A common practice of TDD is that you make tiny steps. But one thing which is bugging me is something I've seen a few people do, where by they just hardcode values/options, and then refactor later to make it work properly. For example…
describe Calculator
it should multiply
assert Calculator.multiply(4, 2) == 8
Then you do the least possible to make it pass:
class Calculator
def self.multiply(a, b)
return 8
And it does!
Why do people do this? Is it to ensure they're actually implementing the method in the right class or something? Cause it just seems like a sure-fire way to introduce bugs and give false-confidence if you forget something. Is it a good practice?
This practice is known as "Fake it 'til you make it." In other words, put fake implementations in until such time as it becomes simpler to put in a real implementation. You ask why we do this.
I do this for a number of reasons. One is simply to ensure that my test is being run. It's possible to be configured wrong so that when I hit my magic "run tests" key I'm actually not running the tests I think I'm running. If I press the button and it's red, then put in the fake implementation and it's green, I know I'm really running my tests.
Another reason for this practice is to keep a quick red/green/refactor rhythm going. That is the heartbeat that drives TDD, and it's important that it have a quick cycle. Important so you feel the progress, important so you know where you're at. Some problems (not this one, obviously) can't be solved in a quick heartbeat, but we must advance on them in a heartbeat. Fake it 'til you make it is a way to ensure that timely progress. See also flow.
There is a school of thought, which can be useful in training programmers to use TDD, that says you should not have any lines of source code that were not originally part of a unit test. By first coding the algorithm that passes the test into the test, you verify that your core logic works. Then, you refactor it out into something your production code can use, and write integration tests to define the interaction and thus the object structure containing this logic.
Also, religious TDD adherence would tell you that there should be no logic coded that a requirement, verified by an assertion in a unit test, does not specifically state. Case in point; at this time, the only test for multiplication in the system is asserting that the answer must be 8. So, at this time, the answer is ALWAYS 8, because the requirements tell you nothing different.
This seems very strict, and in the context of a simple case like this, nonsensical; to verify correct functionality in the general case, you would need an infinite number of unit tests, when you as an intelligent human being "know" how multiplication is supposed to work and could easily set up a test that generated and tested a multiplication table up to some limit that would make you confident it would work in all necessary cases. However, in more complex scenarios with more involved algorithms, this becomes a useful study in the benefits of YAGNI. If the requirement states that you need to be able to save record A to the DB, and the ability to save record B is omitted, then you must conclude "you ain't gonna need" the ability to save record B, until a requirement comes in that states this. If you implement the ability to save record B before you know you need to, then if it turns out you never need to then you have wasted time and effort building that into the system; you have code with no business purpose, that regardless can still "break" your system and thus requires maintenance.
Even in the simpler cases, you may end up coding more than you need if you code beyond requirements that you "know" are too light or specific. Let's say you were implementing some sort of parser for string codes. The requirements state that the string code "AA" = 1, and "AB" = 2, and that's the limit of the requirements. But, you know the full library of codes in this system include 20 others, so you include logic and tests that parse the full library. You go back the the client, expecting your payment for time and materials, and the client says "we didn't ask for that; we only ever use the two codes we specified in the tests, so we're not paying you for the extra work". And they would be exactly right; you've technically tried to bilk them by charging for code they didn't ask for and don't need.
Related
In my memory, most people told me I should design from top to bottom. If I want to implement a web page, I should image or draw this page on paper and then divide it into some functionality. For each functionality, I try design the external API, and implement their inside respectively.
But in TDD, they say I should consider a very very small functionality(a method?) first, write its test, fail, implement it and pass test. Composing them is the last step. I can't image how it gets good API.
And most strangely, they say TDD is not only unit tests and also function tests. I think it means top-bottom. If there is a functionality A composed of methods B, C and D. Because of TDD I write the function test for A first. But... B, C, D are all unimplemented. Should I use three stubs? If B depends on other three methods?
I used TDD to write some small programs. But when I striked an application with GUI, I got stuck.
Since TDD starts with what you can see from the outside (of whatever item you are working on at the moment), I'm not sure how it could qualify as bottom-up.
Taking TDD to the extreme (e.g., as in XP, aka extreme programming), you would certainly start from the end-user perspective, and only ever write as much code as you need to pass the tests created so far. If you find yourself starting with the tests for some internal function before reaching the point where the higher-level tests (plus good design for the code you are writing to make those tests pass) require this routine, you are working on some other paradigm, not strict TDD – because there was no test telling you to write that method in the first place. Not that this is necessarily a bad thing, but any problems you have with that is not really one of the TDD methodology.
