed that the days of waterfall graphs, where the the first version of the application may have rolled out months or even years after the initial specs were written, are over. Today we have a product release every week almost where we work closely with the customer on every increment we build in. Based on these product increments the customer can come with new demands and you better be prepared to react fast instead of having to rewrite large chunks of your code.

Goals of this series

I’ll start with stating what’s definitely not the goal: give a detailed account on all details and aspects of DDD. You can read all about DDD by its inventor Eric Evans in this book. It’s a book that discusses all areas of DDD you can think of. It’s no use regurgitating all of that in these posts. Also, building a model application which uses all concepts from DDD may easily grow into full-fledged enterprise application, such as SAP.

Instead, I’ll try to build the skeleton of a .NET solution that takes the most important ideas from DDD. The result of this skeleton will hopefully be a solution that you can learn from and even tweak it and use in your own project. Don’t feel constrained by this specific implementation – feel free to change it in a way that fits your philosophy.

However, if you’re completely new to DDD then you should still benefit from these posts as I’ll provide explanations for those key concepts. I’ll try to avoid giving you too much theory and rather concentrate on code but some background must be given in order to explain the key ideas. We’ll need to look at some key terms before providing any code. I’ll also refer to ideas from SOLID here and there – if you don’t understand this term then start here.

Also, it would be great to build the example application with TDD, but that would add a lot of noise to the main discussion. If you don’t know what TDD means, start here.

The ultimate goal is to end up with a skeleton solution with the following layers:

  • Infrastructure: infrastructure services to accommodate cross-cutting concerns
  • Data access (repository): data access and persistence technology layer, such as EntityFramework
  • Domain: the domain layer with our business entities and logic, the centre of the application
  • Application services: thin layer to provide actions for the consumer(s) such as a web or desktop app
  • Web: the ultimate consumer of the application whose only purpose is to show data and accept requests from the user

…where the layers communicate with each other in a loosely coupled manner through abstractions. It should be easy to replace an implementation with another. Of course writing a new version of – say – the repository layer is not a trivial task and layering won’t make it easier. However, the switch to the new implementation should go with as little pain as possible without the need to modify any of the other layers.

The Web layer implementation will actually be a web service layer using the Web API technology so that we don’t need to waste time on CSS and HTML. If you don’t know what Web API is about, make sure you understand the basics from this post.

UPDATE: the skeleton application is available for download on GitHub here.

Doing it wrong

Let’s take an application that is layered using the technology-driven approach. Imagine that you’ve been tasked with creating a web application that lists the customers of the company you work for. You know that layered architectures are the norm so you decide to build these 3 layers:

  • User Interface
  • Domain logic
  • Data access

You know more or less what the Customer domain looks like so you create the following table in SQL Server:

Customer table in SQL Server

Then you want to use the ORM capabilities of Visual Studio to create the Customer class for you using the Entity Framework Data Model Wizard. Alternatively you could go for a Linq to SQL project type, it doesn’t make any difference to our discussion. At this point you’re done with the first layer in your project, the data access one:

Entity Framework model context

EntityFramework has created a DbContext and the Customer class for us.

Next, you know that there’s logic attached to the Customer domain. In this example we want to refine the logic of what price reduction a customer receives when purchasing a product. Therefore you implement the Domain Logic Layer, a C# class library. To handle Customer-related queries you create a CustomerService class:

public class CustomerService
{
	private readonly ModelContext _objectContext;

	public CustomerService()
	{
		_objectContext = new ModelContext();
	}

	public IEnumerable<Customer> GetCustomers(decimal totalAmountSpent)
	{
		decimal priceDiscount = totalAmountSpent > 1000M ? .9m : 1m;
		List<Customer> allCustomers = (from c in _objectContext.Customers select c).ToList();
		return from c in allCustomers select new Customer()
		{
			Address = c.Address
			, DiscountGiven = c.DiscountGiven * priceDiscount
			, Id = c.Id
			, IsPreferred = c.IsPreferred
			, Name = c.Name
		};
	}
}

As you can see the final price discount depends also on the amount of money spent by the customer, not just the value currently stored in the database. So, that’s some extra logic that is now embedded in this CustomerService class. If you’re familiar with SOLID then the ‘_objectContext = new ModelContext();’ part immediately raises a warning flag for you. If not, then make sure to read about the Dependency Inversion Principle.

In order to make this work I had to add a library reference from the domain logic to the data access layer. I also had to add a reference to the EntityFramework library due to the following exception:

The type ‘System.Data.Entity.DbContext’ is defined in an assembly that is not referenced. You must add a reference to assembly ‘EntityFramework, Version=4.4.0.0, Culture=neutral, PublicKeyToken=b77a5c561934e089’.

So I import the EntityFramework library into the DomainLogic layer to make the project compile.

At this point I have the following projects in the solution:

Data access and domain logic layer

The last layer to add is the UI layer, we’ll go with an MVC solution. The Index() method which lists all customers might look like the following:

public class HomeController : Controller
{
	public ActionResult Index()
	{
		decimal totalAmountSpent = 1000; //to be fetched with a different service, ignored here
		CustomerService customerService = new CustomerService();
		IEnumerable<Customer> customers = customerService.GetCustomers(totalAmountSpent);
		return View(customers);
	}	
}

In order to make this work I had to reference both the DomainLogic AND the DataAccess projects from the UI layer. I now have 3 layers in the solution:

DDD three layers

So I press F5 and… …get an exception:

“No connection string named ‘ModelContext’ could be found in the application config file.”

This exception is thrown at the following line within CustomerService.GetCustomers:

List<Customer> allCustomers = (from c in _objectContext.Customers select c).ToList();

The ModelContext object implicitly expects that a connection string called ModelContext is available in the web.config file. It was originally inserted into app.config of the DataAccess layer by the EntityFramework code generation tool. So a quick fix is to copy the connection string from this app.config to web.config of the web UI layer:

<connectionStrings> 
    <add name="ModelContext" connectionString="metadata=res://*/Model.csdl|res://*/Model.ssdl|res://*/Model.msl;provider=System.Data.SqlClient;provider connection string=&quot;data source=mycomputer;initial catalog=Test;integrated security=True;MultipleActiveResultSets=True;App=EntityFramework&quot;" providerName="System.Data.EntityClient" />
</connectionStrings>

Evaluation

Have we managed to build a “modern” layered application? Well, we certainly have layers, but they are tightly coupled. Both the UI and the Logic layer are strongly dependent on the DataAccess layer. Examples of tight coupling:

  • The HomeController/Index method constructs a CustomerService object
  • The HomeController/Index directly uses the Customer object from the DataAccess layer
  • The CustomerService constructs a new ModelContext object
  • The UI layer is forced to include an EntityFramework-specific connection string in its config file

At present we have the following dependency graph:

DDD wrong dependency graph

It’s immediately obvious that the UI layer can easily bypass any logic and consult the data access layer directly. It can read all customers from the database without applying the extra logic to determine the price discount.

Is it possible to replace the MVC layer with another UI type, say WPF? It certainly is, but it does not change the dependency graph at all. The WPF layer would also need to reference both the Logic and the DataAccess layers.

Is it possible to replace the data access layer? Say you’re done with object-relational databases and want to switch to file-based NoSql solutions such as MongoDb. Or you might want to move to a cloud and go with an Azure key-value type of storage. We don’t need to go as far as entirely changing the data storage mechanism. What if you only want to upgrade your technology Linq to SQL to EntityFramework? It can be done, but it will be a difficult process. Well, maybe not in this small example application, but imagine a real-world enterprise app with hundreds of domains where the layers are coupled to such a degree with all those references that removing the data access layer would cause the application to break down immediately.

The ultimate problem is that the entire domain model is defined in the data access layer. We’ve let the technology – EntityFramework – take over and it generated our domain objects based on some database representation of our business. It is an entirely acceptable solution to let an ORM technology help us with programming against a data storage mechanism in a strongly-typed object-oriented fashion. Who wants to work with DataReaders and SQL commands in a plain string format nowadays? However, letting some data access automation service take over our core business and permeate the rest of the application is far from desirable. The CustomerService constructor tightly couples the DomainLogic to EntityFramework. Since we need to reference the data access layer from within our UI even the MVC layer is coupled to EntityFramework. In case we need to change the storage mechanism or the domain logic layers we potentially have a considerable amount of painful rework to be done where you have to manually overwrite e.g. the Linq to SQL object context references to EntityFramework object context ones.

We have failed miserably in building a loosely coupled, composable application whose layers have a single responsibility. The domain layer, as stated in the introduction, should be the single most important layer in your application which is independent of all other layers – possibly with the exception of infrastructure services which we’ll look at in a later post in this series. Instead, now it is a technological data access layer which rules and where the domain logic layer is relegated to a second-class citizen which can be circumvented entirely.

