Rash thoughts about .NET, C#, F# and Dynamics NAV.

Nachdem es sich die letzten beiden Jahre mehr und mehr angekündigt hat, wurde der .NET Open Space in Leipzig nun in Dev Open Space 2012 umgetauft. Dies trägt dem Punkt Rechnung, dass die Themenwünsche der Teilnehmer immer breiter geworden sind und wir uns vor allem auch über git, Ruby, JavaScript, HTML5, node.js, CQRS und vieles mehr unterhalten haben. Weiterhin wird es natürlich trotzdem noch reine .NET-Themen geben.

Neu sind außerdem die kostenlosen Workshops die bereits einen Tag vor dem OpenSpace angeboten werden. Ich selbst werde einen zu F# und Test Driven Development halten:

“Test Driven Development (TDD) bringt viele Vorteile für den Code aber erfordert auch eine Menge Übung. Dieser Workshop zeigt, wie man TDD mit F# mittels NaturalSpec and NCrunch erfolgreich einsetzt. NaturalSpec ist ein F#-TDD- Framework, mit dem Unit Tests auf sehr intuitive Weise ausgedrückt werden können. NCrunch hilft, diese Tests ständig (bei jedem Tastendruck) auszuführen. Das zusammen ergibt einen sehr schnellen Feedbackzyklus und TDD wird deutlich schneller. Nach einer kurzen Einführung in die Tools werden im Workshop gemeinsam kleine Programmieraufgaben gelöst.”

Die Anmeldung ist bereits möglich.

I’m happy to announce that I’m giving one of the “Progressive F# Tutorials 2012” in London this year. This event is going to be legendary. Abstract:

Test-Driven Development can give you a lot of benefits for your code but also needs a lot of practice. Come to this session and learn how to master TDD with F#, NaturalSpec and NCrunch.

NaturalSpec is a F# TDD framework which allows to express tests in a very intuitive way and NCrunch helps to execute these tests continuously on very key stroke. This gives a very fast feedback loop and helps to speed up your TDD coding.

After a short introduction of the tools we’ll try to solve a small coding problem together in a coding dojo. All skill levels are welcome and the session will give a lot of room to try out new ideas.

Book your tickets for this awesome event.

In my last article (Introducing NaturalSpec – A Domain-specific language (DSL) for testing) I used NaturalSpec in two small samples. This time I will show how we can set up a NaturalSpec environment to write our first automatically testable scenarios.

1. Choosing an IDE

The first step is to choose an integrated development environment for NaturalSpec. At the current project status you should be able to use NaturalSpec with Visual Studio 2008, Visual Studio 2010 beta 2, the freely available Visual Studio 2008 Shell or the free IDE SharpDevelop 3.0.

2. Installing the testing framework

As NaturalSpec uses NUnit as the underlying testing framework we have to install NUnit 2.5. I also recommend installing TestDriven.Net in order to get a Unit Test runner within Visual Studio.

3. Installing F#

NaturalSpec is completely written in F# and all specs will also be written in F#. This doesn’t imply you have to learn programming in F# but we need the F# compiler to get things working. You can download the F# October 2009 CTP from the Microsoft F# Developer Center.

4. Downloading the latest version of NaturalSpec

You can download a .zip with the latest NaturalSpec libraries from GoogleCode.

5. Creating a spec

This part is written for using Visual Studio 2008. If you use SharpDevelop or Visual Studio 2008 Shell this might differ in some detail.

Start Visual Studio 2008 and create a new F# class library.

Rename Module1.fs in ListSpec.fs and delete script.fsx from the project:

Create a folder “Lib” and unzip the NaturalSpec libraries into it.

Add NaturalSpec.dll and nunit.framework.dll as references to your project:

Copy the following code into ListSpec.fs:

module ListSpec

open NaturalSpec

[<Scenario>]
let When_removing_an_3_from_a_small_list_it_should_not_contain_3() =
  Given [1;2;3;4;5]
    |> When removing 3
    |> It shouldn't contain 3
    |> Verify

If you have TestDriven.Net installed you can run your spec via right click in the solution explorer:

If you don’t like the TestDriven.Net test runner you might want to use the NUnit GUI runner. The output should look like:

In addition the test runner should produce a Spec output file with the name “Spec.txt” within the same folder.

