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2015

TIL – How To Check If a Substitute Was Called Zero Times

Setup

During this past week, I’ve been working on a new feature and during development, I ended up with code that looked like this:

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public class PermissionChecker
{
  public PermissionChecker(IModuleDisabler moduleDisabler, User user)
  {
      if (user.IsAdmin) return;
      else if (user.HasFullRights) ConfigureFullRights(moduleDisabler);
      else if (user.HasPartialRights) ConfigurePartialRights(moduleDisabler);
  }

  private void ConfigureFullRights(IModuleDisabler disabler)
  {
      disabler.DisableSystemAdminModule();
  }

  private void ConfigurePartialRights(IModuleDisabler disabler)
  {
      disabler.DisableSystemAdminModule();
      disabler.DisableReportModule();
      disabler.DisableUserManagementModule();
  }
}

So the code is pretty straight forward, I have a PermissionChecker whose job is to use the IModuleDisabler to turn off certain modules depending upon the user permissions. Pretty straightforward implementation.

Now that the solution is fleshed out, it’s time to write some tests around this. When it comes to testing classes that have dependencies on non-trivial classes, I use NSubstitute, a mocking tool, to create mock versions of those dependencies. In this case, NSubstitute allows me to test how the IModuleDisabler is being used by the PermissionsChecker.

For example, let’s say that I wanted to test how the PermissionChecker interacts with the IModuleDisabler when the user has a partial access, I’d write a test that looks like the following:

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[Test]
public void And_the_user_has_partial_access_then_the_disabler_disables_the_report_module()
{
     // Arrange
     var permissionChecker = new PermissionChecker();
     var mockDisabler = Substitute.For();
     var user = new User {HasPartialAccess = true};

     // Act
     permissionChecker.CheckPermissions(mockDisabler, user);

     // Assert
     mockDisabler.Received(1).DisableReportModule();
}

In the above test, our assertion step is to check if the mockDisabler received a single call to the DisableReportModule. If it didn’t receive a call, then the test fails. We can write similar tests for the different modules that should be disabled for the partial rights permission and follow a similar pattern for the full rights permission.

However, things get a bit more interesting when we’re testing what happens if the user is an admin. If we follow the same pattern, we’d end up with a test that looks like this:

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[Test]
public void And_the_user_has_admin_permissions_then_the_disabler_is_not_used()
{
     // Arrange
     var permissionChecker = new PermissionChecker();
     var mockDisabler = Substitute.For();
     var user = new User {IsAdmin = true};

     // Act
     permissionChecker.CheckPermissions(mockDisabler, user);

     // Assert
     mockDisabler.DidNotReceive().DisableSystemAdminModule();
     mockDisabler.DidNotReceive().DisableReportModule();
     mockDisabler.DidNotReceive().DisableUserManagementModule();
}

This solution works for now, however, there is a major maintainability issue, can you spot it?

Problem

The issue arises when we add a new module to be disabled which forces the IModuleDisabler to implement a new method. In that case, you need to remember to update this test to also check that the new method wasn’t being called. If you forget, this test would still pass, but it’d pass for the wrong reason.

To help illustrate, let’s say that another method, DisableImportModule, has been added to the IModuleDisabler interface. In addition, we also need to make sure that this is called when users have partial access, but should not be called for users who are admins or users who have full access.

To fulfill those requirements, we modify the PermissionChecker as so:

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public class PermissionChecker
{
  public PermissionChecker(IModuleDisabler moduleDisabler, User user)
  {
      if (user.IsAdmin) return;
      else if (user.HasFullRights) ConfigureFullRights(moduleDisabler);
      else if (user.HasPartialRights) ConfigurePartialRights(moduleDisabler);
  }

  private void ConfigureFullRights(IModuleDisabler disabler)
  {
      disabler.DisableSystemAdminModule();
  }

  private void ConfigurePartialRights(IModuleDisabler disabler)
  {
      disabler.DisableSystemAdminModule();
      disabler.DisableReportModule();
      disabler.DisableUserManagementModule();
      disabler.DisableImportModule();
  }
}

At this point, we’d write another test for when the a user has partial access, the import module should be disabled. However, it’s very unlikely that we’d remember to update the test for the admin. Remember, for the admin, we’re checking that it received no calls to any disable methods and the way we’re doing that is by checking each method individually.

