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.NET developers should be familiar with the standard access modifiers (public, protected, internal, private). However, in loosely coupled code we can regard interface implementations as a fifth access modifier. This concept was originally introduced to me by Udi Dahan the only time I've had the pleasure of meeting him. That was many years ago and while I didn't grok it back then, I've subsequently come to appreciate it quite a lot.

Although I can't take credit for the idea, I've never seen it described, and it really deserves to be.

The basic idea is simple:

If a consumer respects the Liskov Substitution Principle (LSP), the only visible members are those belonging to the interface. Thus, the interface represents a dimension of visibility.

As an example, consider this simple interface from AutoFixture:

public interface ISpecimenContext
{
    object Resolve(object request);
}

A well-behaved consumer can only invoke the Resolve method even though an implementation may have additional public members:

public class SpecimenContext : ISpecimenContext
{
    private readonly ISpecimenBuilder builder;
 
    public SpecimenContext(ISpecimenBuilder builder)
    {
        if (builder == null)
        {
            throw new ArgumentNullException("builder");
        }
 
        this.builder = builder;
    }
 
    public ISpecimenBuilder Builder
    {
        get { return this.builder; }
    }
 
    #region ISpecimenContext Members
 
    public object Resolve(object request)
    {
        return this.Builder.Create(request, this);
    }
 
    #endregion
}

Even though the SpecimenContext class defines the Builder property, as well as a public constructor, any consumer respecting the LSP will only see the Resolve method.

In fact, the Builder property on the SpecimenContext class mostly exists to support unit testing because I sometimes need to assert that a given instance of SpecimenContext contains the expected ISpecimenBuilder. This doesn't break encapsulation since the Builder is exposed as a read-only property, and it more importantly doesn't pollute the API.

To support unit testing (and whichever other clients might be interested in the encapsulated ISpecimenBuilder) we have a public property that follows all framework design guidelines. However, it's essentially an implementation detail, so it's not visible via the ISpecimenContext interface.

When writing loosely coupled code, I've increasingly begun to see the interfaces as the real API. Most other (even public) members are pure implementation details. If the members are public, I still demand that they follow the framework design guidelines, but I don't consider them parts of the API. It's a very important distinction.

The interfaces define the bulk of an application's API. Most other types and members are implementation details.

An important corollary is that constructors are implementation details too, since they can never by part of any interfaces.

In that sense we can regard interfaces as a fifth access modifier - perhaps even the most important one.

Comments

In my previous post I described how to customize a Fixture instance to populate lists with items instead of returning empty lists. While it's pretty easy to do so, the drawback is that you have to do it explicitly for every type you want to influence. In this post I will follow up by describing how to enable some general conventions that simply populates all collections that the Fixture resolves.

This post describes a feature that will be available in AutoFixture 2.1. It's not available in AutoFixture 2.0, but is already available in the code repository. Thus, if you can't wait for AutoFixture 2.1 you can download the source and built it.

Instead of having to create multiple customizations for IEnumerable<int>, IList<int>, List<int>, IEnumerable<string>, IList<string>, etc. you can simply enable these general conventions as easy as this:

var fixture = new Fixture()
    .Customize(new MultipleCustomization());

Notice that enabling conventions for populating sequences and lists with ‘many' items is an optional customization that you must explicitly add.

This feature must be explicitly enabled. There are several reasons for that:

• It would be a breaking change if AutoFixture suddenly started to behave like this by default.
• The MultipleCustomization targets not only concrete types such as List<T> and Collection<T>, but also interfaces such as IEnumerable<T>, IList<T> etc. Thus, if you also use AutoFixture as an Auto-Mocking container, I wanted to provide the ability to define which customization takes precedence.

With that simple customization enabled, all requested IEnumerable<T> are now populated. The following will give us a finite, but populated list of integers:

var integers = 
    fixture.CreateAnonymous<IEnumerable<int>>();

This will give us a populated List<int>:

var list = fixture.CreateAnonymous<List<int>>();

This will give us a populated Collection<int>:

var collection = 
    fixture.CreateAnonymous<Collection<int>>();

As implied above, it also handles common list interfaces, so this gives us a populated IList<T>:

var list = fixture.CreateAnonymous<IList<int>>();

The exact number of ‘many' is as always determined by the Fixture's RepeatCount.

As this code is still (at the time of publishing) in preview, I would love to get feedback on this feature.

