Phil Trelford recently released Foq, a small F# mocking library (with a very daring name). If most of your code is in F#, this is probably not a big deal for you, because the technique of mocking isn’t very useful in F# (at least in my experience). On the other hand, if your goal is to unit test some C# code in F#, then Foq comes in very handy.

So why would you want to write your unit tests in F# in the first place?

Let’s start with some plain old C# code, like this:

namespace CodeBase
{
    using System;

    public class Translator
    {
        public const string ErrorMessage = "Translation failure";

        private readonly ILogger logger;
        private readonly IService service;

        public Translator(ILogger logger, IService service)
        {
            this.logger = logger;
            this.service = service;
        }

        public string Translate(string input)
        {
            try
            {
                return this.service.Translate(input);
            }
            catch (Exception exception)
            {
                this.logger.Log(exception);
                return ErrorMessage;
            }
        }
    }

    public interface ILogger
    {
        void Log(Exception exception);
    }

    public interface IService
    {
        string Translate(string input);
    }
}

We have a class, Translator, which takes 2 dependencies, a logger and a service. The main purpose of the class is to Translate a string, by calling the service. If the call succeeds, we return the translation, otherwise we log the exception and return an arbitrary error message.

This piece of code is very simplistic, but illustrates well the need for Mocking. If I want to unit test that class, there are 3 things I need to verify:

• when the translation service succeeds, I should receive whatever the service says is right,
• when the translation service fails, I should receive the error message,
• when the translation service fails, the exception should be logged.

In standard C#, I would typically resort to a Mocking framework like Moq or NSubstitute to test this. What the framework buys me is the ability to create cheaply a fake implementation for the interfaces, setup their behavior to whatever my scenario is (“stubbing”), and in the case of the logger, where I can’t observe through state whether the exception has been logged, verify that the proper call has been made (“mocking”).

This is how my test suite would look:

namespace MoqTests
{
    using System;
    using CodeBase;
    using Moq;
    using NUnit.Framework;

    [TestFixture]
    public class TestsTranslator
    {
        [Test]
        public void Translate_Should_Return_Successful_Service_Response()
        {
            var input = "Hello";
            var output = "Kitty";

            var service = new Mock<IService>();
            service.Setup(s => s.Translate(input)).Returns(output);

            var logger = new Mock<ILogger>();

            var translator = new Translator(logger.Object, service.Object);

            var result = translator.Translate(input);

            Assert.That(result, Is.EqualTo(output));
        }

        [Test]
        public void When_Service_Fails_Translate_Should_Return_ErrorMessage()
        {
            var service = new Mock<IService>();
            service.Setup(s => s.Translate(It.IsAny<string>())).Throws<Exception>();

            var logger = new Mock<ILogger>();

            var translator = new Translator(logger.Object, service.Object);

            var result = translator.Translate("Hello");

            Assert.That(result, Is.EqualTo(Translator.ErrorMessage));
        }

        [Test]
        public void When_Service_Fails_Exception_Should_Be_Logged()
        {
            var error = new Exception();
            var service = new Mock<IService>();
            service.Setup(s => s.Translate(It.IsAny<string>())).Throws(error);

            var logger = new Mock<ILogger>();

            var translator = new Translator(logger.Object, service.Object);

            translator.Translate("Hello");

            logger.Verify(l => l.Log(error));
        }
    }
}

More...

I presented “For Those About to Mock”, an introduction to Mocking for C# developers, at the San Francisco chapter of Bay .NET last week, and promised I would make the material available.

Here it is: you can download the code “For Those About to Mock” here.

Thanks for everyone who made it, it was a great crowd with lots of good questions – I had a great time!

I am in the middle of “Working Effectively with Legacy Code”, and found it every bit as great as it was said to be. In the book, Feathers introduces the concept of Seams and Enabling Points:

a Seam is a place where you can alter behavior in your program without editing it in that place

every seam has an enabling point, a place where you can make the decision to use one behavior or another.

The idea - as I understand it - is that an enabling point is a hook for testability, a place where you can replace the behavior of a piece of code with your own controlled behavior, and validate that the results are as expected.

The reason I am bringing this up is that I have been writing lots of F# lately, and it made me realize that a functional style provides lots of enabling points, and can be much easier to test than object-oriented code.

Here is a simplified, but representative, example of the problem I was looking at: I needed to pick a random item in a list. In C#, a method along these lines would do the job:

public T PickFrom(IList<T> list)
{
   var random = new Random();
   return list[random.Next(list.Count())];
}

However, this code is utterly untestable; it’s also probably a terrible idea to instantiate a new Random every time this is called, so we modify it this way:

public T PickFrom(IList<T> list, Random random)
{
   return list[random.Next(list.Count())];
}

This is much better: now we have a decent Enabling Point, because the list of arguments of the method contains everything that is used inside the method. However, this is still untestable, but for a different reason: by definition, Random.Next() will return different values every time PickFrom is called, and expecting a repeatable result from PickFrom is a bit of a desperate enterprise.