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[Test]
public void And_the_user_has_admin_permissions_then_the_disabler_is_not_used()
{
  // Arrange
  var permissionChecker = new PermissionChecker();
  var mockDisabler = Substitute.For();
  var user = new User {IsAdmin = true};

  // Act
  permissionChecker.CheckPermissions(mockDisabler, user);

  // Assert
  mockDisabler.DidNotReceive().DisableSystemAdminModule();
  mockDisabler.DidNotReceive().DisableReportModule();
  mockDisabler.DidNotReceive().DisableUserManagementModule();
  // Need to add check for DidNotReceive().DisableImportModule();
}

Solution

There’s got to be a better way. After some digging around, I found that any NSubstitute mock, has a ReceivedCalls method that returns all calls that the mock received. With this new knowledge, we can refactor the previous test with the following:

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[Test]
public void And_the_user_has_admin_permissions_then_the_disabler_is_not_used()
{
  // Arrange
  var permissionChecker = new PermissionChecker();
  var mockDisabler = Substitute.For();
  var user = new User {IsAdmin = true};

  // Act
  permissionChecker.CheckPermissions(mockDisabler, user);

  // Assert
  CollectionAssert.IsEmpty(mockDisabler.ReceivedCalls());
}

This solution is much better because if we add more modules, this test is still checking to make sure that admin users do not have any modules disabled.

Summary

When using a NSubstitute mock and you need to make sure that it received no calls to any methods or properties, you can using NSubstitute’s ReceivedCalls in conjunction with CollectionAssert.IsEmpty to ensure that the substitute was not called.

Using F# To Solve a Constraints Problem

In this post, I’m going to solve a logic puzzle using C# and F#. First, I’ll define the problem being solved and what our restrictions are. Next, I’ll show how I’d break down the problem and write an easy-to-read, extendable solution using idiomatic C#. Afterwards, I’ll solve the same problem and write an easy-to-read, extendable solution writing in idiomatic F#. Finally, we’ll compare the two solutions and see why the F# solution is the better solution.

The Problem

For this problem, I’m going to write a constraint solver (thanks to Geoff Mazeroff for the inspiration).

If you’re not familiar with the concept, a constraint is simply some rule that must be followed (such as all numbers must start with a 4). So a constraint solver is something that takes all the constraints and a source of inputs and returns all values that fit all the constraints.

With that being said, our source will be a list of positive integers and our constraints are the following:

  • 4 digits long (so 1000 – 9999)
  • Must be even (so 1000, 1002, 1004, etc…)
  • The first digit must match the last digit (2002, 2012, 2022, etc…)

To further restrict solutions, all code will be production ready. This includes handling error conditions (like input being null), being maintainable (easily adding more constraints) and easy to read.

To quickly summarize, we need to find a robust, maintainable, and readable solution to help us find all 4 digit number that are even and that the first and last digit are equal.

Implementing a Solution in C

For the C# solution, I’m going to need a class for every constraint, a class to execute all constraints against a source (positive integers) and a runner that ties all the pieces together.

Starting with the smaller blocks and building up, I’m going to start with the constraint classes. Each constraint is going to take a single number and will return true if the number follows the constraint, false otherwise.

With that being said, I’d first implement the constraint that all numbers must be 4 digits long

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class MustBeFourDigitsLongConstraint
{
    public bool FollowsConstraint(int value)
    {
        return value.ToString().Length == 4;
    }
}

Second, I’d write the constraint that all numbers must be even

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class MustBeEvenConstraint
{
    public bool FollowsConstraint(int value)
    {
        return value % 2 == 0;
    }
}

Third, I’d implement the constraint that all numbers must have the same first digit and the last digit

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class FirstDigitMustEqualLastDigitConstraint
{
    public bool FollowsConstraint(int value)
    {
        var valueString = value.ToString();
        return valueString[0] == valueString[valueString.Length-1];
    }
}

At this point, I have the constraints written, but I need them to follow a general contract so that the Constraint Solver (about to be defined) can take a list of these constraints. I’ll introduce an interface, IConstraint and update my classes to implement that interface.