How do you get AutoFixture to create populated lists or sequences of items? Recently I seem to have been getting this question a lot, and luckily it's quite easy to answer.

Let's first look at the standard AutoFixture behavior and API.

You can ask AutoFixture to create an anonymous List like this:

var list = fixture.CreateAnonymous<List<int>>();

Seen from AutoFixture's point of view, List<int> is just a class like any other. It has a default constructor, so AutoFixture just uses that and returns an instance. You get back an instance, no exceptions are thrown, but the list is empty. What if you'd rather want a populated list?

There are many ways to go about this. A simple, low-level solution is to populate the list after creation:

fixture.AddManyTo(list);

However, you may instead prefer getting a populated list right away. This is also possible, but before we look at how to get there, I'd like to point out a feature that surprisingly few users notice. You can create many anonymous specimens at once:

var integers = fixture.CreateMany<int>();

Armed with this knowledge, as well as the knowledge of how to map types, we can now create this customization to map IEnumerable<int> to CreateMany<int>:

fixture.Register(() => fixture.CreateMany<int>());

The Register method is really a generic method, but since we have type inference, we don't have to write it out. However, since CreateMany<int>() returns IEnumerable<int>, this is the type we register. Thus, every time we subsequently resolve IEnumerable<int>, we will get back a populated sequence.

Getting back to the original List<int> example, we can now customize it to a populated list like this:

fixture.Register(() =>
    fixture.CreateMany<int>().ToList());

Because the ToList() extension method returns List<T>, this call registers List<int> so that we will get back a populated list of integers every time the fixture resolves List<int>.

What about other collection types that don't have a nice LINQ extension method? Personally, I never use Collection<T>, but if you wanted, you could customize it like this:

fixture.Register(() =>
    new Collection<int>(
        fixture.CreateMany<int>().ToList()));

Since Collection<T> has a constructor overload that take IList<T> we can customize the type to use this specific overload and populate it with ‘many' items.

Finally, we can combine all this to map from collection interfaces to populated lists. As an example, we can map from IList<int> to a populated List<int> like this:

fixture.Register<IList<int>>(() => 
    fixture.CreateMany<int>().ToList());

When we use the Register method to map types we can no longer rely on type inference. Instead, we must explicitly register IList<int> against a delegate that creates a populated List<int>. Because List<int> implements IList<int> this compiles. Whenever this fixture instance resolves IList<int> it will create a populated List<int>.

All of this describes what you can do with the strongly typed API available in AutoFixture 2.0. It's easy and very flexible, but the only important drawback is that it's not general. All of the customizations in this post specifically address lists and sequences of integers, but not lists of any other type. What if you would like to expand this sort of behavior to any List<T>, IEnumerable<T> etc?

Stay tuned, because in the next post I will describe how to do that.

During the last couple of weeks I've been very interested in using a Maybe monad with AutoFixture's Kernel code, but although many examples can be found on the internet, they remain samples. Rinat Abdullin and Zack Owens both posted samples, but I particularly like Mike Hadlow's series about Monads in C# because he also explains how to use LINQ with monads such as the Maybe monad.

As I really wanted a Maybe monad for AutoFixture, I first thought about simply implementing it directly in the AutoFixture source. However, I found it too arbitrary to put such a general purpose programming construct into a specific library such as AutoFixture. My next thought was to create a small open source project just for that single purpose, but then I though about the problem a bit more…

The BCL sort of already has a Maybe monad - you just need to recognize it as such.

What is a Maybe monad really? If you really distill it, it's just a type that either contains a value, or doesn't contain a value. In other words, it's a type that represents a particular range: a set with either zero or one items. That's just a special case of a more general range or collection, and we already have LINQ covering those constructs.

Here it is: the Maybe monad from the BLC (encapsulated in a nice extension method):

public static class LightweightMaybe
{
    public static IEnumerable<T> Maybe<T>(this T value)
    {
        return new[] { value };
    }
}

Obviously, this method returns a Maybe with a value, but we can just as easily represent Nothing with an empty array.