The domain is at the heart of our business. It exists regardless of any technological details. If we sell cars, then we sell cars even if the car objects are stored in an XML file or in the cloud. It is a technological detail how our business is represented in the data storage. It is something that the Dev department needs to be concerned with. The business rules and domains have a lot higher priority than that: it is known to all departments of the company.

Another project type where you can easily confuse the roles of each layer is ASP.NET WebForms with its code behind. It’s very easy to put a lot of logic, database calls, validation etc. into the code-behind file. You’ll soon end up with the Smart UI anti-pattern where the UI is responsible for all business aspects of your application. Such a web application is difficult to compose, unit test and decouple. This doesn’t mean that you must forget WebForms entirely but use it wisely. Look into the Model-View-Presenter pattern, which is sort of MVC for WebForms, and then you’ll be fine.

So how can we better structure our layers? That will be the main topic of the series. However, we’ll need to lay the foundation for our understanding with some theory and terms which we’ll do in the next post.

View the list of posts on Architecture and Patterns here.

SOLID design principles in .NET: the Dependency Inversion Principle Part 5, Hello World revisited

Introduction

I realise that the previous post should have been the last one on the Dependency Inversion Principle but I decided to add one more, albeit a short one. It can be beneficial to look at one more example where we take a very easy starting point and expand it according to the guidelines we’ve looked at in this series.

The main source in the series on Dependency Injection is based on the work of Mark Seemann and his great book on DI.

Demo

The starting point of the exercise is the good old one-liner Hello World programme:

static void Main(string[] args)
{
	Console.WriteLine("Hello world");
}

Now that we’re fluent in DIP and SOLID we can immediately see a couple of flaws with this solution:

  • We can only write to the Console – if we want to write to a file then we’ll have to modify Main
  • We can only print Hello world to the console – we have to manually overwrite this bit of code if we want to print something else
  • We cannot easily extend this application in a sense that it lacks any seams that we discussed before – what if we want to add logging or security checks?

Let’s try to rectify these shortcomings. We’ll tackle the problem of message printing first. The Adapter pattern solves the issue by abstracting away the Print operation in an interface:

public interface ITextWriter
{
	void WriteText(string text);
}

We can then implement the Console-based solution as follows:

public class ConsoleTextWriter : ITextWriter
{
	public void WriteText(string text)
	{
		Console.WriteLine(text);
	}
}

Next let’s find a solution for collecting what the text writer needs to output. We’ll take the same approach and follow the adapter pattern:

public interface IMessageCollector
{
	string CollectMessageFromUser();
}

…with the corresponding Console-based implementation looking like this:

public class ConsoleMessageCollector : IMessageCollector
{
	public string CollectMessageFromUser()
	{
		Console.Write("Type your message to the world: ");
		return Console.ReadLine();
	}
}

These loose dependencies must be injected into another object, let’s call it PublicMessage:

public class PublicMessage
{
	private readonly IMessageCollector _messageCollector;
	private readonly ITextWriter _textWriter;

	public PublicMessage(IMessageCollector messageCollector, ITextWriter textWriter)
	{
		if (messageCollector == null) throw new ArgumentNullException("Message collector");
		if (textWriter == null) throw new ArgumentNullException("Text writer");
		_messageCollector = messageCollector;
		_textWriter = textWriter;
	}

	public void Shout()
	{
		string message = _messageCollector.CollectMessageFromUser();
		_textWriter.WriteText(message);
	}
}

You’ll realise some of the most basic techniques we’ve looked at in this series: constructor injection, guard clause, readonly private backing fields.

We can use these objects from Main as follows:

static void Main(string[] args)
{
	IMessageCollector messageCollector = new ConsoleMessageCollector();
	ITextWriter textWriter = new ConsoleTextWriter();
	PublicMessage publicMessage = new PublicMessage(messageCollector, textWriter);
	publicMessage.Shout();

	Console.ReadKey();
}

Now we’re free to inject any implementation of those interfaces: read from a database and print to file; read from a file and print to an email; read from the console and print to some web service. The PublicMessage class won’t care, it’s oblivious of the concrete implementations.

This solution is a lot more extensible. We can use the decorator pattern to add functionality to the text writer. Let’s say we want to add logging to the text writer through the following interface:

public interface ILogger
{
	void Log();
}

We can have some default implementation:

public class DefaultLogger : ILogger
{
	public void Log()
	{
		//implementation ignored
	}
}

We can wrap the text printing functionality within logging as follows:

public class LogWriter : ITextWriter
{
	private readonly ILogger _logger;
	private readonly ITextWriter _textWriter;

	public LogWriter(ILogger logger, ITextWriter textWriter)
	{
		if (logger == null) throw new ArgumentNullException("Logger");
		if (textWriter == null) throw new ArgumentNullException("TextWriter");
		_logger = logger;
		_textWriter = textWriter;
	}

	public void WriteText(string text)
	{
		_logger.Log();
		_textWriter.WriteText(text);
	}
}

In Main you can have the following:

static void Main(string[] args)
{
	IMessageCollector messageCollector = new ConsoleMessageCollector();
	ITextWriter textWriter = new LogWriter(new DefaultLogger(), new ConsoleTextWriter());
	PublicMessage publicMessage = new PublicMessage(messageCollector, textWriter);
	publicMessage.Shout();

	Console.ReadKey();
}

Notice that we didn’t have to do anything to PublicMessage. We passed in the interface dependencies as before and now we have the logging function included in message writing. Also, note that Main is tightly coupled to a range of objects, but it is acceptable in this case. We construct our objects in the entry point of the application, i.e. the composition root which is the correct place to do that. We don’t new up any dependencies within PublicMessage.

This was of course a very contrived example. We expanded the original code to a lot more complex solution with a lot higher overhead. However, real life applications, especially enterprise ones are infinitely more complicated where requirements change a lot. Customers are usually not sure what they want and wish to include new and updated features in the middle of the project. It’s vital for you as a programmer to be able to react quickly. Enabling loose coupling like that will make your life easier by not having to change several seemingly unrelated parts of your code.

View the list of posts on Architecture and Patterns here.

SOLID design principles in .NET: the Dependency Inversion Principle Part 4, Interception and conclusions

Introduction

I briefly mentioned the concept of Interception in the this post. It is a technique that can help you implement cross-cutting concerns such as logging, tracing, caching and other similar activities. Cross-cutting concerns include actions that are not strictly related to a specific domain but can potentially be called from many different objects. E.g. you may want to cache certain method results pretty much anywhere in your application so potentially you’ll need an ICacheService dependency in many places. In the post mentioned above I went through a possible DI pattern – ambient context – to implement such actions with all its pitfalls.

If you’re completely new to these concepts make sure you read through all the previous posts on DI in this series. I won’t repeat what was already explained before.

The idea behind Interception is quite simple. When a consumer calls a service you may wish to intercept that call and execute some action before and/or after the actual service is invoked.

It happens occasionally that I do the shopping on my way home from work. This is a real life example of interception: the true purpose of my action is to get home but I “intercept” that action with another one, namely buying some food. I can also do the shopping when I pick up my daughter from the kindergarten or when I want to go for a walk. So I intercept the main actions PickUpFromKindergarten() and GoForAWalk() with the shopping action because it is convenient to do so. The Shopping action can be injected into several other actions so in this case it may be considered as a Cross-Cutting Concern. Of course the shopping activity can be performed in itself as the main action, just like you can call a CacheService directly to cache something, in which case it too can be considered as the main action.

The main source in the series on Dependency Injection is based on the work of Mark Seemann and his great book on DI.

The problem

Say you have a service that looks up an object with an ID:

public interface IProductService
{
	Product GetProduct(int productId);
}
public class DefaultProductService : IProductService
{
	public Product GetProduct(int productId)
	{
		return new Product();
	}
}

Say you don’t want to look up this product every time so you decide to cache the result for 10 minutes.

Possible solutions

Total lack of DI

The first “solution” is to directly implement caching within the GetProduct method. Here I’m using the ObjectCache object located in the System.Runtime.Caching namespace:

public Product GetProduct(int productId)
{
	ObjectCache cache = MemoryCache.Default;
	string key = "product|" + productId;
	Product p = null;
	if (cache.Contains(key))
	{
		p = (Product)cache[key];
	}
	else
	{
		p = new Product();
		CacheItemPolicy policy = new CacheItemPolicy();
		DateTimeOffset dof = DateTimeOffset.Now.AddMinutes(10);
		policy.AbsoluteExpiration = dof;
		cache.Add(key, p, policy);
	}
	return p;
}

We check the cache using the cache key and retrieve the Product object if it’s available. Otherwise we simulate a database lookup and put the Product object in the cache with an absolute expiration of 10 minutes.