Summary

In a minimal environment you need SharpDevelop, the F# compiler, NUnit and the NaturalSpec libraries for using NaturalSpec.

In the next post I will show how you can use NaturalSpec to create a spec for C# projects.

In the last article I showed how we can use “FAKE – F# Make” to set up a build script which

1. Cleans up old build outputs
2. Compiles our main projects
3. Compiles test projects
4. Uses NUnit to test our assembly
5. Zips the assemblies to a deploy folder.

This time we will improve the same Calculator sample (download here) with a task for FxCop, so please make sure you succeeded with the last article.

“FxCop is a free static code analysis tool from Microsoft that checks .NET managed code assemblies for conformance to Microsoft’s .NET Framework Design Guidelines.”

[Wikipedia]

Setting up FxCop

Open build.fsx from your Calculator sample folder and add a new target “FxCop” to the targets section:

In the dependencies section modify the build order to:

That’s it. If you run your build script you will get new *.xml file in the .\test\-folder:

There are a lot of parameters for the FxCop task. Some are described on the project page.

Letting the build fail

If you were using MSBuild before you might know how hard it is to let MSBuild fail your build if FxCop reports any errors or warnings.

With FAKE the only thing you have to do is setting the “FailOnError” parameter:

If you activate this option FxCop errors will cause your build to fail. Possible values are:

• FxCopErrorLevel.Warning
• FxCopErrorLevel.CriticalWarning
• FxCopErrorLevel.Error
• FxCopErrorLevel.CriticalError
• FxCopErrorLevel.ToolError
• FxCopErrorLevel.DontFailBuild

The values are cummulative. If you choose FxCopErrorLevel.CriticalWarning the build will fail for critical warnings, errors, critical errors and FxCop tool errors but not for simple warnings. The default is FxCopErrorLevel.DontFailBuild.

[Last updated: Jan 9, 2013]

In this tutorial I will describe how you can set up a complete build infrastructure with “FAKE – F# Make”. You will learn how to:

• install the latest FAKE version
• automatically compile your C# or F# projects
• automatically resolve nuget dependencies
• automatically run NUnit UnitTests on your projects
• zip the output to a deployment folder

Install F#

“FAKE – F# Make” is completely written in F# and all build scripts will also be written in F#, but this doesn’t imply that you have to learn programming in F#. In fact the “FAKE – F# Make” syntax is hopefully very easy to learn. But if you need to you can use the complete power of F# and the .NET Framework.

Download Calculator Sample

Now download the latest FAKE-Calculator.zip from the FAKE project site. This sample includes 3 tiny projects and has basically the following structure:

• src\app
  • Calculator (Command line)
  • CalculatorLib (Class library)
• src\test
  • Test.CalculatorLib
• tools
  • NUnit
  • FxCop
• build.bat
• build.fsx
• completeBuild.bat
• completeBuild.fsx
• Calculator.sln

Getting “FAKE – F# Make” started

In the root of the project you will find a build.bat file:

If you run this batch file from the command line then the latest FAKE version will be downloaded via nuget and your first FAKE script (build.fsx) will be executed. If everything works fine you will get the following output:

Now open the build.fsx with Visual Studio. It should look like this:

As you can see the code is really simple. The first line includes the FAKE library and is vital for all FAKE build scripts.

After this header the Default target is defined. A target definition contains of two important parts. The first is the name of the target (here “Default”) and the second is an action (here a simple trace of “Hello world”).

The last line runs the “Default” target – which means it executes the defined action of the target.

Cleaning the last build output

A typical first step in most build scenarios is to clean the output of the last build. We can achieve this by modifying the build.fsx to the following:

We introduced some new concepts in this snippet. At first we defined a global property called “buildDir” with the relative path of a temporary build folder.