With my ‘new' Maybe monad, I can now write code like this (where request is a System.Object instance):

return (from t in request.Maybe().OfType<Type>()
        let typeArguments = t.GetGenericArguments()
        where typeArguments.Length == 1
        && typeof(IList<>)
            == t.GetGenericTypeDefinition()
        select context.Resolve(typeof(List<>)
            .MakeGenericType(typeArguments)))
        .DefaultIfEmpty(new NoSpecimen(request))
        .SingleOrDefault();

You may think that this looks dense, but before that the code looked like this:

var type = request as Type;
if (type == null)
{
    return new NoSpecimen(request);
}
 
var typeArguments = type.GetGenericArguments();
if (typeArguments.Length != 1)
{
    return new NoSpecimen(request);
}
 
if (typeof(IList<>) != 
    type.GetGenericTypeDefinition())
{
    return new NoSpecimen(request);
}
 
return context.Resolve(typeof(List<>)
    .MakeGenericType(typeArguments));

Notice that in this more traditional approach involving Guard Clauses, I have to construct a new NoSpecimen object in three different places, thus violating the DRY principle. I like not having all those if/return blocks in the code.

Comments

Recently I spent a couple of days with Thomas Jespersen who's working towards a launch of spiir.dk - on Windows Azure. The reason I got to talk to him was to see if I could help with some performance issues he had with Azure Table Storage.

The scenario is really simple: the application needs to load all of a user's bank transactions into memory to enable pretty advanced sorting and filtering. That sounds like a lot, but really isn't more than approximately 200 kB of data retrieved through a single query - so: there are no 1+N problems in play here, but even so it originally took more than two seconds. That's a bit long to wait before you can even start rendering a web page.

By tweaking his partitioning strategy and using parallel queries, Thomas managed to bring down the data retrieval time to approximately one second. Although stress testing indicated that this duration was very stable, even under load, it is still too slow. So we met to see what could be done.

Thomas had done a great job tweaking the query, so I couldn't really suggest some sort of secret API that would make it run significantly faster. Basically, we have to deal with Azure storage being based on REST and that there are a lot of things about run-time behavior we cannot control. Apart from designing a proper partitioning strategy, we can't add indexes to Azure Table Storage.

It was time to take a different approach.

As far as I can tell, Windows Azure is designed to be very scalable. However, just because scalability implies that you can handle an insane amount of work within acceptable time frames, it doesn't mean that you can extrapolate it to mean that under a light load, everything will be lightning fast. That's not the case at all.

Scalability means that performance characteristics remain stable from light to heavy load.

Consequently this means that if performance is adequate under heavy load, it will also be adequate under a light load. Azure Storage is first and foremost designed to be scalable, and as a second priority, as fast as possible.

As Thomas discovered, Azure Table Storage isn't particularly fast.

It may be a masochistic side of me that I'm not otherwise aware of, but I actually appreciate that. It makes us reassess our most basic assumptions.

The data that Thomas needs to read isn't particularly dynamic, so what if we take a snapshot of it? In short, we loaded all of a user's data into memory and serialized it to Azure Blob Storage.

Loading the same data from a binary serialized Blob took only 1/6 of the time it did to load it from Table Storage.

As it turns out, Thomas doesn't even need all the columns from the Table to populate the view, so we could even make the serialized Blob smaller yet.

At this point, however, we now have two representations of the same data: The original data in Table Storage, and a persistent cache in Blob Storage. The remaining challenge is to figure out how to keep these in sync.

This may seem like a hack, but is really represents a paradigm shift. Letting go of ACID opens up a lot of new opportunities.

Actually, I spend most of the next day trying to convince Thomas that CQRS would be the best approach, or that we could at least pick up some of the techniques from asynchronous, messaging based architectures, but that's another story.

The morale here is that on Azure, things may be slower than you are used to, but storage is (relatively) cheap, so denormalization can save you a lot of execution time.

Comments

A week ago I concluded Microsoft Denmark's 2010 .NET Community Christmas Calendar with a challenge about resolving closed types with MEF. As 2011 came around, the deadline ended, so it's now time to pick the winner.

I didn't get a lot of entries, which can be interpreted in at least one (or more) of the following ways:

• The challenge was too difficult
• The challenge wasn't interesting
• The prize wasn't attractive
• People had other things to do during the holidays

Whatever the reason, it made my task of picking a winner that much easier. The best Danish entry came from Daniel Volder Guarnieri who cheated a bit by partially hard-coding the composition of Mayonnaise into the ContainerBuilder. As I wrote in the original challenge, there are many ways to tackle the challenge, and one was to take the unit tests very literally :)

However, honorable mention must go to Boyan Mihaylov who participated just for the honor. He took a more general approach similar to Fluent MEF. This involves implementing a completely new ComposablePartCatalog with associated ComposablePartDefinition and ComposablePart implementations - not a trivial undertaking.