If you’ve read through the posts on DI and SOLID then you should know that this type of code has numerous pitfalls:

  • It is tightly coupled to the ObjectCache class
  • You cannot easily specify a different caching strategy – if you want to increase the caching time to 20 minutes then you’ll have to come back here and modify the method
  • The method signature does not tell anything to the caller about caching, so it violates the idea of an Intention Revealing Interface mentioned before
  • Therefore the caller will need to intimately know the internals of the GetProduct method
  • The method is difficult to test as it’s impossible to abstract away the caching logic. The test result will depend on the caching mechanism within the code so it will be inconclusive

Nevertheless you have probably encountered this style of coding quite often. There is nothing stopping you from writing code like that. It’s quick, it’s dirty, but it certainly works.

As an attempt to remedy the situation you can factor out the caching logic to a service:

public class SystemRuntimeCacheStorage
{
	public void Remove(string key)
	{
		ObjectCache cache = MemoryCache.Default;
		cache.Remove(key);
	}

	public void Store(string key, object data)
	{
		ObjectCache cache = MemoryCache.Default;
		cache.Add(key, data, null);
	}

	public void Store(string key, object data, DateTime absoluteExpiration, TimeSpan slidingExpiration)
	{
		ObjectCache cache = MemoryCache.Default;
		var policy = new CacheItemPolicy
		{
			AbsoluteExpiration = absoluteExpiration,
			SlidingExpiration = slidingExpiration
		};

		if (cache.Contains(key))
		{
			cache.Remove(key);
		}
		cache.Add(key, data, policy);
	}

	public T Retrieve<T>(string key)
	{
		ObjectCache cache = MemoryCache.Default;
		return cache.Contains(key) ? (T)cache[key] : default(T);
	}
}

This is a generic class to store, remove and retrieve objects of type T. As the next step you want to call this service from the DefaultProductService class as follows:

public class DefaultProductService : IProductService
{
	private SystemRuntimeCacheStorage _cacheStorage;

	public DefaultProductService()
	{
		_cacheStorage = new SystemRuntimeCacheStorage();
	}

	public Product GetProduct(int productId)
	{
		string key = "product|" + productId;
		Product p = _cacheStorage.Retrieve<Product>(key);
		if (p == null)
		{
        		p = new Product();
			_cacheStorage.Store(key, p);
		}
		return p;
	}
}

We’ve seen a similar example in the previous post where the consuming class constructs its own dependency. This “solution” has the same errors as the one above – it’s only the stacktrace that has changed. You’ll get the same faulty design with a factory as well. However, this was a step towards a loosely coupled solution.

Dependency injection

As you know by now abstractions are the way to go to reach loose coupling. We can factor out the caching logic into an interface:

public interface ICacheStorage
{
	void Remove(string key);
	void Store(string key, object data);
	void Store(string key, object data, DateTime absoluteExpiration, TimeSpan slidingExpiration);
	T Retrieve<T>(string key);
}

Then using constructor injection we can inject the caching mechanism as follows:

public class DefaultProductService : IProductService
{
	private readonly ICacheStorage _cacheStorage;

	public DefaultProductService(ICacheStorage cacheStorage)
	{
		_cacheStorage = cacheStorage;
	}

	public Product GetProduct(int productId)
	{
		string key = "product|" + productId;
		Product p = _cacheStorage.Retrieve<Product>(key);
		if (p == null)
		{
			p = new Product();
			_cacheStorage.Store(key, p);
		}
		return p;
	}
}

Now we can inject any type of concrete caching solution which implements the ICacheStorage interface. As far as tests are concerned you can inject an empty caching solution using the Null object pattern so that the test can concentrate on the true logic of the GetProduct method.

This is certainly a loosely coupled solution but you may need to inject similar interfaces to a potentially large number of services:

public ProductService(ICacheStorage cacheStorage, ILoggingService loggingService, IPerformanceService performanceService)
public CustomerService(ICacheStorage cacheStorage, ILoggingService loggingService, IPerformanceService performanceService)
public OrderService(ICacheStorage cacheStorage, ILoggingService loggingService, IPerformanceService performanceService)

These services will permeate your class structure. Also, you may create a base service for all services like this:

public ServiceBase(ICacheStorage cacheStorage, ILoggingService loggingService, IPerformanceService performanceService)

If all services must inherit this base class then they will start their lives with 3 abstract dependencies that they may not even need. Also, these dependencies don’t represent the true purpose of the services, they are only “sidekicks”.

Ambient context

For a discussion on this type of DI and when and why (not) to use it consult this post.

Interception using the Decorator pattern

The Decorator design pattern can be used as a do-it-yourself interception. The product service class can be reduced to its true purpose:

public class DefaultProductService : IProductService
	{		
		public Product GetProduct(int productId)
		{
			return new Product();
		}
	}

A cached product service might look as follows:

public class CachedProductService : IProductService
{
	private readonly IProductService _innerProductService;
	private readonly ICacheStorage _cacheStorage;

	public CachedProductService(IProductService innerProductService, ICacheStorage cacheStorage)
	{
		if (innerProductService == null) throw new ArgumentNullException("ProductService");
		if (cacheStorage == null) throw new ArgumentNullException("CacheStorage");
		_cacheStorage = cacheStorage;
		_innerProductService = innerProductService;
	}

	public Product GetProduct(int productId)
	{
		string key = "Product|" + productId;
		Product p = _cacheStorage.Retrieve<Product>(key);
		if (p == null)
		{
			p = _innerProductService.GetProduct(productId);
			_cacheStorage.Store(key, p);
		}

		return p;
	}
}

The cached product service itself implements IProductService and accepts another IProductService in its constructor. The injected product service will be used to retrieve the product in case the injected cache service cannot find it.

The consumer can actively use the cached implementation of the IProductService in place of the DefaultProductService class to deliberately call for caching. Here the call to retrieve a product is intercepted by caching. The cached service can concentrate on its task using the injected ICacheStorage object and delegates the actual product retrieval to the injected IProductService class.

You can imagine that it’s possible to write a logging decorator, a performance decorator etc., i.e. a decorator for any type of cross-cutting concern. You can even decorate the decorator to include logging AND caching. Here you see several applications of SOLID. You keep the product service clean so that it adheres to the Single Responsibility Principle. You extend its functionality through the cached product service decorator which is an application of the Open-Closed principle. And obviously injecting the dependencies through abstractions is an example of the Dependency Inversion Principle.

The Decorator is a well-tested pattern to implement interception in a highly flexible object-oriented way. You can implement a lot of decorators for different purposes and you will adhere to SOLID pretty well. However, imagine that in a large business application with hundreds of domains and hundreds of services you may potentially have to write hundreds of decorators. As each decorator executes one thing only to adhere to SRP you may need to implement 3-4 decorators for each service.

That’s a lot of code to write… This is actually a practical limitation of solely using this pattern in a large application to achieve interception: it’s extremely repetitive and time consuming.

Aspect oriented programming (AOP)

The idea behind AOP is strongly related to attributes in .NET. An example of an attribute in .NET is the following:

[PrincipalPermission(SecurityAction.Demand, Role = "Administrator")]
protected void Page_Load(object sender, EventArgs e)
{
}

This is also an example of interception. The PrincipalPermission attribute checks the role of the current principal before the decorated method can continue. In this case the ASP.NET page won’t load unless the principal has the Administrator role. I.e. the call to Page_Load is intercepted by this Security attribute.

The decorator pattern we saw above is an example of imperative coding. The attributes are an example of declarative interception. Applying attributes to declare aspects is a common technique in AOP. Imagine that instead of writing all those decorators by hand you could simply decorate your objects as follows:

[Cached]
[Logged]
[PerformanceChecked]
public class DefaultProductService : IProductService
{		
	public Product GetProduct(int productId)
	{
		return new Product();
	}
}

It looks attractive, right? Well, let’s see.

The PrincipalPermission attribute is special as it’s built into the .NET base class library (BCL) along with some other attributes. .NET understands this attribute and knows how to act upon it. However, there are no built-in attributes for caching and other cross-cutting concerns. So you’d need to implement your own aspects. That’s not too difficult; your custom attribute will need to derive from the System.Attribute base class. You can then decorate your classes with your custom attribute but .NET won’t understand how to act upon it. The code behind your implemented attribute won’t run just like that.

There are commercial products, like PostSharp, that enable you to write attributes that are acted upon. PostSharp carries out its job by modifying your code in the post-compilation step. The “normal” compilation runs first, e.g. by csc.exe and then PostSharp adds its post-compilation step by taking the code behind your custom attribute(s) and injecting it into the code compiled by csc.exe in the correct places.

This sounds enticing. At least it sounded to me like heaven when we tested AOP with PostSharp: we wanted to measure the execution time and save several values about the caller of some very important methods of a service. So we implemented our custom attributes and very extremely proud of ourselves. Well, until someone else on the team started using PostSharp in his own assembly. When I referenced his project in mine I suddenly kept getting these funny notices that I have to activate my PostSharp account… So what’s wrong with those aspects?