More...

We were doing some pair-programming with Petar recently, Test-Driven Development style, and started talking about how figuring out where to begin with the tests is often the hardest part. Petar noticed that when writing a test, I was typically starting at the end, first writing an Assert, and then coding my way backwards in the test – and that it helped getting things started.

I hadn’t realized I was doing it, and suspected it was coming from Kent Beck’s “Test-Driven Development, by Example”. Sure enough, the Patterns section of the book lists the following:

Assert First. When should you write the asserts? Try writing them first.

So why would this be a good idea?

I think the reason it works well, is that it helps focus the effort on one single goal at a time, and requires clarifying what that goal is. Starting with the Assert forces you to imagine one single fact that should be true once you have implemented the feature, and to think about how you are going to verify that the feature is indeed working.

Once the Assert is in place, you can now write the story backwards: what is the method that was called to get the result being checked, and  where does it belong? What classes and setup is required to make that method call? And, now that the story is written, what is it really saying, and what should the test method name be?

In other words, begin with the Assert, figure out the Act part, Arrange the actors, and (re)name the test method.

I think what trips some people is that while a good test will look like a little story, progressing from a beginning to a logical end, the process leading to it follows a completely opposite direction. Kent Beck points the Self-Similarity in the entire process: write stories which describe what the application will do once done, write tests which describe what the feature does once the code is implemented, and write asserts which will pass once the test is complete. Always start with the end in mind, and do exactly what it takes to achieve your goal.

I am somewhat tests-obsessed, and as a result, often find Excel frustrating to work with, because writing automated tests against it isn’t trivial. So recently, while perusing the chapter on Scripting in Programming F#, I came across an Office automation example, and started wondering whether this would be a practical way to write automated tests against Excel.

The use case I have in mind is an existing Excel Workbook, which contains a model (say, your typical Financial model), with a fixed structure, and maybe a sprinkle of VBA, and no .NET.

For illustration purposes, let’s work with the following: our workbook, Model.xlsx, contains one worksheet, “Finances”, with a Profit cell in B3, computed as the difference between the revenue and cost named cells. Pretty impressive stuff.

What I want is a way to automatically set the Revenue and Cost to some arbitrary value, and check that the result in Profit is what it should be – so that I don’t have to do it myself by hand, and don’t have to remember how this Workbook was supposed to work later on.

Here is how this could look like in a F# script – create a Script file, say WorkbookTest.fsx, with the following code inside:

#r "Microsoft.Office.Interop.Excel"

open System
open Microsoft.Office.Interop.Excel
      
Console.WriteLine("Press [Enter] to start")
Console.ReadLine()

let excel = new ApplicationClass(Visible=false)
let workbooks = excel.Workbooks

let workbookPath = @"C:\Users\Mathias\Desktop\Model.xlsx"

let workbook = workbooks.Open(workbookPath)
let worksheets = workbook.Worksheets
let sheet = worksheets.["Finances"]
let worksheet = sheet :?> Worksheet

let revenueCell = worksheet.Range "Revenue"
revenueCell.Value2 <- 100

let costCell = worksheet.Range "Cost"
costCell.Value2 <- 10

let profitCell = worksheet.Range "Profit"
let profit = profitCell.Value2

Console.WriteLine("Check profit calculations")
Console.WriteLine("Expected: {0}, Actual {1}", 90, profit)

workbook.Close(false, false, Type.Missing)
excel.Quit()

Console.WriteLine("Done, press [Enter] to close")
Console.ReadLine()

The script launches Excel in Invisible mode, opens the workbook, sets the Revenue and Cost to 100 and 10, retrieves the value from Profit, printouts the value it found as well as the expected value – and closes back the Workbook without saving any of the changes.

The nice thing here is that I can now drop that file on my desktop, and simply right-click and select “Run with F# Interactive” to execute it, without building anything, and I’ll see something like this happen:

Nothing earth shattering, but still pretty nice: now I got a script which I can run anytime I want, to check whether the Workbook is behaving properly. Furthermore, what’s nice is that I don’t need to open Visual Studio to work with it: I can simply open WorkbookTest.fsx with Notepad, edit my code, and run it again.

There are some clear issues with the code in its current form. For instance, if anything goes wrong in the code (say, for instance, that I mis-typed a name which doesn’t exist with the workbook), the script will crash miserably, and let the hidden Excel instance hang in the background, waiting for someone to kill it manually. This would require some work to make sure that if exceptions are raised, everything is properly disposed, and no matter what, the file gets closed without saving any modification.

In any case, I thought it was worth sharing, even in its rough state – if only because it was fun, and also because the F# code looks surprisingly more appealing than the usual C# Interop code. Now the fun part would be to turn this into a decent testing framework for Excel…