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public interface IConstraint
{
    bool FollowsConstraint(int value);
}
class MustBeFourDigitsLongConstraint : IConstraint {/* Implementation Details Omitted */}

class MustBeEvenConstraint : IConstraint {/* Implementation Details Omitted */}

class FirstDigitMustEqualLastDigitConstraint : IConstraint {/* Implementation Details Omitted */}

So now I have the constraints defined and they’re now implementing a uniform interface, I can now create the constraint solver. This class is responsible for taking the list of numbers and the list of constraints and then returning a list of numbers that follow all constraints.

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class ConstraintSolver
{
    public List FindValues(List constraints, List values)
    {
        if (constraints == null) throw new ArgumentNullException("constraints");
        if (values == null) throw new ArgumentNullException("values");

        var result = values;
        foreach (var constraint in constraints)
        {
            result = result.Where(x => constraint.FollowsConstraint(x)).ToList();
        }
        return result;
    }
}

Finally, I can put all the pieces together using LINQPad (Full C# solution can be found here).

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void Main()
{
    var numbers = Enumerable.Range(0, 10000).ToList();
    var constraints = new List<IConstraint>{new MustBeFourDigitsLongConstraint(), new MustBeEvenConstraint(), 
             new FirstDigitMustEqualLastDigitConstraint()};

    var constraintSolver = new ConstraintSolver();
    var result = constraintSolver.FindValues(constraints, numbers.ToList());

    result.Dump();
}

This solution is easily extendable because if we need to add another constraint, we just add another class that implements the IConstraint interface and change the Main method to add an instance of the new constraint to the list of constraints.

Implementing a Solution in F

Now that we have the C# solution, let’s take a look at how I would solve the problem using F#.

Similar to the C# solution, I’m going to create a function for every constraint, a function to execute all constraints against a source (positive integers) and a runner that ties all the pieces together.

Also similar to the C# solution, I’m going to start with creating the constraints and then work on the constraint solver function.

First, I’d implement that the number must be four digits long constraint.

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let mustBeFourDigit number = 
    number.ToString().Length = 4

Next, the number must be even constraint.

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let mustBeEven number =
    number % 2 = 0

Lastly, the first digit is the same as the last digit constraint.

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let firstDigitMustBeEqualLast number =
    let numberString = number.ToString().ToCharArray()
    let firstDigit = numberString.GetValue(0)
    let lastDigit = numberString.GetValue(numberString.Length-1)
    firstDigit = lastDigit

At this stage in the C# solution, I had to create an interface, IConstraint, so that the constraint solver could take a list of constraints. What’s cool with F# is that I don’t have to define the interface. The F# type inference is saying that each of these functions are taking the same input (some generic `a) and returning a bool, so I can add all of them to the list. This is pretty convenient since I don’t have to worry about this piece of plumbing.

Now that the different constraints are defined, I’d go ahead and write the last function that takes a list of constraints and a list of numbers and returns the numbers that the constraints fit. (Confused by this function? Take a look at Implementing your own version of # List.Filter)

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let rec findValidNumbers numbers constraints = 
    match constraints with
    | [] -> numbers
    | firstConstraint::remainingConstraints ->
        let validNumbers = numbers |> List.filter firstConstraint
        findValidNumbers validNumbers remainingConstraints

Finally, all the pieces are in place, so I can now put all the pieces together using LINQPad.

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let numbers = [1000 .. 9999]
let constraints = [mustBeFourDigits; mustBeEven; firstDigitMustEqualLast;]

let result = findValidNumbers numbers constraints

printf "%A" result

Comparing Both Solutions

Now that we have both solutions written up, let’s compare and see which solution is better.

First, the same design was used for both solutions. I decided to use this design for both because it’s flexible enough that we could add new constraints if needed (such as, the 2nd digit must be odd). As an example, for the C# solution, I’d create a new class that implemented IConstraint and then update the runner to use the new class. For the F# solution, I’d create a new function and update the runner. So, I’d think it’s safe to say that both solutions score about the same from a maintainability and extendability point of view.

From an implementation perspective, both solutions are production ready since the code handles possible error conditions (C# with null checks in the ConstraintSolver class, F# with none because it doesn’t support null). In addition to being robust, both solutions are readable by using ample whitespace and having all variables, classes, and interfaces clearly described.