  • The code you write will be different from what will be executed as new code will be injected into the compiled one in the post-compilation step. This may be tricky in a debugging session
  • The vendors will be happy to provide helper tools for debugging which may or may not be included in the base price and push you towards an anti-pattern where you depend on certain external vendors – also a form of tight coupling
  • All attributes must have default parameterless constructors – it’s not easy to consume dependencies from within an attribute. Your best bet is using ambient context – or abandon DI and go with default implementations of the dependencies
  • It can be difficult to fine-grain the rules when to apply an aspect. You may want to go with a convention-based applicability such as “apply the aspect on all objects whose name ends with ‘_log'”
  • The aspect itself is not an abstraction; it’s not straightforward to inject different implementations of an aspect – therefore if you decide to go with the System.Runtime.Cache in your attribute implementation then you cannot change your mind afterwards. You cannot implement a factory or any other mechanism to inject a certain aspect in place of some abstract aspect as there’s no such thing

This last point is probably the most serious one. It pulls you towards the dreaded tight-coupling scenario where you cannot easily redistribute a class or a module due to the concrete dependency introduced by an aspect. If you consume such an external library, like in the example I gave you, then you’re stuck with one implementation – and you better make sure you have access to the correct credentials to use that unwanted dependency…

Dynamic interception with a DI container

We briefly mentioned DI containers, or IoC containers in this series. You may be familiar with some of them, such as StructureMap and CastleWindsor. I won’t get into any details regarding those tools. There are numerous tutorials available on the net to get you started. As you get more and more exposed to SOLID in your projects then eventually you’ll most likely become familiar with at least one of them.

Dynamic interception makes use of the ability of .NET to dynamically emit types. Some DI containers enable you to automate the generation of decorators to be emitted straight into a running process.

This approach is fully object-oriented and helps you avoid the shortcomings of AOP attributes listed above. You can register your own decorators with the IoC container, you don’t need to rely on a default one.

If you are new to DI containers then make sure you understand the basics before you go down the dynamic interception route. I won’t show you any code here on how to implement this technique as it depends on the type of IoC container of your choosing. The key steps as far as CastleWindsor is concerned are as follows:

  • Implement the IInterceptor interface for your decorator
  • Register the interceptor with the container
  • Activate the interceptor by implementing the IModelInterceptorsSelector interface – this is the step where you declare when and where the interceptors will be invoked
  • Register the class that implements the IModelInterceptorsSelector interface with the container

Carefully following these steps will ensure that you can implement dynamic interception without the need for attributes. Note that not all IoC containers come with the feature of dynamic interception.

Conclusions

In this mini-series on DI within the series about SOLID I hope to have explained the basics of the Dependency Inversion Principle. This last constituent of SOLID is probably the one that has caused the most controversy and misunderstanding of the 5. Ask 10 developers on the purposes of DIP and you’ll get 11 different answers. You may absolutely have come across ideas in these posts that you disagree with – feel free to comment in that case.

However, I think there are several myths and misunderstandings about DI and DIP that were successfully dismissed:

  • DI is the same as IoC containers: no, IoC containers can automate DI but you can by any means apply DI in your code without a tool like that
  • DI can be solved with factories: look at the post on DI anti-patterns and you’ll laugh at this idea
  • DI requires an IoC containers: see the first point, this is absolutely false
  • DI is only necessary if you want to enable unit testing: no, DI has several advantages as we saw, effective unit testing being only one of them
  • Interception is best done with AOP: no, see above
  • Using an IoC container will automatically result in DI: no, you have to prepare your code according to the DI patterns otherwise an IoC container will have nothing to inject

View the list of posts on Architecture and Patterns here.

SOLID design principles in .NET: the Dependency Inversion Principle Part 3, DI anti-patterns

In the previous post we discussed the various techniques how to implement Dependency Injection. Now it’s time to show how NOT to do DI. Therefore we’ll look at a couple of anti-patterns in this post.

The main source in the series on Dependency Injection is based on the work of Mark Seemann and his great book on DI.

Lack of DI

The most obvious DI anti-patterns is the total absence of it where the class controls it dependencies. It is the most common anti-pattern in DI to see code like this:

public class ProductService
{
	private ProductRepository _productRepository;

	public ProductService()
	{
		_productRepository = new ProductRepository();
	}
}

Here the consumer class, i.e. ProductService, creates an instance of the ProductRepository class with the ‘new’ keyword. Thereby it directly controls the lifetime of the dependency. There’s no attempt to introduce an abstraction and the client has no way of introducing another type – implementation – for the dependency.

.NET languages, and certainly other similar platforms as well, make this extremely easy for the programmer. There is no automatic SOLID checking in Visual Studio, and why would there be such a mechanism? We want to give as much freedom to the programmer as possible, so they can pick – or even mix – C#, VB, F#, C++ etc., write in an object-oriented way or follow some other style, so there’s a high degree of control given to them within the framework. So it feels natural to new up objects as much as we like: if I need something I’ll need to go and get it. If the ProductService needs a product repository then it will need to fetch one. So even experienced programmers who know SOLID and DI inside out can fall into this trap from time to time, simply because it’s easy and programming against abstractions means more work and a higher degree of complexity.

The first step towards salvation may be to declare the private field as an abstract type and mark it as readonly:

public class ProductService
{
	private readonly IProductRepository _productRepository;

	public ProductService()
	{
		_productRepository = new ProductRepository();
	}
}

However, not much is gained here yet, as at runtime _productRepository will always be a new ProductRepository.

A common, but very wrong way of trying to resolve the dependency is by using some Factory. Factories are an extremely popular pattern and they seem to be the solution to just about anything – besides copy/paste of course. I’m half expecting Bruce Willis to save the world in Die Hard 27 by applying the static factory pattern. So no wonder people are trying to solve DI with it too. You can see from the post on factories that they come in 3 forms: abstract, static and concrete.

The “solution” with the concrete factory may look like this:

public class ProductRepositoryFactory
{
	public ProductRepository Create()
	{
		return new ProductRepository();
	}
}
public ProductService()
{
	ProductRepositoryFactory factory = new ProductRepositoryFactory();
	_productRepository = factory.Create();
}

Great, we’re now depending directly on ProductRepositoryFactory and ProductRepository is still hard-coded within the factory. So instead of just one hard dependency we now have two, well done!

What about a static factory?

public class ProductRepositoryFactory
{
	public static ProductRepository Create()
	{
		return new ProductRepository();
	}
}
public ProductService()
{
	_productRepository = ProductRepositoryFactory.Create();
}

We’ve got rid of the ‘new’, yaaay! Well, no, if you recall from the introduction using static methods still creates a hard dependency, so ProductService still depends directly on ProductRepositoryFactory and indirectly on ProductRepository.

To make matters worse the static factory can be misused to produce a sense of freedom to the client to control the type of dependency as follows:

public class ProductRepositoryFactory
{
	public static IProductRepository Create(string repositoryTypeDescription)
	{
		switch (repositoryTypeDescription)
		{
			case "default":
				return new ProductRepository();
			case "test":
				return new TestProductRepository();
			default:
				throw new NotImplementedException();
		}
	}
}
public ProductService()
{
	_productRepository = ProductRepositoryFactory.Create("default");
}

Oh, brother, this is a real mess. ProductService still depends on the ProductRespositoryFactory class, so we haven’t eliminated that. It is now indirectly dependent on the two concrete repo types returned by factory. Also, we now have magic strings flying around. If we ever introduce a third type of repository then we’ll need to revisit the factory and inform all actors that there’s a new magic string. This model is very difficult to extend. The ability to configure in code, or possibly in a config file, gives a false sense of security to the developer.

You can create a mock Product repository for a unit test scenario, extend the switch-case statement in the factory and maybe introduce a new magic string “mock” only for testing purposes. Then you can put “mock” in the Create method, recompile and run your test just for unit testing. Then you forget to put it back to “sql” or whatever and deploy the solution… Realising this you may want to overload the ProductService constructor like this:

public ProductService(string productRepoDescription)
{
	_productRepository = ProductRepositoryFactory.Create(productRepoDescription);
}

That only moves the magic string problem up the stacktrace but does nothing to solve the dependency problems outlined above.