In the Clean target we use the CleanDir task to clean up this build directory. This simply deletes all files in the folder or creates the directory if necessary.

In the dependencies section we say that the Default target has a dependency on the Clean target. In other words Clean is a prerequisite of Default and will be run before the execution of Default:

Building the application

In the next step we want to compile our C# libraries, which means we want to compile all csproj-files under /src/app with MSBuild:

We defined a new build target named “BuildApp” which compiles all csproj-files with the MSBuild task and the build output will be copied to buildDir.

In order to find the right project files “FAKE – F# Make” scans the folder src/app/ and all subfolders with the given pattern. Therefore a similar FileSet definition like in NAnt or MSBuild (see project page for details) is used.

In addition the target dependencies are modified again. Now Default is dependent on BuildApp and BuildApp needs Clean as a prerequisite.

This means the execution order is: Clean ==> BuildApp ==> Default.

Building Test projects

Now our main application will be built automatically and it’s time to build the test project. We use the same concepts as before:

This time we defined a new target “BuildTest” which compiles all C# projects below src/test/ in Debug mode and we put the target into our build order.

If we run build.bat again we get an error like this:

The problem is that we didn’t download the NUnit package from nuget. So let’s fix this in the build script:

With this simple command FAKE will use nuget.exe to install all the package dependencies.

Testing the test assemblies with NUnit

Now all our projects will be compiled and we can use Fake’s NUnit task in order to let NUnit test our assembly:

Our new Test target scans the test directory for test assemblies and runs them with the NUnit runner. The mysterious part (fun p –> …) simply overrides the default parameters of the NUnit task and allows to specify concrete parameters..

Deploying a zip file

Now we want to deploy a *.zip file containing our application:

The new Deploy target scans the build directory for all files. The result will be zipped to /deploy/Calculator.zip via the Zip task.

What’s next?

Now you are ready to write your own “FAKE – F# Make” build scripts. If you have any questions or suggestions feel free to comment on this post.

In the next article I will show how we can add FxCop to our build in order to check specific naming rules.

In my last article I showed two ways to use parameterized scenarios in NaturalSpec. This time I will show how we can combine both to test a small Quicksort function.

First of all we define a scenario for sorting:

/// predefined sorting scenario
let sortingScenario f list =
  Given list
    |> When sorting_with f
    |> It should be sorted
    |> It should contain_all_elements_from list
    |> It should contain_no_other_elements_than list

/// predefined Quicksort scenario
let quicksortScenario list = sortingScenario QuickSort list

Now we define some concrete test cases:

[<Scenario>]
let When_sorting_empty_list() =
  quicksortScenario []
    |> Verify
    
[<Scenario>]
let When_sorting_small_list() =
  quicksortScenario [2;1;8;15;5;22]
    |> Verify      
    
[<ScenarioTemplate(100)>]
[<ScenarioTemplate(1000)>]
[<ScenarioTemplate(2500)>]
let When_sorting_ordered_list n =
  quicksortScenario [1..n]
    |> Verify  
    
[<ScenarioTemplate(100)>]
[<ScenarioTemplate(1000)>]
[<ScenarioTemplate(2500)>]
let When_sorting_random_list n =
  quicksortScenario (list_of_random_ints n)
    |> Verify  

After we defined our spec the task is now to implement the sorting function. I am using a very short (and very naïve) Quicksort implementation in F#:

/// naive implementation of QuickSort - don't use it
let rec quicksort = function
  | [] -> []
  | pivot :: rest ->
     let small,big = List.partition ((>) pivot) rest
     quicksort small @ [pivot] @ quicksort big
     
let QuickSort x =
  printMethod ""
  quicksort x   

If we run the scenario, we get the following output (I shortened a bit):

Scenario: When sorting empty list

- Given []
– When sorting with QuickSort
=> It should be sorted
=> It should contain all elements from []
=> It should contain no other elements than []
==> Result is: []
==> OK
==> Time: 0.0355s