Kudos to Boyan and congratulations to Daniel. My thanks for your submissions, and a happy new year to all my readers!

Comments

For my international reader, a bit of context is in order for this post: Microsoft Denmark sponsors a series of Christmas challenges known as the Microsoft Christmas Calendar. Different bloggers alternate hosting a coding challenge for the day, and Microsoft sponsors the prizes.

Today I have the honor of hosting the last challenge for 2010. Contestants from the Danish .NET community have the opportunity to win a Molecular Gastronomy Starter Kit - if any of my international readers feel like joining in, they are welcome, but (probably) not eligible for the prize.

The challenge #

The Managed Extensibility Framework (MEF) enables us to compose applications by annotating types and members with [Import] and [Export] attributes, but what can you do when you have types without these attributes and you can't add the attributes?

For example, how can we compose Mayonnaise from these three classes?

public sealed class EggYolk { }
 
public sealed class OliveOil { }
 
public sealed class Mayonnaise
{
    private readonly EggYolk eggYolk;
    private readonly OliveOil oil;
 
    public Mayonnaise(EggYolk eggYolk, OliveOil oil)
    {
        if (eggYolk == null)
        {
            throw new ArgumentNullException("eggYolk");
        }
        if (oil == null)
        {
            throw new ArgumentNullException("oil");
        }
 
        this.eggYolk = eggYolk;
        this.oil = oil;
    }
 
    public EggYolk EggYolk
    {
        get { return this.eggYolk; }
    }
 
    public OliveOil Oil
    {
        get { return this.oil; }
    }
}

The challenge is to come up with a good solution to that problem. Here are the formal rules:

• The unit test suite at the end of this post must pass.
• You are not allowed to edit the unit tests.
• You are only allowed to add one (1) using directive to the unit test file to reference the namespace of your proposed solution.
• You must work from the Visual Studio 2010 solution attached to this post. Add a new project that contains your solution. Send me the solution in a .zip file to enter the contest.
• You are allowed to implement your solution in any language you would like as long as it compiles and runs from Visual Studio 2010 Premium.
• The winner is chosen by my subjective judgment, but I will emphasize clean code and design. A tip: attempt to get as good scores as possible from Visual Studio's Code Analysis and Code Metrics. Good scores does not guarantee that you win, but bad scores will most likely ensure that you don't.
• Since many of you are on Christmas vacation the deadline is this year. As long as you submit a solution in 2010 (Danish time) you're a contestant.

There are lots of different ways to skin this cat, so I'm looking forward to your submissions to see all your creative solutions.

This unit test suite is the specification:

using System.ComponentModel.Composition.Hosting;
using Ploeh.Samples.MeffyXmas.MenuModel;
using Xunit;
 
namespace Ploeh.Samples.MeffyXmas.MefMenu.UnitTest
{
    public class ContainerBuilderFacts
    {
        [Fact]
        public void DefaultContainerCorrectlyResolvesOliveOil()
        {
            CompositionContainer container = new ContainerBuilder()
                .Build();
            var oil = container.GetExportedValue<OliveOil>();
            Assert.NotNull(oil);
        }
 
        [Fact]
        public void DefaultContainerCorrectlyResolvesEggYolk()
        {
            CompositionContainer container = new ContainerBuilder()
                .Build();
            var yolk = container.GetExportedValue<EggYolk>();
            Assert.NotNull(yolk);
        }
 
        [Fact]
        public void DefaultContainerCorrectlyResolvesMayonnaise()
        {
            CompositionContainer container = new ContainerBuilder()
                .Build();
            var mayo = container.GetExportedValue<Mayonnaise>();
            Assert.NotNull(mayo);
        }
 
        [Fact]
        public void DefaultContainerReturnsSingletonMayonnaise()
        {
            CompositionContainer container = new ContainerBuilder()
                .Build();
            var mayo1 = container.GetExportedValue<Mayonnaise>();
            var mayo2 = container.GetExportedValue<Mayonnaise>();
            Assert.Same(mayo1, mayo2);
        }
 
