Reflector.Graph release for Reflector 4.1.5.0 available at www.dotnetwiki.org

[Update] Changed Reflector.Graph back to an assembly

New addins:

• Add List: gives thelist of loaded addins,
• Typed DataSet structure: structure of a DataSet (experimental)
• Class Diagram (UML like)

Reflector.Graph release for Reflector 4.1.5.0 available at www.dotnetwiki.org

[Update] Changed Reflector.Graph back to an assembly

New addins:

• Add List: gives thelist of loaded addins,
• Typed DataSet structure: structure of a DataSet (experimental)
• Class Diagram (UML like)

Image that you could open the designer, drag and drop a few test case, and run them with minimal writing... now take a look at this:

(Download a demo solution at http://blog.dotnetwiki.org/downloads/DragAndDropUnitTesting.zip )

Image that you could open the designer, drag and drop a few test case, and run them with minimal writing... now take a look at this:

(Download a demo solution at http://blog.dotnetwiki.org/downloads/DragAndDropUnitTesting.zip )

Introduction

Have you ever wondered how you could animate armies of thousands of soldiers ? flocks of hunderds of fish ? etc... Well, you use what they call Autonomous Agents: agents that have a local behavior that creates interresting global behaviors. The first example of autonomous agents was brought in 1984 by Craig Reynolds which developped a small application to simulation flocks: the boids application was born.

Since then, Reynolds has published an excellent paper in 99 on the subject: Steering behavior for Autonomous Characteres. If you never had a look at this, check out his web site and look at the java demo, it is just splendid!

Previous try

During my Phd, I monitored the course of C/C++ for third year Engineer students. The autonomous agents theme was very appealing and students got very involved into that project. (If you are looking for something fun for teaching software engineering, this theme is great!). At that time, they received a mini drawing library that could render agents in real time in OpenGL and Glut. If you want to give it a try, you can download it from www.dotnetwiki.org (look for Autonomous.binaries.zip in the download section) Of course, I tested the project on myself and built an application that looked as follows:

On the picture, you can see 151 agent (green dots) that are moving toward the little black dot. They are avoiding themselves, avoiding obstacles (big gray circle). The little lines between agents show that there is a "flocking" interaction,i.e. they are avoiding themselves.

During that project, we could see a lot of interresting properties of such flocks. For example, the system has a self-organization property. If you let the simulation go long enough, agents will organize themselves in a perfect triangular tiling as show below:

We could also see waves where the agents stopped going in reverse direction from the direction of the flock (In PDE theory, those are called shocks). In fact, it is the same phenomenon that occurs in traffic jam when a wave a "zero" velocity is travelling along the highway. When you stand back in your car, just look at the way you will start run a few hundred meters and the stop, and again and again. This behavior is predicted by the hyperbolic PDE theory :) In the figure below, the agents are moving left toward the little black dot. You can visualize the waves going right. The gray lines denote flock which means that agents are stopping in order to avoid each other.

NSteer

The code C++ was written using Tempate Meta Programming. In NSteer, I'll try to build gradually a framework for C#

Introduction

Have you ever wondered how you could animate armies of thousands of soldiers ? flocks of hunderds of fish ? etc... Well, you use what they call Autonomous Agents: agents that have a local behavior that creates interresting global behaviors. The first example of autonomous agents was brought in 1984 by Craig Reynolds which developped a small application to simulation flocks: the boids application was born.

Since then, Reynolds has published an excellent paper in 99 on the subject: Steering behavior for Autonomous Characteres. If you never had a look at this, check out his web site and look at the java demo, it is just splendid!

Previous try

During my Phd, I monitored the course of C/C++ for third year Engineer students. The autonomous agents theme was very appealing and students got very involved into that project. (If you are looking for something fun for teaching software engineering, this theme is great!). At that time, they received a mini drawing library that could render agents in real time in OpenGL and Glut. If you want to give it a try, you can download it from www.dotnetwiki.org (look for Autonomous.binaries.zip in the download section) Of course, I tested the project on myself and built an application that looked as follows:

On the picture, you can see 151 agent (green dots) that are moving toward the little black dot. They are avoiding themselves, avoiding obstacles (big gray circle). The little lines between agents show that there is a "flocking" interaction,i.e. they are avoiding themselves.

During that project, we could see a lot of interresting properties of such flocks. For example, the system has a self-organization property. If you let the simulation go long enough, agents will organize themselves in a perfect triangular tiling as show below:

We could also see waves where the agents stopped going in reverse direction from the direction of the flock (In PDE theory, those are called shocks). In fact, it is the same phenomenon that occurs in traffic jam when a wave a "zero" velocity is travelling along the highway. When you stand back in your car, just look at the way you will start run a few hundred meters and the stop, and again and again. This behavior is predicted by the hyperbolic PDE theory :) In the figure below, the agents are moving left toward the little black dot. You can visualize the waves going right. The gray lines denote flock which means that agents are stopping in order to avoid each other.

NSteer

The code C++ was written using Tempate Meta Programming. In NSteer, I'll try to build gradually a framework for C#

The full source of the BENUG presentation is available for download at http://blog.dotnetwiki.org/downloads/benug.package.zip

The file contains the two presentation I did (TFU.pdf and DPF.pdf in the Showtime folder), the CodeSmith templates and the sample project solution. The first presentation gave a quick introduction to unit testing tools + basic database testing. The second paper presented a new way of handling database testing through intelligent data generators (Database Populator Framework).

If you want to do the exercise of the DPF presentation, you should install TestDriven.Net....msi on your machine. Make sure you remove NUnitAddIn before doing that. This file is a special build of NUnitAddIn (now named TestDriven.Net) that ships with MbUnit.

The full source of the BENUG presentation is available for download at http://blog.dotnetwiki.org/downloads/benug.package.zip

The file contains the two presentation I did (TFU.pdf and DPF.pdf in the Showtime folder), the CodeSmith templates and the sample project solution. The first presentation gave a quick introduction to unit testing tools + basic database testing. The second paper presented a new way of handling database testing through intelligent data generators (Database Populator Framework).

If you want to do the exercise of the DPF presentation, you should install TestDriven.Net....msi on your machine. Make sure you remove NUnitAddIn before doing that. This file is a special build of NUnitAddIn (now named TestDriven.Net) that ships with MbUnit.

This addin explores a Typed DataSet generated by the Visual Studio and creates the table structure. For the example, selecting the NorthwindDataSet, you will get this output:

This addin explores a Typed DataSet generated by the Visual Studio and creates the table structure. For the example, selecting the NorthwindDataSet, you will get this output:

Reflector.Graph now builds and diplays the list of available addins and their menu location. Look for the Tools -> List of Reflector.Graph Addins menu item.