Scenario: When sorting small list

- Given [2; 1; 8; 15; 5; 22]
– When sorting with QuickSort
=> It should be sorted
=> It should contain all elements from [2; 1; 8; 15; 5; 22]
=> It should contain no other elements than [2; 1; 8; 15; 5; 22]
==> Result is: [1; 2; 5; 8; 15; 22]
==> OK
==> Time: 0.0065s

Scenario: When sorting ordered list

[…]  100 elements
==> OK
==> Time: 0.0939s

Scenario: When sorting ordered list

[…]  1000 elements
==> OK
==> Time: 0.7130s

Scenario: When sorting ordered list

[…]  2500 elements
==> OK
==> Time: 3.0631s

Scenario: When sorting random list

[…]  100 elements
==> OK
==> Time: 0.0485s

Scenario: When sorting random list

[…]  1000 elements
==> OK
==> Time: 0.1878s

Scenario: When sorting random list

[…]  1000 elements
==> OK
==> Time: 0.8713s

As you can see the function is much faster if we sort a random list. This is because of the naïve choice of the pivot element.

I don’t want to give better implementations here (use LINQ or PLINQ). I just wanted to show how we can easily verify a test function with NaturalSpec.

I wrote a lot about NaturalSpec in my last articles. This time I will show how we can use parameterized scenarios.

1. Using predefined scenarios

By writing predefined parameterized scenarios we can easily create a scenario suite with lots of different test cases:

// predefined scenario
let factorialScenario x result =
  Given x
    |> When calculating factorial
    |> It should equal result

[<Scenario>]
let When_calculation_factorial_of_1() =
  factorialScenario 1 1
    |> Verify   

[<Scenario>]
let When_calculation_factorial_of_10() =
  factorialScenario 10 3628800
    |> Verify

If we run these scenarios with NUnit we will get the following output:

Scenario: When calculation factorial of 1

  – Given 1

    – When calculating factorial

       => It should equal 1

==> OK

==> Time: 0.0093s

Scenario: When calculation factorial of 10

  – Given 10

    – When calculating factorial

       => It should equal 3628800

==> OK

==> Time: 0.0018s

2. Using the ScenarioTemplate attribute

The second and shorter option is to use the ScenarioTemplate attribute, which is inherited from NUnit’s new TestCase attribute:

// with ScenarioTemplate Attribute
[<ScenarioTemplate(1, 1)>]
[<ScenarioTemplate(2, 2)>]
[<ScenarioTemplate(5, 120)>]
[<ScenarioTemplate(10, 3628800)>]
let When_calculating_fac_(x,result) =
  Given x
    |> When calculating factorial
    |> It should equal result
    |> Verify

This code will create 4 different scenarios, which NUnit will display and report separately:

3. Using ScenarioSource

The third option is to use the ScenarioSource attribute. Here we define a function which generates TestData:

/// with a scenario source      
let MyTestCases =
  TestWith 12 3 4
    |> And 12 4 3
    |> And 12 6 2
    |> And 1200 40 30
    |> And 0 0 0 |> ShouldFailWith (typeof<System.DivideByZeroException>)

And then we have to tell NaturalSpec which TestData a scenario should use:

[<Scenario>]
[<ScenarioSource "MyTestCases">]
let When_dividing a b result =
 Given a 
   |> When dividing_by b
   |> It should equal result
   |> Verify

Summary

Sometime it makes sense to test a scenario with a bunch of different parameters. We can use the ScenarioTemplate attribute to easily parameterize our scenarios. If we want more flexibility we can use predefined scenarios with custom parameters or the ScenarioSource attribute.

In my last articles I gave an introduction in NaturalSpec, showed how to get started and demonstrated how we can use NaturalSpec to write automatically testable scenarios for C# projects. This time I will use the same “Car-Dealer”-sample to show how we can mock objects in NaturalSpec.

Mocking objects is an important technique in Test-driven development (TDD) and allows us to simulate complex behavior.