With that being said, this is where the similarities end. When we look at how much code was written to solve the problem, we have a stark difference. For the C# solution, I ended up with 48 lines of code (omitting blank lines), however, for the F# solution, it only took 19. Now you could argue that I could have written the C# solution in fewer lines of code by removing curly braces around one line statements or ignoring null inputs. However, this would lead the code to be less robust.

Another difference between the F# solution and C# is that I was able to focus on the solution without having to wire up an interface. You’ll often hear developers talk about the how little plumbing you need for F# to “just work” and this small example demonstrates that point.

Another difference (albeit subtle) is that the F# solution is that I can use the findValidNumbers function with any generic list of values and any generic list of functions that take the generic type and return true/false.

In other words, if I had another constraint problem using strings, I’d still implement the different constraints, but I could use the same findValidNumbers function. At that point, however, I’d probably rename it to findValidValues to signify the generic solution.

What’s awesome about this is that I didn’t have to do any more work to have a generic solution, F# did that for me. To be fair, the C# solution can easily be made generic, but that would have to be a conscious design decision and I think that’s a downside.

TL;DR

In this post, we took a look at solving a number constraint problem by using idiomatic C# and F#. Even though both solutions are easy to read and easy to extend, the F# version was less than 1/2 the size of the C# solution. In addition, I didn’t have to do any plumbing for the F# version, but had to do some for the C# solution, and to top it off, the F# solution is generically solved, whereas the C# solution is not.

Implementing Your Own Version of F#’s List.Filter

As I’ve been thinking more about F#, I began to wonder how certain methods in the F# stack work, so I decided to implement F#’s List.filter method.

For those of you who aren’t familiar, List.Filter takes a function that returns true or false and a list of values. The result of the call is all values that fulfill the fuction.

For example, if we wanted to keep just the even numbers in our list, then the following would accomplish that goal.

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let values = [1;2;3;4]
let isItEven x = x % 2 = 0


let evenValues = List.filter isItEven values
// val it : int list = [2; 4]

Now that we know the problem, how would we begin to implement? First, we need to define a function called filter:

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let filter () =

However, to match the signature for List.filter, it needs to take a function that maps integers to bools and the list of values to work on

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let filter (func:int->bool) (values:int List) =

Now that we have the signature, let’s add some logic to match on the list of values. When working with lists, there are two possibilities, an empty list and a non-empty list. Let’s first explore the empty list option.

In the case of an empty list of values, then it doesn’t matter what the func parameter does, there are no possible results, so we should return an empty list for the result.

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let filter (func:int->bool) (values:int List) =
    match values with
    | [] -> []

Now that we’ve handled the empty list, let’s explore the non-empty list scenario. In this branch, the list must have a head and a tail, so we can deconstruct the list to follow that pattern.

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let filter (func:int->bool) (values:int List) =
    match values with
    | [] -> []
    | head::tail -> // what goes here?

Now that we’ve deconstructed the list, we can now use the func parameter with the head element. If the value satisfies the func parameter, then we want to add the head element to the list of results and continue processing the rest of the list. To do that, we can use recursion to call back into filter with the same func parameter and the rest of the list:

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let rec filter (func:int->bool) (values:int List) =
    match values with
    | [] -> []
    | head::tail -> 
         if func head then head :: filter func tail

At this point, we need to handle the case where the head element does not satisfy the func parameter. In this case, we should not add the element to the list of results and we should let filter continue the work

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let rec filter (func:int->bool) (values:int List) =
    match values with
    | [] -> []
    | head::tail -> 
         if func head then head :: filter func tail
         else filter func tail

By handling the base case first (an empty list), filter can focus on the current element in the list (head) and then recurse to process the rest of the list. This solution works, but we can make this better by removing the type annotations. Interestingly enough, we don’t care if we’re working with integers, strings, or whatever. Just as long as the function takes some type and returns bool and the list of values matches the same type as the func parameter, it works. So then we end up with the following:

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let rec filter func values =
    match values with
    | [] -> []
    | head::tail -> if func head then head :: filter func tail else filter func tail

In general, when working with lists, I tend to start by matching the list with either an empty list or non-empty. From there, I’ve got my base case, so I can focus on the implementation for the first element. After performing the work for the first element, I can then recurse to the next element.