        [Fact]
        public void WithTransientMayonnaiseReturnTransientMayonnaise()
        {
            CompositionContainer container = new ContainerBuilder()
                .WithNonSharedMayonnaise()
                .Build();
            var mayo1 = container.GetExportedValue<Mayonnaise>();
            var mayo2 = container.GetExportedValue<Mayonnaise>();
            Assert.NotSame(mayo1, mayo2);
        }
 
        [Fact]
        public void TransientMayonnaiseByDefaultContainsSingletonEggYolk()
        {
            CompositionContainer container = new ContainerBuilder()
                .WithNonSharedMayonnaise()
                .Build();
            var mayo1 = container.GetExportedValue<Mayonnaise>();
            var mayo2 = container.GetExportedValue<Mayonnaise>();
            Assert.Same(mayo1.EggYolk, mayo2.EggYolk);
        }
 
        [Fact]
        public void TransientMayonnaiseByDefaultContainsSingletonOil()
        {
            CompositionContainer container = new ContainerBuilder()
                .WithNonSharedMayonnaise()
                .Build();
            var mayo1 = container.GetExportedValue<Mayonnaise>();
            var mayo2 = container.GetExportedValue<Mayonnaise>();
            Assert.Same(mayo1.Oil, mayo2.Oil);
        }
 
        [Fact]
        public void TransientMayonnaiseCanHaveTransientEggYolk()
        {
            CompositionContainer container = new ContainerBuilder()
                .WithNonSharedMayonnaise()
                .WithNonSharedEggYolk()
                .Build();
            var mayo1 = container.GetExportedValue<Mayonnaise>();
            var mayo2 = container.GetExportedValue<Mayonnaise>();
            Assert.NotSame(mayo1.EggYolk, mayo2.EggYolk);
        }
 
        [Fact]
        public void TransientMayonnaiseCanHaveSingletonOil()
        {
            CompositionContainer container = new ContainerBuilder()
                .WithNonSharedMayonnaise()
                .WithNonSharedEggYolk()
                .Build();
            var mayo1 = container.GetExportedValue<Mayonnaise>();
            var mayo2 = container.GetExportedValue<Mayonnaise>();
            Assert.Same(mayo1.Oil, mayo2.Oil);
        }
 
        [Fact]
        public void TransientMayonnaiseCanHaveTransientOil()
        {
            CompositionContainer container = new ContainerBuilder()
                .WithNonSharedMayonnaise()
                .WithNonSharedOil()
                .Build();
            var mayo1 = container.GetExportedValue<Mayonnaise>();
            var mayo2 = container.GetExportedValue<Mayonnaise>();
            Assert.NotSame(mayo1.Oil, mayo2.Oil);
        }
 
        [Fact]
        public void TransientMayonnaiseCanHaveSingletonEggYolk()
        {
            CompositionContainer container = new ContainerBuilder()
                .WithNonSharedMayonnaise()
                .WithNonSharedOil()
                .Build();
            var mayo1 = container.GetExportedValue<Mayonnaise>();
            var mayo2 = container.GetExportedValue<Mayonnaise>();
            Assert.Same(mayo1.EggYolk, mayo2.EggYolk);
        }
 
        [Fact]
        public void PureTransientMayonnaiseIsTransient()
        {
            CompositionContainer container = new ContainerBuilder()
                .WithNonSharedMayonnaise()
                .WithNonSharedEggYolk()
                .WithNonSharedOil()
                .Build();
            var mayo1 = container.GetExportedValue<Mayonnaise>();
            var mayo2 = container.GetExportedValue<Mayonnaise>();
            Assert.NotSame(mayo1, mayo2);
        }
 
        [Fact]
        public void PureTransientMayonnaiseHasTransientEggYolk()
        {
            CompositionContainer container = new ContainerBuilder()
                .WithNonSharedMayonnaise()
                .WithNonSharedEggYolk()
                .WithNonSharedOil()
                .Build();
            var mayo1 = container.GetExportedValue<Mayonnaise>();
            var mayo2 = container.GetExportedValue<Mayonnaise>();
            Assert.NotSame(mayo1.EggYolk, mayo2.EggYolk);
        }
 
        [Fact]
        public void PureTransientMayonnaiseHasTransientOil()
        {
            CompositionContainer container = new ContainerBuilder()
                .WithNonSharedMayonnaise()
                .WithNonSharedEggYolk()
                .WithNonSharedOil()
                .Build();
            var mayo1 = container.GetExportedValue<Mayonnaise>();
            var mayo2 = container.GetExportedValue<Mayonnaise>();
            Assert.NotSame(mayo1.Oil, mayo2.Oil);
        }
    }
}

ContainerBuilder is the class you must implement, so the unit tests don't compile until you make them. Meffy xmas!