The TestFu Database Populator Framework (DPF presented here) is a framework for generating data for database testing. Given a DataSet, the framework can build a "smart" data generator to you can later use in your databse testing. I will present this at BENUG on sep. 9.

Why this framework ?

When you try to apply unit testing to database, you choices are not much: use transaction - clean up you "mess" after each test or even worse backup and restore the database on each test. In fact, there is an intrisic problem with unit testing of database: you cannot ensure the atomicity of each test, i.e. you cannot leave a database in the state that it was prior to the test (you could by restoring the db  from file at each test, but this is costly).

For example, transaction through enterprise services (see Roy's Rollback attribute) works great... but if you are using IDENTITY columns, then the identity counter is not reseted by the transaction and thus, the test case are correlated.

Now, what if we wanted to build unit tests for database that would not require clean up. This would mean that new data should be generated at each execution, since the previous execution would not have been cleaned up. This is where DPF comes into the picture: the DPF engine will generate new data for each of your unit test execution at no cost.

Generating random data is not difficult

That's true, the System.Random class is easy to use. However, things gets (a bit) more complicated when you generate data for database because you have to ensure that integrity constraint are enforced. This is why you will need such framework.

DPF How-to

The DPF totally relies on DataSet and comes with a few CodeSmith templates to accelerate development. The following how-to could be applied to any of your database.

1. If not done yet, create the strongly-typed DataSet of your database. You can do this by adding a new Typed DataSet to your project and drag and drop the tables in the designer. (Make sure VS has imported the constraint).
2. Open the DatabasePopulator.cst template. This template willl create a "strongly typed" database populator for a given database,
    
   where
   • Database will let you choose a database available on your machine, select the target database here,
   • Namespace  is the namespace of the strongly typed generator class,
   • TableNamePrefix is the table prefix in your database (in case there is one). This prefix will be trimmed to create the class names
3. Open the CrudPopulator.cst template and edit it in order to match the way your DAL access the database. This template will generate populator class that can apply CRUD operation to your database. You can also directly use that template and edit each "throw new NotImplementedException()" statement. (I strongly suggest you edit it the template for your needs).
4. Open the DatabasePopulatorTest.cst tempate and generate a fixture. This template will generate a fixture that will test each CRUD operation of each table in the database. The data necessary to those tests will be automatically generated by the populator.

Jamie Cansdale has also started to build new Reflector.Graph addins. This new addin creates a simple UML-like class diagram around the selected type.

Some facts:

• All the nodes of the graph are clickable wich makes it an easy way of navigation the type hierachy,
• Base class is marked in blue, which a filled arrow
• Methods and properties are marked with + (public), - (private), # (protected) and @ (internal)

Congrats Jamie!

Reflector version: 4.1.4.0
Reflector.Graph version: 4.1.4.0
Download: www.dotnetwiki.org

Before getting the new version, make sure you have a look at the release notes below!

New Addins

• StatementGraph (FlowGraph),
• Automatic Unit Test Generator (using the StatementGraph),
• Method Invokation Graph

This is the first release of the statement graph. It is surely not perfect. If you find anomalies in your graph, please prepare a code example that shows the problem and send it to me :)

TestFixtureSetUp and TestFixtureTearDown

MbUnit now supports TestFixtureSetUp and TestFixtuteTearDown attribute to mark methods to be executed at the beginning of a fixture test case execution and at the end.

[TestFixture]
public class Fixture
{
    [TestFixtureSetUp]
    public void TestFixtureSetUp()
    {...}

    ...

    [TestFixturteTearDown]
    public void TestFixtureTearDown()
    {...}
}

• Both method are optional and are allowed once per class,
• If TestFixtureSetUp invocation fails, no test case are executed and they are all marked as failures,
• TestFixtureTearDown is always invoked,
• If TestFixtureTearDown fails, all the test cases are marked as failure
• TestFixtureSetUp and TestFixtureTearDown are executed on the same instance. This is not ensured for the other methods,
• Output in those methods are recorded in the reports

AssemblyCleanUp, SetUp and TearDown

MbUnit also support test assembly setup and teardown. Those methods should be enclosed in a class that is feeded to the AssemblyCleanUpAttribute (Assembly attribute, thanks Omer), They must be public and static. The setup method must be tagged with SetUpAttribute, and the teardown method with TearDownAttribute:

[assembly: AssemblyCleanUp(typeof(AssemblyCleaner))]
...
public class AssemblyCleaner
{
    [SetUp]
    public static void SetUp()
    {
        Console.WriteLine("Setting up {0}", typeof(AssemblyCleanUp).Assembly.FullName);
    }
    [TearDown]
    public static void TearDown()
    {
        Console.WriteLine("Cleaning up {0}", typeof(AssemblyCleanUp).Assembly.FullName);
    }
}

• Only one class with AssemblyCleanUp per assembly is authorized,
• Both methods are optional,
• If SetUp fails, no tests are run and they are all marked as failure,
• TearDown is always executed.
• If TearDown fails, all the tests are marked as failure

This new Reflector.Addin creates a Method Graph where the vertex are methods, and the edges represent an invokation of a method. By clicking on the vertices, you jump to the next method, while keeping record of your previous steps.

Let's see this on FileStream.WriteByte method as shown above. The figure above is generated by right-clicking on the FileStream method and selecting "Method Invokation Graph". If I choose to to click FlushRight, the graph changes to:

I have revamped my TestFixture generator to work with the StatementGraph (i.e. FlowGraph). The generator logics has not changed:

1. Build the Statement Graph from the method,
2. Extract the path necessary to cover the entire graph (cover all statements in the method),
3. Create one method for each path
4. In each method documentation, output the decompiled code where the "target" statements have been highlighted.

Disclaimer

1. This generator is far from behing finished or optimal: the algorithm to produce the graph is not optimal, I have not implement the Newyork Street Sweeper algorithm yet,
2. If your code is buggy, the generator will generate tests for ... buggy code.