“If an object has any of the following characteristics, it may be useful to use a mock object in its place:

• supplies non-deterministic results (e.g. the current time or the current temperature);
• has states that are difficult to create or reproduce (e.g. a network error);
• is slow (e.g. a complete database, which would have to be initialized before the test);
• does not yet exist or may change behavior;
• would have to include information and methods exclusively for testing purposes (and not for its actual task).”

Wikipedia

In our sample we want to mock the Dealer.SellCar() functionality. The first step is to create an C#-Interface for the Dealer:

namespace CarSellingLib
{
    public interface IDealer
    {
        Car SellCar(int amount);
    }
}

NaturalSpec is using Rhino.Mocks as the underlying mocking framework, so we have to create a reference to Rhino.Mocks.dll in our spec library.

Now we can modify our spec to:

// 1. open module
module CarSpec

// 2. open NaturalSpec-Namespace
open NaturalSpec

// 3. open project namespace
open CarSellingLib

// define reusable values
let DreamCar = new Car(CarType.BMW, 200)
let LameCar = new Car(CarType.Fiat, 45)

// 4. define a mock object and give it a name
let Bert = mock<IDealer> "Bert"

// 5. create a method in BDD-style
let selling_a_car_for amount (dealer:IDealer) =
  printMethod amount
  dealer.SellCar amount

// 6. create a scenario
[<Scenario>]
let When_selling_a_car_for_30000_it_should_equal_the_DreamCar_mocked() =
  As Bert
    |> Mock Bert.SellCar 30000 DreamCar  // 7. register mocked call
    |> When selling_a_car_for 30000
    |> It should equal DreamCar
    |> It shouldn't equal LameCar
    |> Verify

As you can see we changed part 4 (in order to get a mocked IDealer instead of the concrete Dealer). In part 7 we register our mocked behavior. We want that whenever Bert.SellCar is called with parameter 30000 the DreamCar should be returned.

The Verify-function checks if the mocked function has been called. If not the scenario will fail.

If we verify our spec with a NUnit runner we get the following output:

Scenario: When selling a car for 30000 it should equal the DreamCar mocked

- As Bert

- With Mocking

- When selling a car for 30000

=> It should equal BMW (200 HP)

=> It should not equal Fiat (45 HP)

==> OK

In my last two articles I gave an introduction in NaturalSpec and showed how to get started. This time I will show how we can use NaturalSpec to write automatically testable scenarios for C# projects.

Like the TDD principle “Write the tests first” we should write our spec first and use the “Red-Green-Refactor” method.

"Red" – Create a spec scenario that fails

At first I created a F# class library project called “Spec.CarSelling” and added project references to NaturalSpec.dll and nunit.framework.dll (see “Getting started” for further explanations).

Now I can write my first scenario:

// 1. define the module
module CarSpec

// 2. open the NaturalSpec namespace

open NaturalSpec

// 3. open project namespace
open CarSellingLib

// 4. define a test context
let Bert = new Dealer("Bert")

// 5. create a method in BDD-style
let selling_a_car_for amount (dealer:Dealer) =
  printMethod amount
  dealer.SellCar amount

// 6. create a scenario
[<Scenario>]
let When_selling_a_car_for_30000_it_should_equal_my_DreamCar() =
  As Bert
    |> When selling_a_car_for 30000
    |> It should equal (new Car(CarType.BMW, 200))
    |> Verify

At this stage the scenario is ready but doesn’t compile. This means we are ready with the "Red"-stage.

"Green" – Make the test the pass

In order to get the test green we have to create a C# class library called CarSellingLib and define the enum CarType and the classes Dealer and Car. Sticking to the YAGNI-principle we implement only the minimum to get the spec green (and ToString()-members for the output functionality).

