Monday, 26 November 2012

Explaining TDD to high school students

Some time ago, I took on a challenge to try and prepare a short introduction to TDD that would make a good presentation for high school students (let's say 45 minutes). As TDD is hard to grasp and get used to even by experienced programmers, I thought that this should be really basic, just to put the point across.

I've pretty much prepared the flow of the presentation. Today I'd like to publish a draft of the presentation in hope to get some constructive feedback and make it even better.

Oh, by the way, I put content associated with each slide below it. Have fun!

Here we go!

Let's start with something obvious. In every activity, it's good to have a goal. Whether you're a race car driver, or a painter or a golf player, or even a tourist laying on the beach to get some sun and rest, you tend to have a goal. Without a goal, it's hard to determine things such as: when am I finished? How do I know that I failed? What can cause me to break the activity? How often do I need to repeat the activity? There are some other questions that can be derived from "having a goal".

We, software engineers, also need to have goals when writing software.

Let's take an exemplary student that is thinking about writing an application "from scratch". His goal may be to create an application that looks and works like Thunderbird e-mail client.

And so, he sets on a journey to make his dream come true. However, the goal is a distant one and so reaching it may be very difficult. This is because there's nothing along the road to tell him whether he's actually closer to or further away from the goal. It's almost like embarking on a journey with eyes closed. In software engineering world, we talk about a project having a high risk associated to it.

However, there's an easy way out of this inconvenience.

If we can split the path into several shorter ones, by choosing a subset of functionality to deliver first, we can arrive at the goal faster and with lower risk. It's like stating "ok, first I need to get to the Statue Of Liberty, and from there...".

Using this approach, we can slowly, but reliably arrive... the full goal. This ability is, of course influenced by another factor - whether or not we have the ability not to mistakenly go back to the point of start. In other words, if our journey is composed of three points: A, B and C, we want to be sure whether from B, we're going to C, not back to A. In order to do this, we need some kind of "landmarks". In software engineering terms, we talk about "a way to confirm existing functionality and avoid introducing regression".

Thus, it makes sense to draw two conclusions.

The first one is that wherever we go and whatever software we write, we cannot take it "in one bite" - we have to split the overall goals into shorter goals to get feedback earlier.

Also, we want to be sure whether we really reached the goal or is it just our imagination. We'd like to be be able to tell whether all the goals are achieved, and if not, we'd like to know what's the next goal we must fulfill in order to get the work done.

Also, we don't want to come back and re-add the functionality we already put in. When we reach one goal, we want to get right to the next one and so on until the application is finished. If we can't completely prevent breaking what already works when adding new functionality, we want to at least know instantly when it happens to address it right away when it's a little trouble to do so.

Thus, we need the goals to be easily and reliably verifiable, so that the first time we arrive at the goal, we want to be sure that we really did. Later, we'd also want to re-verify these goals easily to make sure we didn't lose them accidentally while trying to achieve further goals.

These were the conclusions upon which TDD is built. Now let's see how it looks like in practice, taking on a naive example.

Let's imagine that we're trying to write a function that will raise a number to a given power. Also, let's keep the problem at the primary school level, because that's approximately where I left my math skills :-).

Anyway, we know how the signature would look like - we take one number, and another one and raise the first to the power of another. Now we need to state some goals that will help us arrive at the target.

We can come up with few examples of how properly implemented power function should behave. Each of these examples describes a more general rule. Such examples are called "Key Examples". The first one tells us what about a special case when we take anything and raise it to the power of 0. The second one describes a special case when we take anything and raise it to the power of 1. The third one illustrates the general rule that when we raise something to the power of N, we multiply it N times.

A set of key examples together with more general description forms a specification. Long gone are the times when the best way to write specification was to develop an abstract model of it. Nowadays, we want each rule implemented by the system to be illustrated by a concrete example. That's because...'s very easy to translate the speification made up this way into code, making it executable. This way, we're achieving the so-desired verifiability - if the specification is written as code that actually invokes the developed logic, we can reliably verify whether we really achieved the specified goals. Also, we can re-verify it later in no time, since code executes blazingly fast compared to a human that would need to read the specification and compare it with the actual code.

Ok, so let's take on the first statement of this specification and try to put it in the context.

In order to write and run specifications, we use special tools that provide some infrastructure upon which we can build. Such tools will automate many tasks for us, so we just need to write what we want and the tool will take care of gathering the specifications, executing them and reporting the result. For this example, we're gonna use a framework that's called XUnit.Net.

XUnit.Net allows us to state "facts" about the developed systems, by creating methods and marking them with [Fact] attribute and stating what is the expected behavior of the developed system. If the result is in sync with what we expect, the tool will mark such example as "passed" (usually using green color). If the result is not in sync, the tool will make the example as "failed" (usually using red color). Also, the specification needs a name. We try to name it after a description of the general rule illustrated by the example, so that we can easily come back to it later and read it as a "living documentation".

Now that we have prepared the necessary infrastructure, let's try adding some content to the example.