Examples

Here's a sample of what gets output from the examples in the StatementGraph article. Targetted statements are marked with /* i */ where i is the index of the tested statement

/// <summary>Test fixture for the &lt;see cref="StatementSamples"/&gt; class</summary>
/// <remarks />
[TestFixture()]
public class StatementSamplesTest
{
    /// <summary>Tests the Simple method</summary>
    /// <remarks>
    /// <para>Test coverage (estimated): 100,0%</para>
    /// <para>Target path:</para>
    /// <code>/* 0 */ Console.WriteLine("hello");
    /// </code>
    /// </remarks>
    [Test()]
    [Ignore("NotImplemented")]
    public virtual void Simple0()
    {}
    /// <summary>Tests the Block method</summary>
    /// <remarks>
    /// <para>Test coverage (estimated): 100,0%</para>
    /// <para>Target path:</para>
    /// <code>/* 0 */ Console.WriteLine("hello");
    /// /* 1 */ Console.WriteLine("world");
    /// </code>
    /// </remarks>
    [Test()]
    [Ignore("NotImplemented")]
    public virtual void Block0()
    {}
    /// <summary>Tests the If method</summary>
    /// <remarks>
    /// <para>Test coverage (estimated): 83,3%</para>
    /// <para>Target path:</para>
    /// <code>/* 0 */ if (value &lt; 0)
    /// {
    /// /* 1 */ Console.WriteLine("true");
    /// /* 2 */ return;
    /// }
    /// Console.WriteLine("false");
    /// </code>
    /// </remarks>
    [Test()]
    [Ignore("NotImplemented")]
    public virtual void If0()
    {}
    /// <summary>Tests the If method</summary>
    /// <remarks>
    /// <para>Test coverage (estimated): 50,0%</para>
    /// <para>Target path:</para>
    /// <code>/* 0 */ if (value &lt; 0)
    /// {
    /// Console.WriteLine("true");
    /// return;
    /// }
    /// /* 1 */ Console.WriteLine("false");
    /// </code>
    /// </remarks>
    [Test()]
    [Ignore("NotImplemented")]
    public virtual void If1()
    {}
    /// <summary>Tests the While method</summary>
    /// <remarks>
    /// <para>Test coverage (estimated): 100,0%</para>
    /// <para>Target path:</para>
    /// <code>/* 0 */ int num1 = 0;
    /// while ((num1 &lt; 10))
    /// {
    /// /* 1 */ Console.Write(num1++);
    /// }
    /// </code>
    /// </remarks>
    [Test()]
    [Ignore("NotImplemented")]
    public virtual void While0()
    {}
}

This post presents a new Reflector Addin that creates and diplays the graph of statement inside methods: the StatementGraph. This addin is an evolution of the IL graph. (this addin is not yet available for download).

 The statement graph is built from the Reflector CodeModel where each IStatement instance is a vertex and edges are added accordingly to the code "flow" (creating the edges is the most involved task). The rest of the job is handled by the QuickGraph library. When it makes sense, the vertices are clickable and you can jump to the invoked method, etc... The next step will be to update the Automatic Unit Test generator with the StatementGraph...

Let's see some simple methods and their corresponding graphs:

Simple

• Original code:

  public void Simple()
  {
      Console.WriteLine("hello");
  }
  

• Decompiled:

  public void Simple()
  {
        Console.WriteLine("hello");
  }

• Graph:

  

Two statements in sequence

• Original code:

  public void Body()
  {
      Console.WriteLine("hello");
      Console.WriteLine("world");
  }
  

• Decompiled:

  public void Body()
  {
        Console.WriteLine("hello");
        Console.WriteLine("world");
  }

• Graph:

  

If - Then - Else

• Original code:

  public void If(int value)
  {
      if (value<0)
          Console.WriteLine("true");
      else
          Console.WriteLine("false");
  }

• Decompiled:

  public void If(int value)
  {
        if (value < 0)
        {
              Console.WriteLine("true");
              return;
        }
        Console.WriteLine("false");
  }
  

• Graph:

  

While

• Original code:

  public void While()
  {
      int i = 0;
      while(i<10)
      {
          Console.Write(i++);
      }
  }

• Decompiled:

  public void While()
  {
        int num1 = 0;
        while ((num1 < 10))
        {
              Console.Write(num1++);
        }
  }

• Graph:

  

While with break and continue

• Original code:

  public void WhileBreakContinue()
  {
      int i = 0;
      while (i < 10)
      {
          if (i == 5)
              continue;
          if (i == 7)
              break;
          Console.Write(i++);
      }
      Console.WriteLine("Finished");
  }

• Decompiled:

  public void WhileBreakContinue()
  {
        int num1 = 0;
        while ((num1 < 10))
        {
              if (num1 == 5)
              {
                    continue;
              }
              if (num1 == 7)
              {
                    break;
              }
              Console.Write(num1++);
        }
        Console.WriteLine("Finished");
  }
  
  
  

• Graph:

  

Try - Catch

• Original code:

  public void TryCatch()
  {
      try
      {
          Console.WriteLine("hello");
      }
      catch (Exception ex)
      {
          Console.WriteLine("Boom: {0}",ex);
      }
  }
  

• Decompiled:

  public void TryCatch()
  {
        try
        {
              Console.WriteLine("hello");
        }
        catch (Exception exception1)
        {
              Console.WriteLine("Boom: {0}", exception1);
        }
  }

• Graph:

  

Just finished the private presentation of the PhD... One month to go and I'll get the degree :)

For the curious, here's a link to the presentation: http://blog.dotnetwiki.org/downloads/PhDPresentationdeHalleux.pdf

The "classic" TestFixture now supports a new type of test case: combinatorial tests. This fixture comes from an original idea of Jamie Cansdale, and it's design has been refined with the joint help of Jamie, Omer van Kloeten and the dev@mbunit.tigris.org mailing list.

A simple example

Suppose that we have a ICountX interface that defines a method that counts the number of 'x' in a string:

interface ICountX
{
   int Count(string s);
}

You have two classes that implement that interface:

class SickCountX : ICountX
{
   public int Count(string s)
   {
       return 2;
   }
}

class CountX : ICountX
{
   public int Count(string s)
   {
       int count = 0;
       foreach(char c in s)
           if (c=='x')
              count++;
       return count;
   }
}

Now you would like to test that those two interface implementations work correctly. Let's start by writing a test method inside a TestFixture. The CountIsExact method receives a string, the number of x in the string and checks that a provided ICountX implementation computes the expected x count:

[TestFixture]
public class ICountXTest
{
   public class StringX
   {
       public StringX(string value, int xcount){Value = value; XCount = xcount;}
       public string Value;
       public int XCount;
       public override string ToString() { return String.Format("{0},{1}",this.Value,this.XCount);}
   }

   [CombinatorialTest]
   public void CountIsExact(
      ICountX counter,
      StringX s
      )
   {
       Assert.AreEqual(s.XCount, counter.Count(s.Value));
   }
}

