You’ve decided to use Domain-Driven Design (DDD), but aren’t sure how to implement it. Maybe you’ve seen it go wrong before and aren’t sure how to prevent that happening again. Maybe you’ve never done it and aren’t sure where to start. This post will show you how to implement a DDD domain layer, including aggregates , value objects, domain commands, and validation, and how to avoid some of the pitfalls I’ve seen. It will not discuss the why of DDD vs other competing patterns; nor, for the sake of brevity, will it discuss the infrastructure or application layers of a DDD app. To demonstrate these concepts in action, I have built a backend for a library using DDD; the most relevant sections will be shown in the post, and the full version can be found on GitHub. The tech stack I used is an ASP.NET Core API written in C# backed by a Mongo DB.
The Aggregate Root
The aggregate root is the base data entity of a data model. This entity will contain multiple properties, which may be base CLR types or value objects. Value objects can be viewed as objects that are owned by the aggregate root. Each object, whether an aggregate root or value object, is responsible for maintaining its state. We will start by defined an abstract aggregate root type with properties all our aggregate roots will have:
public abstract class AggregateRoot
{
public string AuditInfo_CreatedBy { get; private set; } = "Library.Web";
public DateTime AuditInfo_CreatedOn { get; private set; } = DateTime.UtcNow;
public void SetCreatedBy(string createdBy)
{
AuditInfo_CreatedBy = createdBy;
}
}
Next, we will define an implementation of this type containing a couple internal constructors, a number of data properties, and a couple methods for updating the data properties. Looking through the implementation below, you will probably note that my data properties have private setters and methods for setting them. This looks a little strange when you consider that properties allow custom setters, but the reason for this is serialization. When we deserialize an object from our DB, we don’t want to have to go through any validation we might do when setting a property; we just want to read into the property and assume the data has already been validated. When the data changes, we need to validate it, so we make the property setters private and provide public methods to set the data. Another benefit the methods provide is you can pass a domain command to them, instead of just the final expected value of the property; this allows you to provide supplemental information as necessary.
public class User : AggregateRoot
{
/// <summary>
/// Used for deserialization
/// </summary>
[BsonConstructor]
internal User(Guid id, string name, bool isInGoodStanding, List<CheckedOutBook> books)
{
Id = id;
Name = name;
IsInGoodStanding = isInGoodStanding;
this.books = books;
}
/// <summary>
/// Used by the UserFactory; prefer creating instances with that
/// </summary>
internal User(string name)
{
Id = Guid.NewGuid();
Name = name;
IsInGoodStanding = true;
}
public Guid Id { get; private set; }
public string Name { get; private set; }
public bool IsInGoodStanding { get; private set; }
[BsonElement(nameof(Books))]
private readonly List<CheckedOutBook> books = new();
public IReadOnlyCollection<CheckedOutBook> Books => books.AsReadOnly();
public async Task CheckoutBook(CheckoutBookCommand command)
{
// validation happens in any event handler listening for this event
// e.g. Does the library have this book, is it available, etc.
await DomainEvents.Raise(new CheckingOutBook(command));
var checkoutTime = DateTime.UtcNow;
books.Add(new CheckedOutBook(command.BookId, checkoutTime, checkoutTime.Date.AddDays(21)));
DomainEvents.Raise(new CheckedOutBook(command));
}
public async Task ReturnBook(ReturnBookCommand command)
{
// validation happens in any event handler listening for this event
// e.g. Does the user have this book checked out, etc.
await DomainEvents.Raise(new ReturningBook(command));
books.RemoveAll(r => r.BookId == command.BookId);
DomainEvents.Raise(new ReturnedBook(command));
}
}
public class CheckedOutBook
{
public CheckedOutBook(Guid bookId, DateTime checkedOutOn, DateTime returnBy)
{
BookId = bookId;
CheckedOutOn = checkedOutOn;
ReturnBy = returnBy;
}
public Guid BookId { get; private set; }
public DateTime CheckedOutOn { get; private set; }
public DateTime ReturnBy { get; private set; }
}
Having POCOs or dumb objects (objects that aren’t responsible for maintaining their internal state) is often one of the first mistakes people make when doing DDD. They will create a class with public getters and setters and put their logic in a service (I will go over domain services and why you don’t usually want to use them later). The problem with this is that two places might be working with the same object instance at the same time and write data that the other is reading or writing, so the object risks ending up in an inconsistent state. DDD prevents inconsistent state by only allowing the object to set its own state, so if two consecutive changes to the same object would lead to inconsistent state, the object will catch that with its internal validation, instead of relying on the caller to have validated the change.
Domain Commands
Domain commands are how you tell an aggregate to update itself. In the code above, CheckoutBook and ReturnBook are domain commands. It isn’t strictly necessary to create a command type to represent the data being passed; you could have just passed a Guid bookId instead of a command class into the method. However, I like creating a command type because you have a single object to run validation against, and you can validate parameters when creating the command instance. For example, if your domain command requires a certain value be provided, you could validate that it’s not null in the type constructor instead of in the domain command itself. The validation on the type especially helps the logic flow well; you can’t really validate a Guid without additional context; you can validate a ReturnBookCommand type that contains a Guid, and you already have the additional context around what the Guid is.