I've been doing Test-Driven Development since 2003. I still do, I still love it, and I still expect to be doing it in the future. Over the years, I've repeatedly returned to the discussion of whether TDD should be regarded as Test-Driven Development or Test-Driven Design. For a long time I've been of the conviction that TDD is both of those. Not so any longer.

TDD is not a good design methodology.

Over the years I've written tons of code with TDD. I've written code where tests blindly drove the design, and I've written code where the design was the result of a long period of deliberation, and the tests were only the manifestations of already well-formed ideas.

I can safely say that the code where tests alone drove the design never turned out particularly well. Although it was testable and, after a fashion, ‘loosely coupled', it was still Spaghetti Code in the sense that it lacked overall consistency and good abstractions.

On the other hand, I'm immensely pleased with code like AutoFixture 2.0, which was mostly the result of hours of careful contemplation riding my bike to and from work. It was still written test-first, but the design was well thought out in advance.

This made me think: did I just fail (repeatedly) at Test-Driven Design, or is the overall concept a fallacy?

That's a pretty hard question to answer; what constitutes good design? In the following, let's assume that the SOLID principles is a pretty good indicator of good design. If so, does test-first drive us towards SOLID design?

TDD versus the Single Responsibility Principle #

Does TDD ensure the application of the Single Responsibility Principle (SRP)? This question is easy to answer and the answer is a resounding NO! Nothing prevents us from test-driving a God Class. I've seen many examples, and I've been guilty of it myself.

Constructor Injection is a much better help because it makes SRP violations so painful.

The score so far: 0 points to TDD.

TDD versus the Open/Closed Principle #

Does TDD ensure that we follow the Open/Closed Principle (OCP)? This is a bit harder to answer. I've previously argued that Testability is just another name for OCP, so that would in itself imply that TDD drives OCP. However, the issue is more complex than that, because there are several different ways we can address the OCP:

• Inheritance
• Composition

According to Roy Osherove's book The Art of Unit Testing, the Extract and Override technique is a common unit testing trick. Personally, I rarely use it, but if used it will indirectly drive us a bit towards OCP via inheritance.

However, we all know that we should favor composition over inheritance, so does TDD drive us in that direction? As I alluded to previously, TDD does tend to drive us towards the use of Test Doubles, which we can view as one way to achieve OCP via composition.

However, another favorite composition technique of mine is to add functionality with a Decorator. This is only possible if the original type implements an interface that can be decorated. It's possible to write a test that forces a SUT to implement an interface, but TDD as a technique in itself does not drive us in that direction.

Grudgingly, however, I must admit that TDD still scores half a point against OCP, for a total score so far of ½ point.

TDD versus the Liskov Substitution Principle #

Does TDD drive us towards adhering to the Liskov Substitution Princple (LSP)? Perhaps, but probably not.

Black box testing can't protect us against the SUT attempting to downcast its dependencies, but at least it doesn't particularly pull us in that direction either. When it comes to the SUT's treatment of a dependency, TDD pulls in neither direction.

Can we test-drive interface implementations that inadvertently violate the LSP? Yes, easily. As I discussed in a previous post, the use of Header Interfaces pulls us towards LSP violations. The more members an interface has, the more likely are LSP violations.

TDD can definitely drive us towards Header Interfaces (although they tend to hurt in the long run). I've seen this happen numerous times, and I've been there myself. TDD doesn't properly encourage LSP adherence.

The score this round: 0 points for TDD, for a running total of ½ point.

TDD versus the Interface Segregation Principle #

Does TDD drive us towards the Interface Segregation Principle (ISP)? No. It's pretty easy to test-drive a SUT towards a Header Interface, just as we can test-drive towards a God Class.

Another 0 points for TDD. The score is still ½ point to TDD.

TDD versus the Dependency Inversion Principle #

Does TDD drive us towards the Dependency Inversion Principle (DIP)? Yes, it does.

The whole drive towards Testability - the ability to replace dependencies with Test Doubles - drives us exactly in the same direction as the DIP.