For GUI programming, of course, you have the standard problem of automating tests, even before you created code. I only know of good tools for web apps for that; if you have good pointers on this topic in the desktop case, I'd sure love to see them.
I've been heavily writing rspec tests for my rails projects keeping a ratio of about 1:1.6 between code/tests. I never really had an issue of what to write first or what it depends on. If the method A that i want to write consists of B and C, then i would first implement B and C, again using the proper testing. To me the sequence is not so important as long as the tests are good and precise.
So, I don't really use stubs the way you describe it, but only if the functionality is already there and i just want to bypass/circumvent it.
BTW, it is considered a top-down approach. This is an excerpt from Rspec Book :
If you ask experienced software
delivery folks why they run a project
like that, front-loading it with all
the planning and analysis, then getting into the detailed design and
programming, and only really integrating and testing it at the end, they
will gaze into the distance, looking
older than their years, and patiently
explain that this is to mitigate
against the exponential cost of
change—the principle that introducing
a change or discovering a defect
becomes exponentially more expensive
the later you discover it. The
top-down approach seems the only
sensible way to hedge against the
possibility of discovering a defect
late in the day.
I would say it's top down. Say I had a single PDF that had 4 distinct documents in it and I was writing software to split them into 4 individual documents instead of a single document, the first test I would probably write is:
// Note: Keeping this very abstract
#Test
public void splitsDocumentsAccordingToDocumentType() {
List docs = new DocumentProcessor().split(new SinglePdfWithFourDocs());
assertEquals(4, docs());
...
}
I would consider the DocumentProcessor.split() method to be similar to "A" in your example. I could now implement the entire algorithm within the single method split and make the tests pass. I don't even need "B" or "C" right? Knowing that you're a good developer and you cringe at the thought of that 1500 line method you would start to look for ways to restructure your code to a more suitable design. Maybe you see that two additional objects (responsibilities) could be split out of this code:
1) Parsing the contents of the file to find the individual documents and
2) Reading and writing of the document from the file system
Let's tackle #1 first. Use a couple of "Extract Method" refactorings to localize code related to the parsing of the contents then an "Extract Class" refactoring, pulling out those methods into a class named, say DocumentParser. This could be analagous to "B" in your example. If you'd like, you could move tests related to document parsing from your DocumentProcessorTest to a new DocumentParserTest and mock or stub the DocumentParser in the DocumentProcessorTest.
For #2 it's pretty much lather, rinse, repeat and you'll end up with something like a DocumentSerializer class, AKA "C". You can mock this as well in your DocumentProcessorTest and you now have no file I/O and have test driven a component that has two additional collaborators without having to design your entire class (with individual methods). Notice that we took an "outside in" approach, which really enables the refactoring.
Thanks
The first part of the TDD cycle is selecting a test to fail. I'd like to start a community wiki about this selection process.
Sometimes selecting the test to start with is obvious, start with the low hanging fruit. For example when writing a parser, an easy test to start with is the one that handles no input:
def testEmptyInput():
result = parser.parse("")
assertNullResult(result)
Some tests are easy to pass requiring little implementation code, as in the above example.
Other tests require complex slabs of implementation code to pass, and I'm left with the feeling I haven't done the the "easiest thing possible to get the test to pass". It's at this point I stop trying to pass this test, and select a new test to try to pass, in the hope that it will reveal an easier implementation for the problematic implementation.
I'd like to explore some of the characteristic of these easy and challenging tests, how they impact testcase selection and ordering.
How does test selection relate to topdown and bottom up strategies? Can anyone recommend writings that addresses these strategies in relation to TDD?
I start by anchoring the most valuable behaviour of the code.
For instance, if it's a validator, I'll start by making sure it says that valid objects are valuable. Now we can showcase the code, train users not to do stupid things, etc. - even if the validator never gets implemented any further. After that, I start adding the edge cases, with the most dangerous validation mistakes first.
If I start with a parser, rather than start with an empty string, I might start with something typical but simple that I want to parse and something I'd like to get out of that. For me unit tests are more like examples of how I'm going to want to use the code.
I also follow BDD's practice of naming the tests should - so for your example I'd have shouldReturnNullIfTheInputIsEmpty(). This helps me identify the next most important thing the code should do.