Next, we create a few strings and xcount that can serve for creating test case. By simplicity we use the new C# 2.0 iterators to implement that:

[Factory(typeof(StringX))]
public IEnumerable Strings()
{
    yield return new StringX("",0);
    yield return new StringX("x",1);
    yield return new StringX("xa",1);
    yield return new StringX("xax",2);
    yield return new StringX("aaa",0);
}

Note that we have tagged the method with Factory so that MbUnit knows this method creates StringX instances. We also create another method that will create instance of ICountX to test:

[Factory(typeof(ICountX))]
public IEnumerable Counters()
{
   yield return new SickCountX();
   yield return new CountX();
}

Now, we would like to cross product the output of Counters and StringX and feed the combination in the CountIsExact test method. To do so, we use the UsingFactories attribute to tag the parameters of the method:

[CombinatorialTest]
public void CountIsExact(
   [UsingFactories("Counters")] ICountX counter,
   [UsingFactories("Strings")] StringX s
)
{...}

The fixture is ready, so we can give it a run. The output of the test execution is as follows:

[mbunit][Failure] CountIsExact(Counters(SandBox.SickCountX),Strings(,0))
[mbunit][Failure] CountIsExact(Counters(SandBox.SickCountX),Strings(x,1))
[mbunit][Failure] CountIsExact(Counters(SandBox.SickCountX),Strings(xa,1))
[mbunit][Success] CountIsExact(Counters(SandBox.SickCountX),Strings(xax,2))
[mbunit][Failure] CountIsExact(Counters(SandBox.SickCountX),Strings(aaa,0))
[mbunit][Success] CountIsExact(Counters(SandBox.CountX),Strings(,0))
[mbunit][Success] CountIsExact(Counters(SandBox.CountX),Strings(x,1))
[mbunit][Success] CountIsExact(Counters(SandBox.CountX),Strings(xa,1))
[mbunit][Success] CountIsExact(Counters(SandBox.CountX),Strings(xax,2))
[mbunit][Success] CountIsExact(Counters(SandBox.CountX),Strings(aaa,0))
6 succeeded, 4 failed, 0 skipped, took 0,00 seconds.

It worked! As expected, we have 5 x 2 = 10 test case generated. Each test case name is generated out of the data source and different data values. Of course, you can "bind" data to the parameters using various other ways and the tests support more that 2 parameters as we will see in the following. We could also have added multiple Using Attributes.

Prequisites

This new features uses the TestFu.Operations framework in the background. This framework is detailed in the here (part 1) and here (part 2).

Rationale

The CombinatorialTest has the following workflow:

• for each parameter of the test method, get all the domains D of the parameter from the UsingAttributes (there are a bunch of those). This creates a collection of domain for each parameter which is also a domain itself, which we'll call parameter domain: PD = collection of D,
• foreach tuple in the CartesianProduct of the parameter domains
  • foreach ptuple in the PairWizeProduct of the domain in the tuple (each entry is a domain for the corresponding method parameters)
    • Create a test case that will invoke the test method with the values in ptuple.

Note that in the example above, PD = { { Counters }, { Strings } }, hence the Cartesian product has only one element {Counters} x {Strings} = (Counters,Strings). 

Custom Using Attributes

All Using attribute inherit from the abstract base class attribute UsingBaseAttribute which defines one abstract method:

public abstract class UsingBaseAttribute : Attribute
{
    public abstract void GetDomains(
        IDomainCollection domains, 
        ParameterInfo parameter,
        object fixture);
}

This method receives the tagged parameter, an instance of the fixture class and a collection of domains. It can add new domain to this fixture. For example, the following attribute, UsingLinear, generate a linearly spaced vector of integers:

public sealed class UsingLinearAttribute : UsingBaseAttribute
{
    private IDomain domain;
    public UsingLinearAttribute(int start, int stepCount)
    {
        this.domain = new LinearInt32Domain(start, stepCount);
    }
    public override void GetDomains(IDomainCollection domains, ParameterInfo parameter, object fixture)
    {
        domains.Add(domain);
    }
}

Here we have used the LinearInt32Domain shipped with TestFu.Operations and we have added that domain to the domain collection. Let's write a test that uses that attribute and see the result:

[CombinatorialTest]
public void UsingLinear(
    [UsingLinear(0, 10)] int i)
{
    Console.WriteLine(i);
}


--- output
[mbunit][Success] UsingLinear(0)
[mbunit][Success] UsingLinear(1)
[mbunit][Success] UsingLinear(2)
[mbunit][Success] UsingLinear(3)
[mbunit][Success] UsingLinear(4)
[mbunit][Success] UsingLinear(5)
[mbunit][Success] UsingLinear(6)
[mbunit][Success] UsingLinear(7)
[mbunit][Success] UsingLinear(8)
[mbunit][Success] UsingLinear(9)
10 succeeded, 0 failed, 0 skipped, took 0,00 seconds.

Built in Using Attributes

MbUnit comes with a number of built-in using attribute that should get you started almost all situations.

UsingLinearAttribute

Already described previously.

UsingLiteralsAttribute

This attribute lets you specify a list of value separated by ';'. MbUnit will try to convert those to the parameter type using Convert.ChangeType method:

[CombinatorialTest]
public void UsingLinearAndLiterals(
    [UsingLinear(0, 3)] int i,
    [UsingLiterals("a;b")] char c
)
{
    Console.WriteLine("{0} {1}",i,c);
}
--- output
[mbunit][Success] UsingLinearAndLiterals(0,a)
[mbunit][Success] UsingLinearAndLiterals(0,b)
[mbunit][Success] UsingLinearAndLiterals(1,a)
[mbunit][Success] UsingLinearAndLiterals(1,b)
[mbunit][Success] UsingLinearAndLiterals(2,a)
[mbunit][Success] UsingLinearAndLiterals(2,b)
6 succeeded, 0 failed, 0 skipped, took 0,00 seconds.