Today I Learned – The Chain of Responsibility Design Pattern

There is nothing new in the world except the history you do not know. – Harry S. Truman

The more experience I gain problem solving, the more this holds true. For this post, I’m going to first discuss the problem that I was trying to solve. Next, I’ll show what my first solution was, followed by the shortcomings of this solution. Thirdly, we’ll iterate over a better solution to the problem. This in turn, will provide the motivation for what the Chain of Responsibility is and how to implement. Finally, I’ll wrap up with what the benefits were of using this design. .

Problem I was trying to solve

As part of the process of installing our software, there are scripts that will update the database from it’s current version to the latest version. As it stands, it needs to be able to upgrade a database from any version to the current version.

Previous Solution

The first thing that comes to me is that I need to apply database scripts in a sequential way. For example, if the database’s current version is 1.0 and the latest version is 3.0, it would need to apply the script to upgrade the database from 1.0 to 2.0 and then apply the script to upgrade the database from 2.0 to 3.0.

For the first implementation, there were only two versions, 1.0 and 2.0. Since I didn’t want to build in a lot of functionality if it wasn’t needed yet, I created a helper method that returns the correct updater for a given version. In the below code, if the version does not exist, I assume the database does not exist and return the class that will create the database. Otherwise if the version is 1.0, I return a class that is responsible for the upgrading a database from 1.0 to 2.0. If the version is 2.0, I return a class that doesn’t do anything (i.e. there’s no upgrades to be done).

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public IDatabaseUpdater GetDatabaseUpdater(string version)
{
  if (string.IsNullOrWhiteSpace(version))
    return new DatabaseCreator();
  if (version == "1.0")
    return new Database100To200Updater();
  if (version == "2.0")
    return new CurrentVersionUpdater();
  throw new ArgumentException("The version " + version + " is not supported for database upgrades.");
}

Problem with solution

This solution worked well when there only three possible actions (create a new database, apply the single script, or do nothing). However, we are now going to be shipping version 3.0 and there will need to be a new class that is responsible for upgrading the 2.0 to 3.0. In order to add this functionality, I’d have to do the following:

  1. Create the Database200To300Updater class that contained the logic for updating the database from 2.0 to 3.0.
  2. Modify the Database100To200Updater class to also use the Database200To300Updater in order to perform the next part of the upgrade.
  3. Add additional logic to the above method so that if the database is 2.0 to return the Database200To300Updater class.

After making the modifications, the method now looks like:

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public IDatabaseUpdater GetDatabaseUpdater(string version)
{
  if (string.IsNullOrWhiteSpace(version))
    return new DatabaseCreator();
  if (version == "1.0")
    return new Database100To200Updater(new Database200To300Updater());
  if (version == "2.0")
    return new Database200To300Updater();
  if (version == "3.0")
    return new CurrentVersionUpdater();

  throw new ArgumentException("The version " + version + " is not supported for database upgrades.");
}

So far, so good, we now have the logic to be able to apply scripts in order, however, now that we’ve added version 3.0, I start to wonder what I would do if we added more versions? After some thought, it would look identical to the previous steps (see below for what would happen if we added version 4.0).

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public IDatabaseUpdater GetDatabaseUpdater(string version)
{
  if (string.IsNullOrWhiteSpace(version))
    return new DatabaseCreator();
  if (version == "1.0")
    return new Database100To200Updater(new Database200To300Updater(new Database300To400Updater()));
  if (version == "2.0")
    return new Database200To300Updater(new Database300To400Updater());
  if (version == "3.0")
    return new Database300To400Updater();
  if (version == "4.0")
    return new CurrentVersionUpdater();
  throw new ArgumentException("The version " + version + " is not supported for database upgrades.");
}

If we create some variables to hold onto these classes, and reorder the if statements, we can write this helper method as:

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public IDatabaseUpdater GetDatabaseUpdater(string version)
{
  if (string.IsNullOrWhiteSpace(version))
    return new DatabaseCreator();
  if (version == "4.0")
    return new CurrentVersionUpdater();
  var database300Updater = new Database300To400Updater();
  var database200Updater = new Database200To300Updater(database300To400Updater);
  var database100Updater = new Database100To200Updater(database200To300Updater);

  if (version == "1.0")
    return database100Updater;
  if (version == "2.0")
    return new database200Updater;
  if (version == "3.0")
    return new database300Updater;

  throw new ArgumentException("The version " + version + " is not supported for database upgrades.");
}

Motivation for the Chain of Responsibility

What I find interesting in this design is that I’ve now chained these updater classes together so that if the version 1.0 is returned, it will also use the 2.0 updater, which in turn calls the 3.0 updater. It was at this point, that I remembered a design pattern that followed this structure.