public class CheckoutBookCommand
{
public Guid BookId { get; }
public Guid UserId { get; }
public CheckoutBookCommand(Guid userId, Guid bookId)
{
if (bookId == Guid.Empty) { throw new ArgumentException($"Argument {nameof(bookId)} cannot be an empty guid", nameof(bookId)); }
if (userId == Guid.Empty) { throw new ArgumentException($"Argument {nameof(userId)} cannot be an empty guid", nameof(userId)); }
BookId = bookId;
UserId = userId;
}
}
Validation
You probably noticed the comments I had in the domain command implementations about validation. Validation is often tricky to get right in DDD because it uses other dependencies, such as a DB. For example, to successfully check out a book, the system has to make sure both the book and user are in the system, that the book is available, that the user is in good standing, etc. To do these, we already pulled the user from the DB to get the user aggregate, so we know the user is in the system. However, we haven’t checked that the book is in the system, so we need to reference a database instance when we do our validation inside the domain command. We can’t inject a DB instance into the aggregate because we don’t resolve aggregates from the IoC container, and even if we could, it’s not the aggregate’s responsibility to connect to the DB. We could new a DB instance up in the command, but that is wrong for reasons outside the scope of this article, in addition to not being the aggregate’s responsibility to talk to the DB (research Dependency Injection and Inversion of Control if you don’t know why). This is where our command system comes into play. Notice the DomainEvents.Raise call. I have that implemented with MediatR, which is a .NET implementation of the mediator pattern; see the link at the end of this article for more detail:
public static class DomainEvents
{
public static Func<IPublisher> Publisher { get; set; }
public static async Task Raise<T>(T args) where T : INotification
{
var mediator = Publisher.Invoke();
await mediator.Publish<T>(args);
}
}
We register IPublisher and our notifications and commands with our IoC container so we can resolve dependencies in our handlers. We then create a method that knows how to resolve an IPublisher instance and assign it to the static Publisher property in our startup. The static Raise method then has all the information it needs to raise the event and wait for the handlers to complete. In this example, I use the FluentValidation library for validation within these handlers. We could put an error handler in our HTTP response pipeline to catch ValidationExceptions and translate them into 400 responses.
public class CheckingOutBook : INotification
{
public CheckoutBookCommand Command { get; }
public CheckingOutBook(CheckoutBookCommand command) => Command = command;
}
public class CheckingOutBookValidationHandler : INotificationHandler<CheckingOutBook>
{
private readonly CheckingOutBookValidator validator;
public CheckingOutBookValidationHandler(CheckingOutBookValidator validator) => this.validator = validator;
public Task Handle(CheckingOutBook @event, CancellationToken cancellationToken)
{
validator.ValidateAndThrow(@event.Command);
return Task.CompletedTask;
}
}
public class CheckingOutBookValidator : AbstractValidator<CheckoutBookCommand>
{
public CheckingOutBookValidator(ILibraryRepository repository)
{
RuleFor(x => x.UserId)
.MustAsync(async (userId, _) =>
{
var user = await repository.GetUserAsync(userId);
return user?.IsInGoodStanding == true;
}).WithMessage("User is not in good standing");
RuleFor(x => x.BookId)
.MustAsync(async (bookId, _) => await repository.GetBookAsync(bookId) is not null)
.WithMessage("Book does not exist")
.DependentRules(() =>
{
RuleFor(x => x.BookId)
.MustAsync(async (bookId, _) => !await repository.IsBookCheckedOut(bookId))
.WithMessage("Book is already checked out");
});
}
}
Creating Entities
At this point you may be wondering how we ensure an aggregate root is valid on initial creation since we can’t await results in a constructor the way we do in our command handlers inside the entity. This is a prime case for the use of factories; we’ll make our constructor internal to reduce the accessibility as much as possible and create a factory that makes any infrastructure calls it needs, calls the constructor, then raises an event with the newly created entity as data that can be used to validate it. This way, we encapsulate all the logic needed to create an event, instead of relying on each place an event is created to perform the logic correctly and ensure the entity is valid.
public class UserFactory
{
public async Task<User> CreateUserAsync(string name)
{
var user = new User(name);
await DomainEvents.Raise(new CreatingUser(user));
return user;
}
}
Domain Services
You are probably wondering at this point why I didn’t simply use a service to perform the checkout book command. For example, I could define the service with a method CheckoutBook(User user, Guid bookId), and perform all the validation inline, instead of importing MediatR and FluentValidation and creating 3 classes to simply validate my user. Then I would inject this service into whatever place calls the domain command and call the service instead of calling the domain command. I could still have my domain command be responsible for updating the entity instance to ensure it isn’t having random values assigned in places. The problem with this is I now have some logic in the service and some in my entity; how do I determine which logic goes where? When multiple devs are working on a project, this becomes very difficult to handle, and people have to figure out where existing logic is and where to put new logic. This issue often leads to duplicated logic, which leads to bugs when one is updated and the other isn’t, among other issues. Additionally, as I mentioned above, because the validation logic occurs outside my entity, I can no longer trust that the entity is in a valid state because I don’t know if the validation was run before the command to update the entity was called. Because DDD implemented correctly only allows the entity to update itself, we can validate data changes once inside the entity just before we update it, instead of hoping the caller remembered to fully validate the changes.
References
- Ardalis (a partner contractor on a project) on GitHub: https://github.com/ardalis/DDD-NoDuplicates
- FluentValidation: https://fluentvalidation.net/
- MediatR: https://github.com/jbogard/MediatR
- Source Code: https://github.com/Hosch250/Library-DDD
Super Development 
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