UsingFactoriesAttribute

This attribute will look for factory method in a specified type. If the factory type is not specified, it will default it to the fixture type. If the member name is not specified, it will look for all the methods tagged with Factory attribute and compatible with the parameter type:

• Not specifying the member name, MbUnit looks for all the compatible factories:

  [Factory]
  public int GetZero()
  {
      return 0;
  }
  [Factory]
  public int[] GetZeroOne()
  {
      return new int[] { 0, 1 };
  }
  [Factory(typeof(int))] // we need to specify the factory type
  public IEnumerable GetZeroOneAsEnumerable()
  {
      return this.GetZeroOne();
  }
  [CombinatorialTest]
  public void UsingFactories(
      [UsingFactories] int i
      )
  {
      Console.WriteLine("{0}", i);
  }
  
  
  -- output
  
  [mbunit][Success] UsingFactories(GetZero(0))
  [mbunit][Success] UsingFactories(GetZeroOne(0))
  [mbunit][Success] UsingFactories(GetZeroOne(1))
  [mbunit][Success] UsingFactories(GetZeroOneAsEnumerable(0))
  [mbunit][Success] UsingFactories(GetZeroOneAsEnumerable(1))
  
  

• Using external factories by specifying a factory type:

  public class IntFactory
  {
      [Factory]
      public int One()
      {
          return 1;
      }
  }
  
  
  [CombinatorialTest]
  public void UsingFactory(
      [UsingFactories(typeof(IntFactory))] int i)
  {
      Console.WriteLine("{0}", i);
  }
  
  --- output
  
  [mbunit][Success] UsingFactory(One(1))
  1 succeeded, 0 failed, 0 skipped, took 0,00 seconds.
  

UsingImplementationsAttribute

This attribute looks for all the implementation of a type in an assembly, creates an instance and feeds it to the test.

[CombinatorialTest]
public void TestCountX([UsingImplementationsAttribute(typeof(ICountX))] ICountX countX)

What about tuple filtering ?

In some situation you may want to filter out tuple. For example, we want to check that a methods throws ArgumentNullException on null arguments:

[Factory]
public string[] Strings()
{
    return new string[] { null, "hello" };
}

[CombinatorialTest]
[ExpectedArgumentNullException]
public void TestWithValidator(
    [UsingFactories("Strings")] string s1,
    [UsingFactories("Strings")] string s2
)
{
    if (s1 == null)
        throw new ArgumentNullException();
    if (s2 == null)
        throw new ArgumentNullException();
}

(Note that ExceptedException and all the other decorator work on the combinatorial tests). If we run the test now, we wil have unwanted tuple such as (null, null) and ("hello", "hello"): the first does not give much information and the second will not throw and hence, is erroneous. In this kind of situation, you can specify a "filter" method that takes the same arguments as the test method and return bool:

public bool IsValid(string s1, string s2)
{
   if (s1 == null && s2 == null)
      return false;
   if (s1 != null && s2 != null)
      return false;
   return true;
}

[CombinatorialTest(TupleValidatorMethod = "IsValid")]
[ExpectedArgumentNullException]
public void TestWithValidator(...

--- output

[mbunit][Success] TestWithValidator(Strings(),Strings(hello))
[mbunit][Success] TestWithValidator(Strings(hello),Strings())

As expected, the unwanted tuple have been dropped.

Conclusion

Combinatorial test provides a flexible, extensible and powerfull way of generating test case. It implements the classic PairWize combinatorial generation in order to avoid exponential test explosion while integrating smoothly in the MbUnit architecture.

Reflector version: 4.1.2.0
Reflector.Graph version: 4.1.2.0
Download: www.dotnetwiki.org

Before getting the new version, make sure you have a look at the release notes below!

Important Changes:

• The graphs are now visualized in SVG by embedding Internet Explorer inside Reflector. Make sure you have a SVG viewer that works with IE installed on your machine. I strongly recommend Adobe SVG Viewer.
• The version number of the assemblies is now following Reflector version. Hence, current version number is 4.1.2.0.

Release Notes:

• The Assembly Graph and IL graph now have clickable nodes. In general, clicking on a vertex will move the selection to that element in the Reflector tree.
• The Assembly Graph now shows all the referenced even if they are not loaded. Click on a unloaded assembly will load it in Reflector,

Adobe SVG viewer tips:

If you are using Adobe SVG viewer, here are a few tips:

• Alt + left down + move move = panning the view,
• Ctrl + left click = zoom in,
• Ctrl + Shift + left click = zoom out,
• Ctrl + left click + mouse move = zoom region,
• Right click pops up the SVG viewer context menu.

Here's the new look of the Assembly graph.

In the previous post on combinatorial testing, I mentionned that Cartesian product was not a good solution when the number of domains and their dimension grew, because of obvious explosion of the number of tests.

A common approach to this problem is to consider a set of combination to create all the possible 2-tuples between the domains. It is called  PairWize or AllPairs suites generation. In TestFu.Operations, I decided to implement the algorithms found in [1]. Currently only the A1 algorithm is implemented. A2 and A4 should follow soon. Note that those algorithms are constructive, memory cheap and fast.

PairWize suite generation

The use of the PairWize algorithm is straightforward and follows the same semantics as the cartesian product. In the example below, we want to generate the allpairs for 3 domains of respective size 2,3,4.

int[] array1 = new int[] { 1, 2 };
char[] array2 = new char[] { 'a', 'b','c' };
string[] array3 = new string[] { "a", "combinatorial", "hello","world" };

int i = 1;
foreach (ITuple tuple in Products.PairWize(array1, array2, array3))
{
    Console.WriteLine("{0}: {1}",i++, tuple);
}

-- output
1: 1, a, a
2: 1, a, combinatorial
3: 2, a, a
4: 1, a, hello
5: 1, a, a
6: 1, a, world
7: 2, a, a
8: 2, b, a
9: 1, b, combinatorial
10: 2, b, combinatorial
11: 2, b, hello
12: 1, b, combinatorial
13: 2, b, world
14: 2, b, combinatorial
15: 1, c, a
16: 1, c, hello
17: 1, c, combinatorial
18: 2, c, hello
19: 1, c, hello
20: 1, c, world
21: 2, c, hello
22: 2, c, a
23: 1, c, world
24: 2, c, combinatorial
25: 2, c, world
26: 2, c, hello
27: 1, c, world
28: 2, c, world

If you wish to compare with the article, this is the output for a (k,l) = (7,3) and for the bipartite graphs A1 = {0,1,2,3} B1={4,5,6}, A2 = {0,4,2,3} B2={1,5,6} and A3 = {0,1,5,3} B3={4,2,6}. Remember that if we want to generate the test cases using the Cartesian product, we would have 3^7 = 2187 tests to run.