Let’s look at an abstract factory:

public interface IProductRepositoryFactory
{
	IProductRepository Create(string repoDescription);
}

ProductRepositoryFactory can implement this interface:

public class ProductRepositoryFactory : IProductRepositoryFactory
{
	public IProductRepository Create(string repositoryTypeDescription)
	{
		switch (repositoryTypeDescription)
		{
			case "default":
				return new ProductRepository();
			case "test":
				return new TestProductRepository();
			default:
				throw new NotImplementedException();
		}
	}
}

You can use it from ProductService as follows:

private IProductRepositoryFactory _productRepositoryFactory;
private IProductRepository _productRepository;

public ProductService(string productRepoDescription)
{
	_productRepositoryFactory = new ProductRepositoryFactory();
	_productRepository = _productRepositoryFactory.Create(productRepoDescription);
}

We need to new up a ProductRepositoryFactory, so we’re back at square one. However, abstract factory is still the least harmful of the factory patterns when trying to solve DI as we can refactor this code in the following way:

private readonly IProductRepository _productRepository;

public ProductService(string productRepoDescription, IProductRepositoryFactory productRepositoryFactory)
{
	_productRepository = productRepositoryFactory.Create(productRepoDescription);
}

This is not THAT bad. We can provide any type of factory now but we still need to provide a magic string. A way of getting rid of that string would be to create specialised methods within the factory as follows:

public interface IProductRepositoryFactory
{
	IProductRepository Create(string repoDescription);
	IProductRepository CreateTestRepository();
	IProductRepository CreateSqlRepository();
	IProductRepository CreateMongoDbRepository();
}

…with ProductService using it like this:

private readonly IProductRepository _productRepository;

public ProductService(IProductRepositoryFactory productRepositoryFactory)
{
	_productRepository = productRepositoryFactory.CreateMongoDbRepository();
}

This is starting to look like proper DI. We can inject our own version of the factory and then pick the method that returns the necessary repository type. However, this is a false positive impression again. The ProductService still controls the type of repository returned by the factory. If we wanted to test the SQL repo then we have to revisit the product service – and all other services that need a repository – and select CreateSqlRepository() instead. Same goes for unit testing. You can certainly create a mock repository factory but you’ll need to make sure that the mock implementation returns mock objects for all repository types the factory returns. That breaks ISP in SOLID.

No, even in the above case the caller cannot control type of IProductRepository used within ProductRepository. You can certainly control the concrete implementation of IProductRepositoryFactory, but that’s not enough.

Conclusion: factories are great for purposes other than DI. Use one of the strategies outlined in the previous post.

Lack of DI creates tightly coupled classes where one cannot exist without the other. You cannot redistribute the ProductService class without the concrete ProductRepository so it diminishes re-usability.

Overloaded constructors

Consider the following code:

private readonly IProductRepository _productRepository;

public ProductService() : this(new ProductRepository())
{}

public ProductService(IProductRepository productRepository)
{
        _productRepository = productRepository;
}

It’s great that we have can inject an IProductRepository but what’s the default constructor doing there? It simply calls the overloaded one with a concrete implementation of the repository interface. There you are, we’ve just introduced a completely unnecessary coupling. Matters get worse if the default implementation comes from an external source such as a factory seen above:

private readonly IProductRepository _productRepository;

public ProductService() : this(new ProductRepositoryFactory().Create("sql"))
{}

public ProductService(IProductRepository productRepository)
{
	_productRepository = productRepository;
}

By now you know why factories are not suitable for solving DI so I won’t repeat myself. Even if clients always call the overloaded constructor the class still cannot exist without either the ProductRepository or the ProductRepositoryFactory class.

The solution is easy: get rid of the default constructor and force clients to provide their own implementations.

Service locator

I’ve already written a post on this available here, so I won’t repeat the whole post. In short: a Service Locator resembles a proper IoC container such as StructureMap but it introduces easily avoidable couplings between objects.

Conclusion

We’ve discussed some of the ways how not to do DI. There may certainly be more of those but these are probably the most frequent ones. The most important variant to get rid of is the lack of DI which is exacerbated by the use of factories. That’s also the easiest to spot – look for the ‘new’ keyword in conjunction with dependencies.

The use of static method and properties can also be indicators of DIP violation:

DateTime.Now.ToString();
DataAccess.SaveCustomer(customer);
ProductRepositoryFactory.Create("sql");

We’ve seen especially in the case of factories that static methods and factories only place the dependencies one step down the execution ladder. Static methods are acceptable if they don’t themselves have concrete dependencies but only use the parameters already used by the object that’s calling the static method. However, if those static methods new up other dependencies which in turn may instantiate their own dependencies then that will quickly become a tightly coupled nightmare.

View the list of posts on Architecture and Patterns here.

SOLID design principles in .NET: the Dependency Inversion Principle Part 2, DI patterns

In the previous post we went through the basics of DIP and DI. We’ll continue the discussion with the following questions: how to implement DI?

The main source in the series on Dependency Injection is based on the work of Mark Seemann and his great book on DI.

Flavours of DI

I hinted at the different forms of DI in the previous post. By far the most common form is called Constructor Injection:

public ProductService(IProductRepository productRepository)
{
	_productRepository = productRepository;
}

Constructor injection is the perfect way to ensure that the necessary dependency is always available to the class. We force the clients to supply some kind of implementation of the interface. All you need is a public constructor that accepts the dependency as a parameter. In the constructor we save the incoming concrete class for later use, i.e. assign to a private variable.

We can introduce a second level of security by introducing a guard clause:

public ProductService(IProductRepository productRepository)
{
       if (productRepository == null) throw new ArgumentNullException("ProductRepo");
	_productRepository = productRepository;
}

It is good practice to mark the private field readonly, in this case the _productRepository, as it guarantees that once the initialisation logic of the constructor has executed it cannot be modified by any other code:

private readonly IProductRepository _productRepository;

This is not required for DI to work but it protects you against mistakes such as setting the value to null someplace else in your code.

Constructor injection is a good way to document your class to the clients. The clients will see that ProductService will need an IProductRepository to perform its job. There’s no attempt to hide this fact.

When the constructor is finished then the object is guaranteed to have a valid dependency, i.e. the object is in a consistent state. The following method will not choke on a null value where _productRepository is called:

public IEnumerable<Product> GetProducts()
{
	IEnumerable<Product> productsFromDataStore = _productRepository.FindAll();	
	return productsFromDataStore;
}

We don’t need to test for null within the GetProducts method as we know it is guaranteed to be in a consistent state.

Constructor injection should be your default DI technique in case your class has a dependency and no reasonable local defaults exist. A local default is an acceptable local implementation of an abstract dependency in case none is injected by the client. We’ll talk more about this a bit later. Also, try to avoid overloaded constructors because then you’ll need to rely on those local defaults if an empty constructor is used. In addition, having just one constructor greatly simplifies the usage of automated DI containers, also called IoC containers. If you don’t know what they are, then don’t worry about them for now. They are not a prerequisite for DIP and DI and they cannot magically turn tightly coupled code into a loosely coupled one. Make sure that you first understand how to do DI without such tools.

You can read briefly about them here. In short they are ‘magic’ tools that can initialise dependencies. In the above example you can configure such a container, such as StructureMap to magically inject a MyDefaultProductRepository when it sees that an IProductRepository is needed.

The next DI type in line is called Property injection. Property injection is used when your class has a good local default for a dependency but still want to enable clients to override that default. It is also called Setter injection:

public IProductRepository ProductRepository { get; set; }

In this case you obviously cannot mark the backing field readonly.

This implementation is fragile as by default all object types are set to null so ProductRepository will also be null. You’ll need to extend the property setter as follows:

public IProductRepository ProductRepository 
{
	get
	{
		return _productRepository;
	}
	set
	{
		if (value == null) throw new ArgumentNullException("ProductRepo");
		_productRepository = value;
	}
}

We’re still not done. There’s nothing forcing the client to call this setter so the GetProducts method will throw an exception. At some point we must initialise the dependency, maybe in the constructor:

public ProductService()
{
	_productRepository = new DefaultProductRepository();
}

By now we know that initialising an object with the ‘new’ keyword increases coupling between two objects so whenever possible accept the dependency in form of an abstraction instead.

Alternatively you can take the Lazy Initialisation approach in the property getter:

public IProductRepository ProductRepository 
{
	get
	{
		if (_productRepository == null)
		{
			_productRepository = new ProductRepository();
		}
		return _productRepository;
	}
	set
	{
		if (value == null) throw new ArgumentNullException("ProductRepo");
		_productRepository = value;
	}
}

We can go even further. If you want that the client should only set the dependency once without the possibility to alter it during the object’s lifetime then the following approach can work:

public IProductRepository ProductRepository 
{
	get
	{
		if (_productRepository == null)
		{
			_productRepository = new ProductRepository();
		}
		return _productRepository;
	}
	set
	{
		if (value == null) throw new ArgumentNullException("ProductRepo");
		if (_productRepository != null) throw new InvalidOperationException("You are not allowed to set this dependency more than once.");
		_productRepository = value;
	}
}

BTW this doesn’t mean that from now on you must never again use the new keyword to initialise objects. At some point you’ll HAVE TO use it as you can’t connect the bits and pieces using abstractions only. E.g. this is invalid code:

ProductService ps = new ProductService(new IProductRepository());

No, unless you have some IoC Container in place you’ll need to go with what’s called the poor man’s dependency injection:

ProductService ps = new ProductService(new DefaultProductRepository());

Where DefaultProductRepository implements IProductRepository.