In this design pattern, you essentially have Handlers (in my case updaters) that check to see if they can handle the request. If so, they do and that stops the chain. However, if they can’t handle the request, they pass it to their Successor (which was also a Handler) to handle the request. The design pattern I was thinking about is the Chain of Responsibility pattern.

In order to implement this pattern, you need to have an IHandler interface that exposes a Handle method and either a method or property to set the Successor. The method is the action to take (in our case Update) and the Successor represents the next Handler in the chain if the request could not be handled. The second component is referred to as ConcreteHandlers and they are just the implementors of the interface. One way to implement this is like the following:

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public interface IHandler
{
  IHandler Successor { get; set; }
  void Update(int version);
}

public class ConcreteHandlerA : IHandler
{
  public IHandler Successor { get; set; }

  public void Update(int version)
  {
    if (CanTheRequestBeHandled) {
      // handle the request
    }
    else {
      Successor.Update(version);
    }
  }
}

The main difference between the pattern and what I need is that instead of doing if (canHandle)/else call Successor, what I’m really looking for is to run the upgrade script if the version we’re upgrading to is higher than our current version and then always call the successor. Given this change, here’s what that new implementation looks like:

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public class ConcreteHandlerA : IHandler
{
  public Successor { get; set; }
  public void Update(int version)
  {
    if (CanTheRequestBeHandled) {
      // handle the request
    }
    Successor.Update(version);
  }
}

Implementing the Chain of Responsibility

Now that I know the pattern to use and how it works, I need to update the IDatabaseUpdater interface to follow the IHandler interface. Next, I will need to modify the concrete handlers to use the new interface correctly.

Implementing the Handler

First, we will update our IDatabaseUpdater interface to follow the IHandler look:

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public interface IDatabaseUpdater
{
  void Update(int version);
}
After
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public interface IDatabaseUpdateHandler
{
  void Update(int version);
  IDatabaseUpdateHandler Successor { get; set; }
}

Implementing the Concrete Handler

Second, we will need to update our concrete handlers to implement the interface correctly and to update their UpdateMethod to follow the design. In my case, the concrete handlers perform similar logic, so one of the classes is used for an example.

Before
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public class Database100To200Updater : IDatabaseUpdater
{
  private Database200To300Updater _successor;
  public Database100To200Updater(Database200To300Updater successor)
  {
    if (successor == null)
      throw new ArgumentNullException("successor");
    _successor = successor;
  }

  public void Update()
  {
    Console.WriteLine("Updating the database to version 2.0");
    _successor.Update();
  }
}
After

Thanks to the public property, I was able to remove the private member and that in turn allowed me to remove the constructor. 

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public class Database100To200Updater : IDatabaseUpdateHandler
{
  public void Update(int version)
  {
    if (version >= 2)
      Console.WriteLine("Updating the database to version 2.0");
    if (Successor != null)
      Successor.Update(version);
  }

  public IDatabaseUpdateHandler Successor { get; set;}
}

Updating the Helper Method

Now that we’ve updated the interface and implementors, it’s time to update the helper method to take advantage of the new design.

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public IDatabaseUpdateHandler GetDatabaseUpdater(string version)
{
  if (string.IsNullOrWhiteSpace(version))
    return new DatabaseCreator();

  var database300To400 = new Database300To400Updater();
  var database200To300 = new Database200To300Updater();
  var database100To200 = new Database100To200Updater();

  database100To200.Successor = database200To300;
  database200To300.Successor = database300To400;

  return database100To200;
}

Chain of Responsibility is great, here’s why

What I really like about the chain of responsibility pattern is that I was able to connect my upgrade classes together in a consistent fashion. Another reason why I like this pattern is that it forces me to have the logic to determine whether I should run the update or not inside the individual classes instead of the helper method. This produces more readable code which then lends itself to easier maintainability.