1: 0, 0, 0, 0, 0, 0, 0
2: 0, 0, 0, 0, 1, 1, 1
3: 1, 0, 0, 0, 0, 1, 1
4: 0, 1, 0, 0, 1, 0, 1
5: 0, 0, 0, 0, 2, 2, 2
6: 2, 0, 0, 0, 0, 2, 2
7: 0, 2, 0, 0, 2, 0, 2
8: 1, 1, 1, 1, 0, 0, 0
9: 0, 1, 1, 1, 1, 0, 0
10: 1, 0, 1, 1, 0, 1, 0
11: 1, 1, 1, 1, 1, 1, 1
12: 1, 1, 1, 1, 2, 2, 2
13: 2, 1, 1, 1, 1, 2, 2
14: 1, 2, 1, 1, 2, 1, 2
15: 2, 2, 2, 2, 0, 0, 0
16: 0, 2, 2, 2, 2, 0, 0
17: 2, 0, 2, 2, 0, 2, 0
18: 2, 2, 2, 2, 1, 1, 1
19: 1, 2, 2, 2, 2, 1, 1
20: 2, 1, 2, 2, 1, 2, 1
21: 2, 2, 2, 2, 2, 2, 2

Compairing results with AllPairs

For 10 domains with 10 values each, the TestFu algorithm generate 370 test suite. The AllPairs tool generate 177 which is roughly 50% less. This behavior was expected by the algorithm author. A greedy algorithm on the output could lower our result. Note that the tests were generate in 36.419ms which shows the efficiency of the algorithm.

References:

[1] Efficient Algorithms for Generation of Combinatorial Covering Suites, by Adrian Dumitrescu

TestFu has now limited support for generate test suites using Combinatorial Testing as the TestFu.Operations namespace. Combinatorial Testing is an interresting testing technique that has been studied a quite some time now (see citeseer search). There already exists a few package that provide tools to generate test suites (see jenny, allpairs) but none in the .Net framework.

Combinatorial Testing description and Glossary

In this chapter, I will define the different "actors" that interact in the combinatorial testing. I will link them to their corresponding interface in TestFu.

• A domain (IDomain) is a finite set of objects.
• Ex: {1,2,3} is a domain composed of the integers 1,2,3
• The boundary of a domain D is the set of objects in D that are at the boundary of the domain.  The boundary is also a domain,
• If we decide that the first and last element of an array is it's domain, {1,3} is the boundary of {1;2,3}
• A tuple (ITuple) acts as a container for other objects,
• A product on a domain collection (IDomainCollection) is an algorithm (ITupleEnumerable) that generate a suite of tuples (ITupleEnumerator), created by combining one element of each domain, using a predefined strategy.

Currently, the only product available is the cartesian product which returns an exhaustive enumeration of the all possible combination. It is well-known that this product is not efficient at all covering the tests because of the exponential explosion of the number of suites, better strategy have been developped such as the PairWaise covering (all pairs), t-wize, etc... I haven't had the time to look at those yet.

Let's see some code

The TestFu.Operations namespace is designed to be simpler but no simpler. Let's start by defining some domains:

int[] array1 = { 1, 2 };
string[] array2 = { "a", "combinatorial", "hello", "world" };
char[] array3 = { 'a', 'b', 'c' };

Note: TestFu.Operations currently supports arrays, collection (ICollection), enumerable collection (IEnumerable) or singleton domain (1 element). Of course, this is totally extendible. You could easily think about a domain reading the rows of a DataTable, or the elements of a XmlDocument

The static class Products contains a rich set of methods that can create the different products. Let's start with the cartesian product of array1 x array2:

int i = 1;
foreach (ITuple tuple in Products.Cartesian(array1, array2))
{
    Console.WriteLine("\t{0}: {1}",i++,tuple);
}

-- output
        1: 1, a
        2: 1, combinatorial
        3: 1, hello
        4: 1, world
        5: 2, a
        6: 2, combinatorial
        7: 2, hello
        8: 2, world

As expected, each returned tuple is a collection of element from each domain. We could also decide to test the boundaries of the arrays only (first and last element each time):

i = 1;
foreach (ITuple tuple in Products.BoundaryCartesian(array1, array2))
{
    Console.WriteLine("\t{0}: {1}", i++, tuple);
}

-- output
        1: 1, a
        2: 1, world
        3: 2, a
        4: 2, world

The products can act on an arbitrary number of domains so we can add array3 in the product (don't forget about the explosion of the tests number!):

i = 1;
foreach (ITuple tuple in Products.Cartesian(array1, array2, array3))
{
    Console.WriteLine("\t{0}: {1}", i++, tuple);
}

-- output
        1: 1, a, a
        2: 1, a, b
        3: 1, a, c
        4: 1, combinatorial, a
        5: 1, combinatorial, b
        6: 1, combinatorial, c
        7: 1, hello, a
        8: 1, hello, b
        9: 1, hello, c
        10: 1, world, a
        11: 1, world, b
        12: 1, world, c
        13: 2, a, a
        14: 2, a, b
        15: 2, a, c
        16: 2, combinatorial, a
        17: 2, combinatorial, b
        18: 2, combinatorial, c
        19: 2, hello, a
        20: 2, hello, b
        21: 2, hello, c
        22: 2, world, a
        23: 2, world, b
        24: 2, world, c

Where to go from here ?

The next important step is to implement an algorithm that computes the pair-wize or t-wize suite generation. This is very important if you have a lot of domains. In a near future, I will also show how we can use these products to produce a new type of fixture in MbUnit. This fixture was suggested by Jamie Cansdale.

In this post, I have showed a new, simple, way of creating combinatorial tests using the TestFu.Operations namespace.

Yesterday, Jamie Cansdale (NunitAddin) and I spent time "pair-programming" on MbUnit, NUnitAddIn and other tools like the Reflector.Graph addins. The collaboration has been very productive! I've got a lot of blog entry to write about the things we have built yesterday, I'll summarize quickly:

• MbUnit has now a much better support for NUnitAddIn:
  • this solution should be "version" proof: it should not break if NUnitAddIn updates and so on,
  • you can select a method and execute the tests involving that method,
  • MbUnit generates the Html report and puts the URL in the output, ready for you
• MbUnit has new fixtures! CrossFixture generates generate the cross products of different data source and hands it to the test...
• Reflector.Graph renders to SVG: we are now hosting IE inside Reflector to display SVD graphs...
• Reflector.Graph graphs has clickable links! You can click on an assembly to load it, and so on...

A lot of work, a lot of fun...

In this entry, I'll give a tutorial on using QuickGraph to compute the maximum flow of a capacitated network. I will start by giving some defnitions in order to make things clear, then I will apply the QuickGraph algorithms to a practical example.

Maximum Flows

Computing the maximum flow in a network is one of the classic graph theory problem (see [1]). Here's a prototype of flow network:

Imagine a pipeline network for transporting oil from a single source to a single sink. Each edge represents a section of pipeline, and the endpoints of the edge corresponds to the junctures at the ends of that section. The edge capacity is the maximum amount of oil that can flow through the corresponding section per unit time.