This is also related to BDD's "outside-in". Here are a couple of blog posts I wrote which might help: Pixie Driven Development and Bug Driven Development. Bug Driven Development helps me to work out what the next bit of system-level functionality I need should be, which then helps me find the next unit test.
Hope this gives you a slightly different perspective, anyway - good luck!
To begin with, I'll pick a simple typical case and write a test for it.
While I'm writing the implementation I'll pay attention to corner cases that my code handles incorrectly. Then I'll write tests for those cases.
Otherwise I'll look for things that the function in question should do, but doesn't.
In doing test driven development I have been in the habit of writing the first unit test for a new piece of functionality first, then writing the code for that functionality. If I have additional tests to write to cover all scenarios, I usually write them after the code is written. Is this considered bad form? Should I try and write every conceivable test for a piece of functionality first, before ever writing that code?
In order to do TDD properly, you always write the test first, and then the functionality second.
To add to that, I would take one scenario at a time, don't write 20 tests and then write the code for those 20 tests. Write one test, red/green flag it, then move on to your next test. This makes sure you're also doing one of the core tenets of TDD, which is to do the simplest implementation possible that meets all of your requirements/scenarios.
actually no, I often discover functionality "on-the-go". Let me explain the "no" a bit further:
I usually start out writing a test case for a high level feature, defining its Interface. After that, I usually set this test to ignore and continue writing tests for each of the Interfaces functionality. My cycle goes like:
Integration Test for Story A (high level API)
Write Unit Test for method xyz called in Integration Test
Implement method (red/green/refactor)
Repeat 2+3 till Integration Test passes.
While doing so, I often realize I have forgotten some small functionality in my main test. I then usually take time to look back at my customers requirements. If its a fit, I go back and add a test for it, set to ignored as I first want to finish what I started.
Sometimes I see the chance to do a refactoring. I usually finish an implementation till I reach a commit point and do refactoring then, however sometimes I stash my changes, go back and do the refactoring (including new tests if nescessary) first. This workflow is powererd by Mercurial MQ.
For most people, TDD and incremental/agile development go together. This looks something like:
Write a test for some feature
Write just enough code to make the test pass, refactoring as necessary
Repeat.
If you happen to have a detailed specification ahead of time, you could write all of the tests first, but you'd have to live with having sone tests not passing for a while.
The sooner you write the tests, the better. I usually find writing tests being harder tasks than actually implementing the functionality because you have to be aware of all the possible outcomes. So I tend to write more tests when I'm "in the zone". And when during coding I realize I might have missed a test case I just note that down on the to-do lists.
So in my opinion it's up to your leisure but I would implement tests in multiple batches.
The way I see it, test driven development isn't necessarily tests first development. Your tests drive your development and you are really writing your tests as you develop your application. You start by writing a simple test that fails because you haven't written the functionality yet. Then you write your code to implement that so that the tests pass.
Then you go back to your test, make modifications that will force you to add more functionality or refactor your code to follow better practices or reduce duplicate code, go fix your code to make the test pass...repeat, repeat, repeat.
A couple of videos that demonstrates this is below, although you can probably find a lot more by googling "TDD Video"
http://agilesoftwaredevelopment.com/videos/test-driven-development-basic-tutorial
(oops, only one video, new users can't insert more than one link)
I try to write a test at some level before each bit of functionality. Sometimes, I have to write a little more code to get through the compiler, but I try to minimise that. Writing the test first means that I've thought about what the code is supposed to achieve before writing it.
One technique I find useful is to keep an index card or notepad handy, and make a note of all the cases that I think of along the way. That allows me to focus on the current task without losing track of all the other things I'm supposed to think about. Afterwards, I can work through the list and either complete the extra cases or drop them as not necessary.
You could do that, but you wouldn't be doing TDD. The problem (well, one of them, anyway) with writing all of your tests up front is that in any case where the requirements are non-trivial, your tests will be building in a lot of assumptions about the structure of the code you're test-driving. Big steps lead to missteps.
One of the keys of successful TDD involves taking small steps. Small steps mean fewer changes to back out when something goes wrong. Small steps mean you can more often get your head around the effects of the changes you're making. And because small steps are easier to take with confidence, they have the paradoxical effect of increasing your velocity.