Since we tend to mistake such mechanistic loose coupling with proper application design, this probably explains why we, for so long, have confused TDD with good design. However, although I view loose coupling as a prerequisite for good design, it is by no means enough.

For those that still keep score, TDD scores 1 point against DIP, for a total of 1½ points.

TDD does not ensure SOLID #

With 1½ out of 5 possible points I have stated my case. I am convinced that TDD itself does not drive us towards SOLID design. It's definitely possible to use test-first techniques to drive towards SOLID designs, but that will always be an extra effort that supplements TDD; it's not something that is inherently built into TDD.

Obviously you could argue that SOLID in itself is not the end-all, be-all of proper API design. I would agree. However, based on my experience with TDD, I think the conclusion holds. TDD does not drive us towards good design. It is not a design technique.

I still write code test-first because I find it more productive, but I make design decisions out of band. I'm a Test-Driven Design Apostate.

Comments

As a comment to my previous post about interfaces being no guarantee for abstractions, Danny asks some interesting questions. In particular, his questions relate to Udi Dahan's presentation Intentions & Interfaces: Making patterns concrete (also known as Making Roles Explicit). Danny writes:

it would seem that Udi recommends creating interfaces for each "role" the domain object plays and using a Service Locator to find the concrete implementation ... or in his case the concrete FetchingStrategy used to pull data back from his ORM. This sounds like his application would have many 1:1 abstractions.

Can this be true, or can we consolidate Role Interfaces with the Reused Abstractions Principle (RAP) - preferably without resorting to a Service Locator? Yes, of course we can.

In Udi Dahan's talks, we see various examples where he queries a Service Locator for a Role Interface. If the Service Locator returns an instance he uses it; otherwise, he falls back to some sort of default behavior. Here is my interpretation of Udi Dahan's slides:

public void Persist(Customer entity)
{
    var validator = this.serviceLocator
        .Get<IValidator<Customer>>();
    if (validator != null)
    {
        validator.Validate(entity);
    }
 
    // Save entity in actual store
}

This is actually not very pretty object-oriented code, but I have Udi Dahan suspected of choosing this implementation to better communicate the essence of how to use Role Interfaces. However, a more proper implementation would have a default (or Null Object) implementation of the Role Interface, and then the special implementation.

If we assume that a NullValidator exists, we can require that the Service Locator can always serve up a proper instance of IValidator<Customer>. This enables us to simplify the Persist method to something like this:

public void Persist(Customer entity)
{
    var validator = this.serviceLocator
        .Get<IValidator<Customer>>();
    validator.Validate(entity);
 
    // Save entity in actual store
}

Either the Service Locator returns a specialized CustomerValidator, or it returns the NullValidator. In any case, this assumption enables us to leverage the Liskov Substitution Principle and refactor the conditional logic to polymorphism.

In other words: every single time we discover the need to extract a Role Interface, we should end up with at least two implementations: the Null Object and the Special Case. Thus the RAP is satisfied.

As a last refactoring, we can also get rid of the Service Locator. Instead, we can use Constructor Injection to inject IValidator<Customer> directly into the Persistence class:

public class CustomerPersistence 
{
    private readonly IValidator<Customer> validator;
 
    public CustomerPersistence(IValidator<Customer> v)
    {
        if (v == null)
        {
            throw new ArgumentNullException("...");
        }
 
        this.validator = v;
    }
 
    public void Persist(Customer entity)
    {
        this.validator.Validate(entity);
 
        // Save entity in actual store
    }
}

Thus, the use of Role Interfaces in no way hinges on using a Service Locator, and everything is good again :)

Comments

In my previous post I discussed why the use of interfaces doesn't guarantee that we work against good abstractions. In this post I will look at some guidelines that might be helpful in defining better abstractions.

One important trait of a useful abstraction is that we can create many different implementations of it. This is the Reused Abstractions Principle (RAP). This is particularly important because composition and separation of concerns often result in such reuse. Every time we use Null Objects, Decorators or Composites, we reuse the same abstraction to compose an application from separate classes that all adhere to the Single Responsibility Principle. For example, Decorators are an excellent way to implement Cross-Cutting Concerns.

The RAP gives us a way to identify good abstractions after the fact, but doesn't say much about the traits that make up a good, composable interface.

On the other hand, I find that the composability of an interface is a pretty good indicator of its potential for reuse. While we can create Decorators from just about any interface, creating meaningful Null Objects or Composites are much harder. As we previously saw, bad abstractions often prevent us from implementing a meaningful Composite.