What is the maximum amount of oil per unit time that can flow through the network ? That question is a maximum flow problem.

A single-source single-sink network is a connected directed graph that has a distinguised vertex called the source with nonzero outdegree, and a distinguished vertex called sink with  nonzero indegree. A single source-single sink network with source s and sink t (also called target) is called a s-t network. A capacitated network is a connected directed graph such that each edge e is assigned a nonnegative weight cap(e), called the capacity of edge e.

In the following, we shall consider a capacitated s-t network.

Sample network

I will illustrate the example on a 5-vertex capacitated network with source s and sink t as depicted below. This network is extracted from Chapter 12 of [1].

By convention, each edge is tagged with it's capacity (on the left) and, if computed, the flow. s is the source, t is the sink.

Building the sample network with QuickGraph

The first step of the tutorial is to create the sample network above using QuickGraph. To do so, we create a AdjacencyGraph and populate it "manually" with the vertices and edges:

using QuickGraph; // NamedVertex
using QuickGraph.Providers; // providers
using QuickGraph.Representations; // AdjacencyGraphg
using QuickGraph.Concepts; // IEdge

// the graph
AdjacencyGraph graph = new AdjacencyGraph(
    new NamedVertexProvider(),
    new EdgeProvider(),
    true);
// the capacity dictionary
EdgeDoubleDictionary capacities = new EdgeDoubleDictionary();

// adding vertices
NamedVertex s = (NamedVertex)graph.AddVertex(); s.Name = "s";
NamedVertex x = (NamedVertex)graph.AddVertex(); x.Name = "x";
NamedVertex v = (NamedVertex)graph.AddVertex(); v.Name = "v";
NamedVertex w = (NamedVertex)graph.AddVertex(); w.Name = "w";
NamedVertex t = (NamedVertex)graph.AddVertex(); t.Name = "t";

// adding edges
IEdge sx = graph.AddEdge(s, x); capacities[sx] = 5;
IEdge sv = graph.AddEdge(s, v); capacities[sv] = 7;
IEdge xv = graph.AddEdge(x, v); capacities[xv] = 3;
IEdge xw = graph.AddEdge(x, w); capacities[xw] = 7;
IEdge wv = graph.AddEdge(w, v); capacities[wv] = 5;
IEdge wt = graph.AddEdge(w, t); capacities[wt] = 4;
IEdge vt = graph.AddEdge(v, t); capacities[vt] = 6;

Once the graph is built, you can easily draw it using GraphvizAlgorithm. This topic has already been discribed in previous posts so I won't enter into the details .

Preparing the network for the Maximum Flow

In order to work properly, the maximum flow algorithms require that for each edge (u,v) in the network, there exists a reversed edge (v,u). Moreover, a dictionary associating each edge to its reversed must be provided. The sample network obviously does not fullfill this requirement. Therefore, we must add "articifial" reversed edge that have capacity equal to zero. In order to help you with this (tedious) task, QuickGraph provides the ReversedEdgeAugmentorAlgorithm algorithm that will do the job for you:

using QuickGraph.Algorithms.MaximumFlow;

// creating the augmentor
ReversedEdgeAugmentorAlgorithm reversedEdgeAugmentor = new ReversedEdgeAugmentorAlgorithm(this.graph);
// attaching handler to the ReversedEdgeAdded event
// this event is triggered on each "artifical" edge added to the graph
ReversedEdgeAugmentorAlgorithm reversedEdgeAugmentor.ReversedEdgeAdded += new EdgeEventHandler(reversedEdgeAugmentor_ReversedEdgeAdded);

// add the articifial edges
reversedEdgeAugmentor.AddReversedEdges();
...
// cleans up
reversedEdgeAugmentor.RemoveReversedEdges();

// this handler sets the capacity of the new edge to zero
void reversedEdgeAugmentor_ReversedEdgeAdded(Object sender, EdgeEventArgs e)
{
    capacities[e.Edge] = 0;
}

The method AddReversedEdges augments the graph with the reversed edges, while the RemoveReversedEdges "cleans up the mess". If we draw the flow graph after the AddReversedEdges call, it gives the following results (where the reversed edges are dashed):

Computing the MaximumFlow

QuickGraph implements 2 maximum flow algorithms: Edmund Karp and Push Relabel. We will use PushRelabel as it is more efficient, however, both inherit from the abstract base class MaximumFlowAlgorithm. The method Compute computes the maximum flow and returns it's value:

MaximumFlowAlgorithm algo = new PushRelabelMaximumFlowAlgorithm(
    graph,
    capacities,
    reversedEdgeAugmentor.ReversedEdges
    );

double value = algo.Compute(s, t);

After cleaning up the reversed edges, we can draw the graph with the maximum flow in each edge. Note that for this sample, the maxium flow value is 10.

Demo source

The full source of the demo is available in the MbUnit CVS at http://mbunit.tigris.org/source/browse/mbunit/src/QuickGraphTest/MaximumFlowDemo.cs

Acknoledgment

Many thanks to Arun Bhalla for porting PushRelabel to C#

References

[1] Graph Theory and Its applications, Jonathan Gross and Jay Yellen

As mentionned in a previous post, I mentionned that dnAnalytics was a new project providing a managed wrapper above LAPACK. Those guys have been doing a great job and the current release (trunk 271) is already featuring a lot of the "classic" Matrix Algebra algorithms:

• Dense matrices (float or double) with support for the classic operations, +, *, -,
• Norms: norm-1, norm-2, norm-infty, etc...,
• Condition number,
• QR decomposition,
• LU decomposition,
• SVD decomposition

The library is both accessible as a fully managed version, and a managed wrapper above the native, rock solid, LAPACK library. If you are doing matrix algebra in your application, and you care about robustness, efficiency and accuracy, you should be interrested by this project.

In my previous Singleton Unit Testing, I proposed a possible solution for unit testing a singleton (I'll name it the ShortLivingSingleton approach). Omer Van Kloeten came up with another approach (the KillTheSingleton approach), Darren Oakey with the CreateForTesting approach and , Len Holgate finishes the picture tearing appart our the first 2 solutions (the SingletonIsBad approach). Since comments on this topic have been interresting, they are worth a little summary.

The problem

The application you are developping is using a Singleton, that you need to test. How do you test a singleton ?

SingletonIsBad approach

1. Singleton are evil! If you have the opportunity to refactory the code, make sure you definitely need this singleton, otherwize get rid of it.
2. You have no choice and you cannot get rid of the singleton. Make sure you split the singleton functionalities in two classes: The class that does all the work and the singleton aspect that prevents multiple instances. Doing so, you will not have to cheat to test the singleton.
3. You could not fullfill any of the point above, and you will need to cheat...