namespace CarSellingLib
{
    public enum CarType
    {
        BMW
    }
}

namespace CarSellingLib
{
    public class Car
    {
        public Car(CarType type, int horsePower)
        {
            Type = type;
            HorsePower = horsePower;
        }

        public CarType Type { get; set; }
        public int HorsePower { get; set; }

        public override string ToString()
        {
            return string.Format("{0} ({1} HP)", Type, HorsePower);
        }

        public override bool Equals(object obj)
        {
            var y = obj as Car;
            if(y == null) return false;
            return Type == y.Type && HorsePower == y.HorsePower;
        }
    }
}

using System;

namespace CarSellingLib
{
    public class Dealer
    {
        public Dealer(string name)
        {
            Name = name;
        }

        public string Name { get; set; }

        public Car SellCar(int amount)
        {
            return new Car(CarType.BMW, 200);
        }

        public override string ToString()
        {
            return Name;
        }
    }
}

When we add a project reference to our spec-project the UnitTests should pass and we have completed the "Green" step. (See "Getting started" if you don’t know how to run the spec.) Now we can add some more scenarios to our spec:

// 1. define the module 

module CarSpec

// 2. open NaturalSpec-Namespace
open NaturalSpec

// 3. open project namespace
open CarSellingLib

// 4. define a test context
let Bert = new Dealer("Bert")

// define reusable values
let DreamCar = new Car(CarType.BMW, 200)
let LameCar = new Car(CarType.Fiat, 45)

// 5. create a method in BDD-style
let selling_a_car_for amount (dealer:Dealer) =
  printMethod amount
  dealer.SellCar amount

// 6. create a scenario
[<Scenario>]
let When_selling_a_car_for_30000_it_should_equal_the_DreamCar() =
  As Bert
    |> When selling_a_car_for 30000
    |> It should equal DreamCar
    |> It shouldn't equal LameCar
    |> Verify      

[<Scenario>]
let When_selling_a_car_for_19000_it_should_equal_the_LameCar() =
  As Bert
    |> When selling_a_car_for 19000
    |> It should equal LameCar
    |> It shouldn't equal DreamCar
    |> Verify

// create a scenario that expects an error
[<Scenario>]
[<Fails_with "Need more money">]
let When_selling_a_car_for_1000_it_should_fail_with_Need_More_Money() =
  As Bert
    |> When selling_a_car_for 1000
    |> Verify

Now we are in the “Red”-Phase again.

"Refactor" – rearrange your code to eliminate duplication and follow patterns

After making the spec "Green" and doing some refactoring the project code could look like this:

namespace CarSellingLib
{
    public enum CarType
    {
        Fiat,
        BMW
    }
}

namespace CarSellingLib
{
    public class Car
    {
        public Car(CarType type, int horsePower)
        {
            Type = type;
            HorsePower = horsePower;
        }

        public CarType Type { get; set; }
        public int HorsePower { get; set; }

        # region ToString, Equals 

        public override string ToString()
        {
            return string.Format("{0} ({1} HP)", Type, HorsePower);
        }

        public override bool Equals(object obj)
        {
            var y = obj as Car;
            if(y == null) return false;
            return Type == y.Type && HorsePower == y.HorsePower;
        }

        #endregion
    }
}

using System;

namespace CarSellingLib
{
    public class Dealer
    {
        public Dealer(string name)
        {
            Name = name;
        }

        public string Name { get; set; }

        public Car SellCar(int amount)
        {
            if (amount > 20000)
                return new Car(CarType.BMW, 200);

            if (amount > 3000)
                return new Car(CarType.Fiat, 45);

            throw new Exception("Need more money");
        }

        public override string ToString()
        {
            return Name;
        }
    }
}

The spec output should look like the following:

Scenario: When selling a car for 1000 it should fail with Need More Money

- Should fail…
– As Bert
– When selling a car for 1000

Scenario: When selling a car for 19000 it should equal the LameCar

- As Bert
– When selling a car for 19000
=> It should equal Fiat (45 HP)
=> It should not equal BMW (200 HP)
==> OK

Scenario: When selling a car for 30000 it should equal my DreamCar

- As Bert
– When selling a car for 30000
=> It should equal BMW (200 HP)
==> OK

Scenario: When selling a car for 30000 it should equal the DreamCar

- As Bert
– When selling a car for 30000
=> It should equal BMW (200 HP)
=> It should not equal Fiat (45 HP)
>==> OK

4 passed, 0 failed, 0 skipped, took 1,81 seconds (NUnit 2.5).