Coming back to Property injection, you can use it whenever there’s a well functioning default implementation of a dependency but you still want to let your users provide their own implementation. In other words the dependency is optional. However, this choice must be a conscious one. As there’s nothing forcing the clients to call the property setter your code shouldn’t complain if the dependency is null when it’s needed. That’s a sign saying that you need to turn to constructor injection instead. In case you don’t really need a local default then the Null Object pattern can come handy. If the local default is part of the .NET base class library then it may be an acceptable approach to use it.

As you see the last version of the property getter-setter is considerably more complex than taking the constructor injection approach. It looks easy at first, just insert a get;set; type of property but you soon notice that it’s a fragile structure.

A third way of doing DI is called method injection. It is used when we want to ensure that we can inject a different implementation every time the dependency is used:

public IEnumerable<Product> GetProducts(IProductDiscountStrategy productDiscount)
{
	IEnumerable<Product> productsFromDataStore = _productRepository.FindAll();
	foreach (Product p in productsFromDataStore)
	{
		p.AdjustPrice(productDiscount);
	}
	return productsFromDataStore;
}

Here we apply a discount strategy on each product in the iteration. The actual strategy may change a lot, it can depend on the season, the loyalty scheme, the weather, the time of the day etc. As usual you can include a guard clause:

public IEnumerable<Product> GetProducts(IProductDiscountStrategy productDiscount)
{
	if (productDiscount == null) throw new ArgumentNullException("Discount strategy");
	IEnumerable<Product> productsFromDataStore = _productRepository.FindAll();
	foreach (Product p in productsFromDataStore)
	{
		p.AdjustPrice(productDiscount);
	}
	return productsFromDataStore;
}

In this approach it’s easy to vary the concrete discount strategy every time we call the GetProducts method. If you had to inject this into the constructor then you’d need to create a new ProductService class every time you want to apply some pricing strategy. In case the method doesn’t use the injected dependency you won’t need a guard clause. This may sound strange at first; why have a dependency in the signature if it is not used in the method body? Occasionally you’re forced to implement an interface where the interface method defines the dependency – more on that in the post about the Interface Segregation Principle.

Patterns related to method injection are Factory and Strategy. Choosing the proper implementation to be injected into the GetProducts method will almost certainly depend on other inputs such as the choices the user makes on the UI. These patterns will help you solve that problem.

An example of method injection from .NET is the Contains extension method from LINQ:

bool IEnumerable<T>.Contains(T object, IEqualityComparer<T> comparer);

You can then provide your own version of the equality comparer.

The last type of DI we’ll discuss is making dependencies available through a static accessor. It is also called injection through the ambient context. It is used when implementing cross-cutting concerns.

What are cross-cutting concerns? Operations that may be performed in many unrelated classes and that are not closely related to those classes. A classic example is logging. You may want to log exceptions, performance data etc. I may want to log the time it takes the GetProducts method to return in the ProductService class. You could inject an ILogger interface to every class that needs logging but it introduces a large amount of pollution across your objects. Also, an ILogger interface attached to a constructor is not truly necessary for the dependent object to perform its real job. Logging is usually not part of the core job of services and repositories.

If you’re a web developer then you must have come across the HttpContext object at some point. It is an application of the ambient context pattern. You can always try and access that object and get hold of the current HTTP context which may or may not be available right there and then by its Current static property. You can construct your own Context object where you retrieve the current context using threads. A time provider context may look as follows:

public abstract class TimeProviderContext
{
	public static TimeProviderContext Current
	{
		get
		{
			TimeProviderContext timeProviderContext = Thread.GetData(Thread.GetNamedDataSlot("TimeProvider")) as TimeProviderContext;
			if (timeProviderContext == null)
			{
				timeProviderContext = TimeProviderContext.DefaultTimeProviderContext;
				Thread.SetData(Thread.GetNamedDataSlot("TimeProvider"), timeProviderContext);
			}
			return timeProviderContext;
		}
		set
		{
			Thread.SetData(Thread.GetNamedDataSlot("TimeProvider"), value);
		}
	}
	public static TimeProviderContext DefaultTimeProviderContext = new DotNetTimeProvider();

	public abstract DateTime GetTime { get; }
}

…where DotNetTimeProvider looks as follows:

public class DotNetTimeProvider : TimeProviderContext
{
	public override DateTime GetTime
	{
		get { return DateTime.Now; }
	}
}

The TimeProviderContext is abstract and has a static Current property to get hold of the current context. That’s the classic setup of the ambient context. Using the Thread object like that will ensure that each thread has its own context. There’s a default implementation which is the standard DateTime class from .NET. It’s important to note that the Current property must be writable so that clients can assign their own time providers by deriving from the TimeProviderContext object. This can be helpful in unit testing where ideally you want to control the time instead of waiting for some specific date. The local default makes sure that the client doesn’t get a null reference exception when calling the Current property.

For simplicity’s sake I only put a single abstract method in this class to get the date but ambient context classes can provide as many properties as you need.

You can then use this context in client classes as follows:

public DateTime TestTime()
{
	return TimeProviderContext.Current.GetTime;
}

Ambient context should be used with care. Use it only if you want to make sure that a cross-cutting concern is available anywhere throughout your application. In that case it may be futile to force objects to take on dependencies they may not need now but might do so at some point in the future:

public IProductRepository ProductRepository 
{
	get
	{
		if (_productRepository == null)
		{
			_productRepository = new ProductRepository(TimeProviderContext.Current);
		}
		return _productRepository;
	}
}

…where ProductRepository looks as follows:

public class ProductRepository : IProductRepository
{	

	public ProductRepository(TimeProviderContext timeProviderContext)
	{
		//do nothing with the time provider context right now but it may be needed later
	}

	public IEnumerable<Product> FindAll()
	{
		return new List<Product>();
	}
}

That only increases the coupling between objects and pollutes your object structure.

A disadvantage with the ambient context approach is that the consuming class carries an implicit dependency. In other words it hides from the clients that it needs a time provider in order to perform its job. If you put the TestTime() method shown above in the ProductService class then there’s no way for the client to tell just by looking at the interface that ProductService uses this dependency. Also, callers of the TestTime method will get different results depending on the actual context and it may not be transparent to them why this happens without looking at the source code.

There’s actually a technical term to describe this “openness” that Eric Evans came up with: Intention-revealing interfaces. An API should communicate what it does by its public interface alone. A class using the ambient context does exactly the opposite. Clients may know of the existence of a TimeProviderContext class but will probably not know that it is used in ProductService.

There are cross cutting concerns that only perform some task without returning an answer: logging exceptions and performance data are such cases. If you have that type of scenario then a technique called Interception is something to consider. We’ll look at interception briefly it the blog post after the next one.

Conclusion

Of the four techniques discussed your default choice should always be Constructor Injection in case there’s a dependency within your class. If the dependency varies from operation to operation then Method Injection is good candidate.

Then you can ask the question if the dependency represents a cross-cutting concern. If not and a good local default exists then you can go down the Property Injection path. Otherwise if you need some return value from the cross-cutting concern dependency and you have a good local default in case Context.Current is null then Ambient Context can help. Else if this dependency only has void methods then take a look at Interception.

When in doubt, especially if you are trying to pick a strategy between Constructor Injection and another variant then pick Constructor injection. Things can never go fatally wrong with that option.

View the list of posts on Architecture and Patterns here.

SOLID design principles in .NET: the Dependency Inversion Principle and the Dependency Injection pattern

Introduction

The Dependency Inversion Principle (DIP) helps to decouple your code by ensuring that you depend on abstractions rather than concrete implementations. Dependency Injection (DI) is an implementation of this principle. In fact DI and DIP are often used to mean the same thing. A key feature of DIP is programming to abstractions so that consuming classes can depend on those abstractions rather than low-level implementations. DI is the act of supplying all classes that a service needs rather than letting the service obtain its concrete dependencies. The term Dependency Injection may first sound like some very advanced technology but in reality there are absolutely no complex techniques behind it. As long as you understand abstractions and constructors and methods that can accept parameters you’ll understand DI as well.

Another related term is Inversion of Control, IoC. IoC is an older term than DI. Originally it meant a programming style where a framework or runtime controlled the programme flow. Sticking to this definition software that is developed with .NET uses IoC – in this case .NET is the controlling framework. You hook up to its events, lifetime management etc. You are in control of your methods and references but .NET provides the ultimate glue. Nowadays we’re so used to working with frameworks that we don’t care – we’re actually happy that we don’t need to worry about tedious infrastructure stuff. With time IoC drifted away to mean Inversion of Control Containers which are mechanisms that control dependencies. Martin Fowler was the one who came up with the term Dependency Injection to mean this particular flavour of IoC. Thus, DI is still the correct term to describe the control over dependencies although people often use IoC instead.