The two first point came from Len Holgate and I totally agree with him. The third point is for tester who do not have the possiblity of avoiding or refactoring the singleton. To tackle this problem, I and Omer have proposed 2 cheats and Darrel Oakley proposed a wider solution to the problem.

CreateForTesting approach

The approach asks you to embed some functionality in a class that helps other people test it. The most common thing is to add - to most objects - a function CreateTestFoo, where Foo is the object that you are testing. This gives you a new and fully initialized version of Foo - however complicated Fooactually is.

Cheating the singleton.

Both cheat solutions are based on Reflection, therefore they will not work if you have denied Reflection on your tested assembly (Haacked's  comment).

ShortLivingSingleton  approach

This approach consists of creating a new non-singleton approach for each test and do the testing on this instance. To do so, we use reflection to access the private constructor and instanciate the singleton. Therefore, the singleton is never created and never used.

KillTheSingleton approach

This approach kills the singleton after each test, in the TearDown method for example. To "kill" the singleton, the static field holding the singleton reference is nullified using Reflection and garbage collection is forced.

Conclusions

Singletons are evil but yet you find people using them (shame on me). They are problematic to test because you cannot separate the unit tests.  The first step for testing them is actually to refactor your application and get rid of the singleton. If this cannot be done, you have to cheat the singleton using Reflection to properly test them.

ps: I'd like to thank all the people who commented the blog entry for their constructive comments :) Cheers, Jonathan

Here are the NSort benchmarks for arrays of integer filled with random data. These benchmarks are for the non-generic versions.

The code to generate the benchmarks uses NPerf is given below:

using System;
using System.Collections;
using NPerf.Framework;

namespace NSort.Perf
{
    [PerfTester(typeof(ISorter), 10
        , Description = "Sort Algorithm benchmark for Random data"
        , FeatureDescription = "Collection size")]
    public class SorterBenchmark
    {
        protected int[] list;
        public int CollectionCount(int testIndex)
        {
            int n = 0;
            if (testIndex < 0)
                n=10;
            else
                n = (testIndex+1)*500;
            return n; 
        }
        [PerfRunDescriptor]
        public double RunDescription(int testIndex)
        {
            return (double)CollectionCount(testIndex);
        }

        [PerfSetUp]
        public override void SetUp(int testIndex, ISorter sorter)
        {
            Random rnd = new Random();
            this.list = new int[CollectionCount(testIndex)];
            for (int i = 0; i < this.list.Length; ++i)
                this.list[i] = rnd.Next();
        }
        [PerfTest]
        public void SortRandomData(ISorter sorter)
        {
            sorter.Sort(this.list);
        }
    }
}

NSort is a very nice and flexible package of sorting (15) algorithms from which the developer can choose. This library was a jointly work from me, Marc Clifton and Robert Rohde. In this blog, I'll show how NSort can be quickly "upgraded" to Generic and how you can use the extensibility of MbUnit to test it efficiently.

Generic

Converting the algorithms to Generic was really straightforward. For almost all cases, it was just a matter of adding <T> here and there, and replacing temporary object instance by T. Let's see this with the two interfaces of the project: IStorter and ISwap:

using System.Collections;
...

public interface ISorter
{
    IComparer Comparer {get;}
    void Sort(IList list);
}
public interface ISwap
{
    void Swap(IList array, int left, int right);
    void Set(IList array, int left, int right);
    void Set(IList array, int left, object obj);
}

Now, their generic brothers:

using System.Collections.Generic;
...

public interface ISorter<T>
{
    IComparer<T> Comparer {get;}
    void Sort(IList<T> list);
}
public interface ISwap<T>
{
    void Swap(IList<T> array, int left, int right);
    void Set(IList<T> array, int left, int right);
    void Set(IList<T> array, int left, object obj);
}

That was pretty quick. The conversion of the algorithms followed the same ideas and a dozens of cut/paste/replace later the NSort.Generic namespace was born.

Testing

There is a well-know proverb that says "the one who live by the cut-and-paste, die by the cut-and-paste" and that's exactly how I ported NSort to generics... so to ensure the quality of it really needs proper testing.

Testing NSort

Let's start with the testing of the non-generic classes. The main purpose of the NSort is to provide implementation of the ISorter interface that effectively sort list of elements and that's what we are willing to test. A quick (internal) brain strom for test cases of ISorter yields:

• Sort a null list throws ArgumentNullException,
• Sort a list with 0,1,2, n (n large) elements check it is effectively sorted. The purpse of the 0,1,2 is to test "boundary" lists.

Since we are testing an interface, this is a good candidate to use CompositeUnitTesting the TypeFixture of MbUnit:

[TypeFixture(typeof(ISorter))]
public class SorterTest
{
    private int[] list;
    private void CreateSortAndCheckSorted(ISorter sorter, int length)
    {
        Random rnd = new Random();
        list = new int[length];
        // create data
        for (int i = 0; i < list.Length; ++i)
            list[i] = rnd.Next();

        // sort table
        sorter.Sort(list);

        // verify
        for (int i = 0; i < list.Length - 1; ++i)
        {
            Assert.IsTrue(sorter.Comparer.Compare(list[i], list[i + 1]) <= 0,
                "Element {0} ({1}) is strictly greather that {1} ({2})",
                i, list[i], i + 1, list[i + 1]
            );
        }
    }

    [Test]
    [ExpectedArgumentNullException]
    public void SortNulList(ISorter sorter)
    {
        sorter.Sort(null);
    }

    [Test]
    public void SortEmptyList(ISorter sorter)
    {
        CreateSortAndCheckSorted(sorter, 0);
    }
    [Test]
    public void SortListWithOneElement(ISorter sorter)
    {
        CreateSortAndCheckSorted(sorter, 1);
    }
    [Test]
    public void SortListWithTwoElements(ISorter sorter)
    {
        CreateSortAndCheckSorted(sorter, 2);
    }
    [Test]
    public void SortListOfSize100(ISorter sorter)
    {
        CreateSortAndCheckSorted(sorter, 100);
    }
}

Now that we have defined the fixture, we need to feed it with ISorter instances. Usually, you would need to write a factory class that would create the instance, but this task was too boring not to be automated. What I want is a way to tell MbUnit to look for all the classes in NProf that implemented ISorter that apply the fixture to it...

Implementing a custom factory attribute:

The TypeFixture fixture looks fo