First, we state our assumptions. We often think about examples in executable specifications in terms of three sections: "Given" (assumptions), "When" (action), "Then" (desired result). We treat it as a general template for a behavior description. In this case, our assumption is that we have any number which happens to be 3 (but the name points that it can be any other number as well). We understand the code we just wrote as "given any number".

Now for the action, or "When". In our case, the action that we want to describe is taking something to the power of 0. Note that we use 0 explicitly and not give it any name. This is to stress that the described behavior takes place only when we use 0 here. This part should be understood as "When we raise it to the power of 0".

And now, the desired result, or "Then". Here, we state what should happen when the behavior is in place - in other words, what will make the example "passed" (green). In our case, we say "Then the result should be equal to 1". If this is not true, the example will be marked as "failed" (red).

Ok, let's quickly recap by trying to read the whole example. It reads like this:

Given any number
When I raise it to the power of 0
Then the result should be equal to 1

Our goal is to make this example "pass" (green) - when we it happens, the tool will display a message like the one on the slide. Note that the goal fulfills the criteria that we defined earlier. It is:

  • short
  • incremental - covers a well defined part of the functionality
  • verifiable - we can compile it, run it and in a second, we'll get a response on whether this goal is achieved or not.

By the way, this goal is so far unfulfilled. We don't have any code to even get past the compilation stage...

So let's add some. Note that we're deliberately putting in an implementation that will make this example "failed" (displayed in red). This is to make sure that the goal is well-stated. One can, by mistake, make an example that will always "pass", and we want ourselves protected from this kind of errors. Thus, we make the first implementation as naive as possible just to compile it and watch it not fulfilling our current specification.

The example we have created seems state the goal well. As the system does not work the way this example describes, it shows "failure" (in red), meaning that the goal is not achieved yet. Our task is to achieve it.

Thankfully, this simple goal could be achieved by changing one character in the original implementation. This is just enough implementation to put the desired behavior in place. Done.

"Wait a minute" - you may say - "this isn't a proper implementation of power algorithm! It's cheating!". And you may give some examples where the current implementation won't work... 2 to the power of 2. If you really said this, all of this would actually be correct, except for the "cheating" part :-).

That's because TDD process consists of small cycles, where we do provide the simplest implementation possible and expand it when we expand the specification with new examples.

This process is usually called "Red - Green - Refactor" and consists of three stages:

  1. Red - named after the color that the tool for running executable specification shows you when the goal stated with an example is not achieved. We saw this when we made out Pow() method return 0 instead of expected 1.
  2. Green - named after the color that the tool shows you when the goal stated with example is achieved by the current implementation. We saw this when we put in the correct implementation for "anything to the power of 0" scenario.
  3. Refactor - After achieving the goal and making sure no previous goals were lost, it's a good moment to take a step back and look at the current design. Maybe the behaviors added on "one by one" basis can be generalized? Maybe something other can be cleaned up? In our case, no refactoring was needed, since there was hardly any design, however, in real-life scenarios, this is a crucial step.

When we finish the whole cycle, we take on another goal and do over until we run out of goals. That's the core of the TDD process.

Now's the time for a confession - you thought this presentation was about Test-Driven Development, but until now, I didn't even mention the word "test" - I was only talking about goals, specifications and examples. So where are the tests?

Ok, here's the thing: we use the examples to state our goals and verify their achievement up to the moment when the logic is in place. After this happens, we don't throw out these examples - they take on the role of micro-level tests that ensure all behaviors persist when we add more logic. These "tests" are a by-product of the TDD process.

The example we went through just now was a simplified case of a single function. As you surely know, the real-world projects, especially those object oriented ones, are not like this. They consist of a web of objects, collaborating together to achieve a task.

Most of these objects know about other objects and use them. In other words, object depend on other objects. Some say that object orientation is all about managing dependencies. How does TDD fit here?

Using examples, we can specify how an object should interact with its collaborators, even those that do not exist yet. "What?" - you may ask - "how am I supposed to create an example of an object that uses something which does not exist?". True, it's impossible per se, but there are ways to deal with that.

The trick is to develop fake objects that look like the real ones on the surface, but underneath, they allow us to set up their behavior, so that the specified object "thinks" different things happen in the system. It's like taking over all media in real life and broadcasting fake auditions about earthquake in New York - people in other countries, who know about current situation in New York from media only will believe the lies and act like they were real. Here, we wanna do the same thing - cheat an object about what happens in its surrounding to write examples on how it should behave.

In order to do it, we can use polymorphism. Let's take a look at two examples of such fake objects.

Sometimes, we want to state that the specified object should communicate something to its collaborators. Let's say we have a drive full of music and we want to show an example where our object makes an attempt to play the music. If we used the real drive, the music playing or not could result from many different conditions (like file privileges, format, whether there are actually any files on the drive etc.) which are out of scope of this example. To make things easier, we use a fake object, cheating our specified one into thinking that it's dealing with a real drive.

This is the second type, that allows us to set up a value returned by a method. Using this object, we can cheat the users of the drive into thinking that it's read only. If we used a real drive, we would probably have to invoke some complex logic to set it in this state. With a fake, we can just pre-program an answer that will be issued when the question gets asked.

The End

That's all I have for now, I'd be grateful for any feedback on this draft. Bye!

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