DIP is a large topic so it will span several posts to discuss it thoroughly. However, one important conclusion up front is the following:

The frequency of the ‘new’ keyword in your code is a rough estimate of the degree of coupling in your object structure.

A side note: in the demo I’ll concentrate on interfaces but DI works equally well with abstract classes.

The main source in the series on Dependency Injection is based on the work of Mark Seemann and his great book on DI.

What are dependencies?

Dependencies can come in different forms.

A framework dependency is your choice of the development framework, such as .NET. You as a .NET developer are probably comfortable with that dependency as it’s unlikely to change during the product’s lifetime. Most often if you need the product to run on a different framework then it will be rewritten for that platform in a different language without discarding the original product. As this dependency is very unlikely to change and it’s a very high level dependency we don’t worry about it in this context.

Third party libraries introduce a lower level dependency that may well change over time. If a class depends on an external dll then that class may be difficult to test as we need that library to be in a consistent state when testing. However, some of those dependencies may never change. E.g. if I want to communicate with the Amazon cloud in code then it’s best to download and reference the Amazon .NET SDK and use that for entire lifetime of the product. It’s unlikely that I will write my own SDK to communicate with the Amazon web services.

Databases store your data and they can come in many different forms: SQL Server, MySQL, MongoDb, RavenDb, Oracle etc. You may think that an application will never change its storage mechanism, but you’ll better be prepared and abstract it away behind a repository as we’ll see in the demo.

Some other less obvious dependencies include the File System, Emails, Web services and other networking technologies.

System resources such as the Clock to get the current time. You may think that’s unnecessary to abstract that away. After all, why would you ever write your own time provider if the System Clock is available? Think of unit testing a method that depends on time: a price discount is given between 5pm and 6pm on every Friday. How would you unit test that logic? Do you really wait until 5pm on a Friday and hope that you can make the test pass before 6pm? That’s not too clever, as your unit test can only run during that time. So there’s a valid point in abstracting away system resources as well.

Configuration in general, such as the app settings you read from the config file.

The new keyword, as hinted at in the introduction, generally points to tighter coupling and an introduction of an extra dependency. As soon as you write var o = new MyObject() in your class MyClass then MyClass will be closely dependent on MyObject(). If MyObject() changes its behaviour then you have to be prepared for changes and unexpected behaviour in MyClass as well. Using static methods is no way out as your code will depend on the object where the static method is stored, such as MyFactory.GetObject(). You haven’t newed up a MyFactory object but your code is still dependent on it.

Depending on threading-related objects such as Thread or Task can make your methods difficult to test as well. If there’s a call to Thread.Sleep then even your unit test will need to wait.

Anytime you introduce a new library reference you take on an extra dependency. If you have a 4 layers in your solution, a UI, Services, Domains and Repository then you can glue them together by referencing them in Visual Studio: UI uses Services, Services use the Repo etc. The degree of coupling is closely related to how painful it is to replace those layers with new ones. Do you have to sit for days in front of your computer trying to reconnect all the broken links or does it go relatively fast as all you need to do is inject a different implementation of an abstraction?

Getting random numbers using the Random object also introduces an extra dependency that’s hard to test. If your code depends on random numbers then you may have to run the unit test many times before you get to test all branches. Instead, you can provide a different implementation of generating random numbers where you control the outcome of this mechanism so that you can easily test your code.

I’ve provided a hint on how to abstract away built-in .NET objects in your code at the end of this post.

Demo

In the demo we’ll use a simple Product domain whose price can be adjusted using a discount strategy. The Products will be retrieved using a ProductRepository. A ProductService class will depend on ProductRepository to communicate with the underlying data store. We’ll first build the classes without DIP in mind and then we’ll refactor the code. We’ll keep all classes to a minimum without any real implementation so that we can concentrate on the issues at hand. Open Visual Studio and create a new console application. Add the following Product domain class:

public class Product
{
	public void AdjustPrice(ProductDiscount productDiscount)
	{
	}
}

…where ProductDiscount looks even more simple:

public class ProductDiscount
{
}

ProductRepository will help us communicate with the data store:

public class ProductRepository
{
	public IEnumerable<Product> FindAll()
	{
		return new List<Product>();
	}
}

We connect the above objects in the ProductService class:

public class ProductService
{
	private ProductDiscount _productDiscount;
	private ProductRepository _productRepository;

	public ProductService()
	{
		_productDiscount = new ProductDiscount();
		_productRepository = new ProductRepository();
	}

	public IEnumerable<Product> GetProducts()
	{
		IEnumerable<Product> productsFromDataStore = _productRepository.FindAll();
		foreach (Product p in productsFromDataStore)
		{
			p.AdjustPrice(_productDiscount);
		}
		return productsFromDataStore;
	}
}

A lot of code is still written like that nowadays. This is the traditional approach in programming: high level modules call low level modules and instantiate their dependencies as they need them. Here ProductService calls ProductRepository, but before it can do that it needs to new one up using the ‘new’ keyword. The client, i.e. the ProductService class must fetch the dependencies it needs in order to carry out its tasks. Two dependencies are created in the constructor with the ‘new’ keyword. This breaks the Single Responsibility Principle as the class is forced to carry out work that’s not really its concern.

The ProductService is thus tightly coupled to those two concrete classes. It is difficult to use different discount strategies: there may be different discounts at Christmas, Halloween, Easter, New Year’s Day etc. Also, there may be different strategies to retrieve the data from the data store such as using an SQL database, a MySql database, a MongoDb database, file storage, memory storage etc. Whenever those strategies change you must update the ProductService class which breaks just about every principle we’ve seen so far in this series on SOLID.

It is also difficult to test the product service in isolation. The test must make sure that the ProductDiscount and ProductRepository objects are in a valid state and perform as they are expected so that the test result does not depend on them. If the ProductService sends an email then even the unit test call must send an email in order for the test to pass. If the emailing service is not available when the test runs then your test will fail regardless of the true business logic of the method under test.

All in all it would be easier if we could provide any kind of strategy to the ProductService class without having to change its implementation. This is where abstractions and DI enters the scene.

As we can have different strategies for price discounts and data store engines we’ll need to introduce abstractions for them:

public interface IProductDiscountStrategy
{
}
public interface IProductRepository
{
	IEnumerable<Product> FindAll();
}

Have the discount and repo classes implement these interfaces:

public class ProductDiscount : IProductDiscountStrategy
{
}
public class ProductRepository : IProductRepository
{
	public IEnumerable<Product> FindAll()
	{
		return new List<Product>();
	}
}

When we program against abstractions like that then we introduce a seam into the application. It comes from seams on cloths where they can be sewn together. Think of the teeth – or whatever they are called – on LEGO building blocks. You can mix and match those building blocks pretty much as you like due to the standard seams they have. In fact LEGO applied DIP and DI pretty well in their business idea.

Let’s update the ProductService class step by step. The first step is to change the type of the private fields:

private IProductDiscountStrategy _productDiscount;
private IProductRepository _productRepository;

You’ll see that the AdjustPrice method of Product now breaks so we’ll update it too:

public void AdjustPrice(IProductDiscountStrategy productDiscount)
{
}

Now the Product class can accept any type of product discount so we’re on the right track. See that the AdjustPrice accepts a parameter of an abstract type? We’ll look at the different flavours of DI later but that’s actually an application of the pattern called method injection. We inject the dependency through a method parameter. We’ll employ constructor injection to remove the hard dependency on the ProductRepository class within ProductService:

public ProductService(IProductRepository productRepository)
{
	_productDiscount = new ProductDiscount();
	_productRepository = productRepository;
}

Here’s the final version of the ProductService class:

public class ProductService
{
	private IProductRepository _productRepository;

	public ProductService(IProductRepository productRepository)
	{
		_productRepository = productRepository;
	}

	public IEnumerable<Product> GetProducts(IProductDiscountStrategy productDiscount)
	{
		IEnumerable<Product> productsFromDataStore = _productRepository.FindAll();
		foreach (Product p in productsFromDataStore)
		{
			p.AdjustPrice(productDiscount);
		}
		return productsFromDataStore;
	}
}

Now clients of ProductService, possibly a ProductController in an MVC app, will need to provide these dependencies so that the ProductService class can concentrate on its job rather than having to new up dependencies. Obtaining the correct pricing and data store strategy should not be the responsibility of the ProductService. This relates well to the Open-Closed Principle in that you can create new pricing strategies without having to update the ProductService class.

It’s important to note that the ProductService class is now honest and transparent. It is honest about its needs and doesn’t try to hide the external objects it requires in order to fulfil its job, i.e. its dependencies are explicit. Clients using the ProductService class will know that it requires a discount strategy and a product repository. There are no hidden side effects and unexpected results.