Summary

I showed how we can use NaturalSpec for the Red-Green-Refactor process of C# projects and how easy it is to get a spec in natural language.

Test-Driven development (TDD) is a well known software development technique and follows the mantra “Red-Green-Refactor”. Behavior-Driven Development (BDD) is a response to TDD and introduces the idea of using natural language to express the Unit Test scenarios.

There are a lot of popular testing frameworks around which can be used for BDD including xUnit.net ,NUnit, StoryQ, MSpec, NSpec and NBehave. Most of them can be used with fluent interfaces and therefore provides a good readability of the sources. Some of them even provide the possibility to generate a spec in natural language out of passed Unit tests.

What is a spec?

“A specification is an explicit set of requirements to be satisfied by a material, product, or service.”

American Society for Testing and Materials (ASTM) definition

A spec is an important document for the communication process – it enables domain experts to communicate with developers. But how can you verify the compliance with the spec? The answer is: you have to write unit tests. Even with the mentioned frameworks there is a lot of work to do in order to translate a spec scenario into a Unit Test.

Question 7 in the famous Joel Test is “Do you have a spec?”.

The idea of NaturalSpec is to give domain experts the possibility to express their scenarios directly in compilable Unit Test scenarios by using a Domain-specific language (DSL) for Unit Tests. NaturalSpec is completely written in F# – but you don’t have to learn F# to use it. You don’t even have to learn programming at all.

Example 1 – Specifying a list

Let’s consider a small example. If we want to test a new List implementation a spec could look like this:

[<Scenario>]
let When_removing_an_3_from_a_small_list_it_should_not_contain_3() =
  Given [1;2;3;4;5]              // “Arrange” test context
    |> When removing 3           // “Act”
    |> It shouldn't contain 3    // “Assert”
    |> It should contain 4       // another assertion
    |> Verify                    // Verify scenario

I used BDD style here and expressed my scenario in a quite natural language. As the comments are indicating the scenario is following the Arrange Act Assert (“AAA”) pattern.

With the Keyword “Given” I can create a test context (the objects I want to test). In this sample I created a list with 5 elements. With the keyword “When” I call a function which does something with my test context. In this case I want to remove the value 3. In the Assert section (keywords “It should” or “It shouldn’t”) I can give some observations, which should hold for my manipulated test context.

When I run this scenario via a NUnit runner (i am using TestDriven.Net) I get the following output:

Scenario: When removing an 3 from a small list it should not contain 3

- Given [1; 2; 3; 4; 5]
– When removing 3
=> It should not contain 3
=> It should contain 4
==> OK

Example 2 – Specifying a factorial function

If you implement factorial function the spec could look like this:

[<Scenario>]
let When_calculating_fac_5_it_should_equal_120() =
  Given 5
    |> When calculating factorial
    |> It should equal 120
    |> Verify    

[<Scenario>]
let When_calculating_fac_1_it_should_equal_1() =
  Given 1
    |> When calculating factorial
    |> It should equal 1
    |> Verify          

[<Scenario>]
let When_calculating_fac_0_it_should_equal_0() =
  Given 0
    |> When calculating factorial
    |> It should equal 1
    |> Verify

And the output of NaturalSpec would look like this:

Scenario: When calculating fac 0 it should equal 0

- Given 0
– When calculating factorial
=> It should equal 1
==> OK

Scenario: When calculating fac 1 it should equal 1

- Given 1
– When calculating factorial
=> It should equal 1
==> OK

Scenario: When calculating fac 5 it should equal 120

- Given 5
– When calculating factorial
=> It should equal 120
==> OK

Getting started

Of course you can use NaturalSpec to specify C# objects. I see my post "Using NaturalSpec to create a spec for C# projects" for a small sample.

You can download NaturalSpec at GoogleCode and follow the “Getting started” tutorial in order to write your first automatically testable spec.

I am very interested in your feedback. Do you like the syntax? What should I change? Do you consider using a spec tool like NaturalSpec?