Being able to implement a meaningful Composite is a good indication of a sound interface.

This understanding is equivalent to the realization associated with the concept of Closure of Operations from Domain-Driven Design. As soon as we achieve this, a lot of very intuitive, almost arithmetic-like APIs tend to follow. It becomes much easier to compose various instances of the abstraction.

With Composite as an indicator of good abstractions, here are some guidelines that should enable us to define more useful interfaces.

ISP #

The more members an interface has, the more difficult it is to create a Composite of it. Thus, the Interface Segregation Principle is a good guide, as it points us towards small interfaces. By extrapolation, the best interface would be an interface with a single member.

That's a good start, but even such an interface could be problematic if it's a Leaky Abstraction or a Shallow Interface. Still, let us assume that we aim for such Role Interfaces and move on to see what other guidelines are available to us.

Commands #

Commands, and by extension any interface that consists of all void methods, are imminently composable. To implement a Null Object, just ignore the input and do nothing. To implement a Composite, just pass on the input to each contained instance.

A Command is the epitome of the Hollywood Principle because telling is the only thing you can do. There's no way to ask a Command about anything when the method returns void. Commands also guarantee the Law of Demeter, because there's no way you can ‘dot' across a void :)

If a Command takes one or more input parameters, they must all stay clear of Shallow Interfaces and Leaky Abstractions. If these conditions are satisfied, a Command tends to be a very good abstraction. However, sometimes we just need return values.

Closure of Operations #

We already briefly discussed Closure of Operations. In C# we can describe this concept as any method that fits this signature in some way:

T DoIt(T x);

An interface that returns the same type as the input type(s) exhibit Closure of Operations. There may be more than one input parameter as long as they are all of the same type.

The interesting thing about Closure of Operations is that any interface with that quality is easily implemented as a Null Object (just return the input). A sort of Composite is often also possible because we can pass the input to each instance in the Composite and use some sort of aggregation or selection algorithm to return a result.

Even if the return type doesn't easily lend itself towards aggregation, you can often implement a coalescing behavior with a Composite by returning the first non-null instance returned by the contained instances.

Interfaces that exhibits Closure of Operations tend to be good abstractions, but it's not always possible to design APIs like that.

Reduction of Input #

Sometimes we can keep some of the benefits from Closure of Operations even though a pure model isn't possible. Any method that returns a type that is a subset of the input types also tends to be composable.

One variation is something like this:

T1 DoIt(T1 x, T2 y, T3 z);

In this sort of interface, the return type is the same as the first parameter. When creating Null Objects or Composites, we can generally just do as we did with pure Closure of Operations and ignore the other parameters.

Another variation is a method like this:

T1 DoIt(Foo<T1, T2, T3> foo);

where Foo is defined like this:

public class Foo<T1, T2, T3>
{
    public T1 X { get; set; }
    public T2 Y { get; set; }
    public T3 Z { get; set; }
}

In this case we can still reduce the input to create the output by simply selecting and returning foo.X and ignoring the other properties.

Still, we may not always be able to define APIs such as these.

Composable return types #

Sometimes (perhaps even most of the times) we can't mold our APIs into any of the above shapes because we inherently need to map one type into another type:

T2 Map(T1 x);

To keep such a method composable, we must then make sure that the output type itself is composable. This would allow us to implement a Composite by wrapping each return value from the contained instances into a Composite of the return type.

Likewise, we could create a Null Object by returning another Null Object for the return type.

In theory, we could repeat this design process to create a big chain of composable types, as long as the last type terminates the chain by fitting into one of the above shapes. However, this can quickly become unwieldy, so we should go to great efforts to make those chains as short as possible.

It should be noted that every type that implements IEnumerable fits pretty well into this category. A Null Object is simply an empty sequence, and a Composite is simply a sequence with multiple items. Thus, interfaces that return enumerables tend to be good abstractions.

Conclusion #

There are many well-known variations of good interface design. The above guiding principles looks only at a small, interrelated set. In fact, we can regard both Commands and Closure of Operations as degenerate cases of Reduction of Input. We should strive to create interfaces that directly fit into one of these categories, and when that isn't possible, at least interfaces that return types that fit into those categories.

Keeping interfaces small and focused makes this possible in the first place.

P.S. (added 2019-01-28) See my retrospective article on the topic.

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