The opposite case is a class having implicit dependencies such as the first version of the ProductService class. It’s not obvious for the caller that ProductService will use external libraries and it does not have any control whatsoever over them. In the best case if you have access to the code then you can inspect it and maybe even refactor it. The first version of ProductService tells the client that it suffices to simply create a new ProductService object and then it will be able to fetch the products. However, what do we do if the database is not present? Or if the prices are not correct due to the wrong discount strategy? Then comes the part where ProductService says ‘oh, sorry, I need database access before I can do anything, didn’t you know that…?”.

Imagine that you get a new job as a programmer. Normally all ‘dependencies’ that you need for your job are provided for you: a desk, a computer, the programming software etc. Now think how this would work without DI: you’ll have to buy a desk, get a computer within some specified price range, install the software yourself etc. That is the opposite of DI and that is how ProduceService worked before the refactoring.

A related pattern to achieve DI is the Adapter pattern. It provides a simple mechanism to abstract away dependencies that you have no control over, such as the built-in .NET classes. E.g. if your class sends emails then your default choice could be to use the built-in .NET emailing objects, such as MailMessage and SmtpClient. You cannot easily abstract away that dependency as you have no access to the source code, you cannot make it implement a custom interface, such as IEmailingService. The Adapter patter will help you solve that problem. Also, unit testing code that sends emails is cumbersome as even the test call will need to send out an email. Ideally we don’t test those external services so instead inject a mock object in place of the real one. How that is done? Start here.

View the list of posts on Architecture and Patterns here.

SOLID design principles in .NET: the Interface Segregation Principle

Introduction

The Interface Segregation Principle (ISP) states that clients should not be forced to depend on interfaces they do not use. ISP is about breaking down big fat master-interfaces to more specialised and cohesive ones that group related functionality. Imagine that your class needs some functionality from an interface but not all. If you have no direct access to that interface then all you can do is to implement the relevant bits and ignore the methods that are not relevant for your class.

The opposite is that an interface grows to allow for more functionality where there’s a chance that some methods in the interface are not related, e.g. CalculateArea() and DoTheShopping(). All implementing classes will of course need to implement all methods in the interface where the unnecessary ones may only have a throw new NotImplementedException as their method body.

For the caller this won’t be obvious:

Person.DoTheShopping();
Neighbour.DoTheShopping();

Triangle.CalculateArea();
Square.CalculateArea();

These look perfectly reasonable, right? However, if the interface they implement looks like this…:

public interface IMasterInterface
{
    void DoTheShopping();
    double CalculateArea();
}

…then the client may as well make the following method calls:

Person.CalculateArea();
Triangle.DoTheShopping();

…where the true implementations will probably throw a NotImplementedException or will have an empty body or return some default value such as 0 at best. Also, if you loop through an enumeration of IMasterInterface objects then the caller expects to be able to simply call the CalculateArea() on every object in the list adhering to the LSP principle of the previous post. Then they will see exceptions thrown or inexplicable 0’s returned where the method does not apply.

The above example is probably too extreme, nobody would do anything like that in real code I hope. However, there are more subtle differences between two ‘almost related’ objects than between a Person and a Triangle as we’ll see in the demo.

Often such master interfaces are a result of a growing domain where more and more properties and behaviour are assigned to the domain objects without giving much thought to the true hierarchy between classes. Adhering to ISP will often result in small interfaces with only 1-3 methods that concentrate on some very specific tasks. This helps you create subclasses that only implement those interfaces that are meaningful to them.

Big fat interfaces – and abstract base classes for that matter – therefore introduce unnecessary dependencies. Unnecessary dependencies in turn reduce the cohesion, flexibility and maintainability of your classes and increase the coupling between dependencies.

Demo

We’ll simulate a movie rental where movies can be rented in two formats: DVD and BluRay. The domain expert correctly recognises that these are indeed related products that both can implement the IProduct interface. Open Visual Studio, create a new Console app and add the following interface:

public interface IProduct
{
	decimal Price { get; set; }
	double Weight { get; set; }
	int Stock { get; set; }
        int AgeLimit { get; set; }
	int RunningTime { get; set; }
}

Here I take the interface approach but it’s perfectly reasonable to follow an approach based on an abstract base class instead, such as ProductBase.

The following two classes implement the interface:

public class DVD : IProduct
{
	public decimal Price { get; set; }
	public double Weight { get; set; }
	public int Stock { get; set; }
        int AgeLimit { get; set; }
	public int RunningTime { get; set; }
}
public class BluRay : IProduct
{
	public decimal Price { get; set; }
	public double Weight { get; set; }
	public int Stock { get; set; }
        int AgeLimit { get; set; }
	public int RunningTime { get; set; }
}

All is well so far, right? Now management comes along and says that they want to start selling T-Shirts with movie stars printed on them so the new product is more or less related to the main business. The programmer first thinks it’s probably just OK to implement the IProduct interface again:

public class TShirt : IProduct
{
	public decimal Price { get; set; }
	public double Weight { get; set; }
	public int Stock { get; set; }
        int AgeLimit { get; set; }
	public int RunningTime { get; set; }
}

Price, stock and weight are definitely relevant to the TShirt domain. Age limit? Not so sure… Running time? Definitely not. However, it’s still there and can be set even if it doesn’t make any sense. Also, the programmer may want to extend the TShirt class with the Size property so he adds this property to the IProduct interface. The DVD and BluRay classes will then also need to implement this property, but does it make sense to store the size of a DVD? Well, maybe it does, but it’s not the same thing as the size of a TShirt. The TShirt size may be a string, such as “XL” or an enumeration, e.g. Size.XL, but the size of a DVD is more complex. It is more likely to be a dimension with 3 values: width, length and depth. So the type of the Size property will be different. Setting the type to Object is a quick fix but it’s a horrendous crime against OOP I think.

The solution is to break up the IProduct interface into two smaller ones:

public interface IProduct
{
	decimal Price { get; set; }
	double Weight { get; set; }
	int Stock { get; set; }
}

The IProduct interface still fits the DVD and BluRay objects and it fits the new TShirt interface as well. The RunningTime property is only relevant to movie-related objects:

public interface IMovie
{
	int RunningTime { get; set; }
}

BluRay and DVD implement both interfaces:

public class BluRay : IProduct, IMovie
{
	public decimal Price { get; set; }
	public double Weight { get; set; }
	public int Stock { get; set; }
	public int RunningTime { get; set; }
}
public class DVD : IProduct, IMovie
{
	public decimal Price { get; set; }
	public double Weight { get; set; }
	public int Stock { get; set; }
	public int RunningTime { get; set; }
}

Now you can have a list of IProduct objects and call the Price property on all of them. You won’t have access to the RunningTime property which is a good thing. By default it will be 0 for all TShirt objects so you could probably get away with that in this specific scenario, but it still goes against ISP. As soon as you’re dealing with IMovie objects then the RunningTime property makes perfect sense.

A slightly different solution after breaking out the IMovie interface is that IMovie implements the IProduct interface:

public interface IMovie : IProduct
{
	int RunningTime { get; set; }
}

We can change the implementing objects as follows:

public class TShirt : IProduct
{
	public decimal Price { get; set; }
	public double Weight { get; set; }
	public int Stock { get; set; }
}
public class BluRay : IMovie
{
	public decimal Price { get; set; }
	public double Weight { get; set; }
	public int Stock { get; set; }
	public int RunningTime { get; set; }
}
public class DVD : IMovie
{
	public double Weight { get; set; }
	public int Stock { get; set; }
	public int RunningTime { get; set; }
	public decimal Price { get; set; }
}

So the DVD and BluRay classes are still of IProduct types as well because the IMovie interface implements it.

A real life example

If you’ve worked with ASP.NET then you must have come across the MembershipProvider object in the System.Web.Security namespace. It is used within .NET for built-in membership providers such as SqlMembershipProvider which provides functions to create new users, authenticate your users, lock them out, update their passwords and much more. If the built-in membership types are not suitable for your purposes then you can create your own custom membership mechanism by implementing the MembershipProvider abstraction:

public class CustomMembershipProvider : MembershipProvider

I won’t show the implemented version because it’s too long. MembershipProvider forces you to implement a whole range of methods, e.g.:

public override bool ChangePassword(string username, string oldPassword, string newPassword)
public override bool DeleteUser(string username, bool deleteAllRelatedData)
public override bool EnablePasswordRetrieval
public override int MinRequiredPasswordLength

At the time of writing this post MembershipProvider includes 27 methods and properties for you to implement. It has been criticised due to its size and the fact that if you only need half of the methods then the rest will throw the dreaded NotImplementedException. If you’re building a custom Login control then all you might be interested in is the following method:

public override bool ValidateUser(string username, string password)

At best you can provide some null objects to quietly ignore the unnecessary methods but it may be confusing to the callers that expect a reasonable result from a method.

An alternative solution in cases where you don’t own the code is to follow the Adapter pattern to hide the unnecessary parts in the original abstraction.

View the list of posts on Architecture and Patterns here.

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