The TDD cycle starts with requirements. Start by choosing a requirement you know how to define through tests immediately, in a few short steps. If you look at a requirement and you're not sure how to test it, or you think, "Yeah, but to do that, I'd need to [insert ill-defined steps] first", then you should either skip to another requirement that you know how to do, or you should break this requirement into smaller requirements that you know how to do.
Once you have that, you work in a short red-green-refactor cycle: Write a test that quantifies some part of the requirement ("red", because it fails, because it has no implementation to test yet), write any code that will pass the test ("green"), then rework the code to remove duplication, magic numbers, and other code smells ("refactor"). During the refactoring phase, you should continue working in small steps, frequently re-running the test to make sure you haven't broken anything. Continue this cycle until you can look your boss/client in the eye and call the requirement met.
Now that you have one simple piece of your system defined, you've opened up the list of requirements available to implement - requirements that are adjacent to or dependent on the one you just implemented can now be tested and implemented in smaller steps building on what you've already done.
So the upshot of all that is: Don't try to do all your tests at once. One (small) thing at a time.
The point of TDD is that you have to observe that test fails when feature is not yet implemented. So you have to write test before code.
When you get into the TDD rhythm you write one test at a time and make it work. Very short red-green-refactor cycles really feel the rhythm. That being said, there is nothing wrong with other approaches (and they may even make more sense for some types of problems) but typically the only thing you need to do about other tests you are thinking of is write them down (or have your pair if you are pair programming write them down) so you don't forget them. You have to do that anyway because you could forget about a test in the middle of writing a different test.
Do just enough tests to test 1 unit of code at a time.. then write the actual code until it passes the test.. rinse, wash, repeat until done.
If you find yourself needing to write many tests for one unit of code ( a method, a function etc) it might be a sign that you are trying to do too much in that unit... which in turn makes the unit dificult to test & to refactor at a later time.
I'm about to start out my first TDD (test-driven development) program, and I (naturally) have a TDD mental block..so I was wondering if someone could help guide me on where I should start a bit.
I'm creating a function that will read binary data from socket and parses its data into a class object.
As far as I see, there are 3 parts:
1) Logic to parse data
2) socket class
3) class object
What are the steps that I should take so that I could incrementally TDD? I definitely plan to first write the test before even implementing the function.
The issue in TDD is "design for testability"
First, you must have an interface against which to write tests.
To get there, you must have a rough idea of what your testable units are.
Some class, which is built by a function.
Some function, which reads from a socket and emits a class.
Second, given this rough interface, you formalize it into actual non-working class and function definitions.
Third, you start to write your tests -- knowing they'll compile but fail.
Part-way through this, you may start head-scratching about your function. How do you set up a socket for your function? That's a pain in the neck.
However, the interface you roughed out above isn't the law, it's just a good idea. What if your function took an array of bytes and created a class object? This is much, much easier to test.
So, revisit the steps, change the interface, write the non-working class and function, now write the tests.
Now you can fill in the class and the function until all your tests pass.
When you're done with this bit of testing, all you have to do is hook in a real socket. Do you trust the socket libraries? (Hint: you should) Not much to test here. If you don't trust the socket libraries, now you've got to provide a source for the data that you can run in a controlled fashion. That's a large pain.
Your split sounds reasonable. I would consider the two dependencies to be the input and output. Can you make them less dependent on concrete production code? For instance, can you make it read from a general stream of data instead of a socket? That would make it easier to pass in test data.
The creation of the return value could be harder to mock out, and may not be a problem anyway - is the logic used for the actual population of the resulting object reasonably straightforward (after the parsing)? For instance, is it basically just setting trivial properties? If so, I wouldn't bother trying to introduce a factory etc there - just feed in some test data and check the results.
First, start thinking "the testS", plural, rather than "the test", singular. You should expect to write more than one.
Second, if you have mental block, consider starting with a simpler challenge. Lower the difficulty until it's real easy to do, then move on to more substantial work.
For instance, assume you already have a byte array with the binary data, so you don't even need to think about sockets. All you need to write is something that takes in a byte[] and return an instance of your object. Can you write a test for that ?
If you still have mental block, lower it yet another notch. Assume your byte array is only going to contain default values anyway. So you don't even have to worry about the parsing, just about being able to return an instance of your object that has all values set to the defaults. Can you write a test for that ?
I imagine something like:
public void testFooReaderCanParseDefaultFoo() {
FooReader fr = new FooReader();
Foo myFoo = fr.buildFoo();
assertEquals(0, myFoo.bar());
}
That's rock bottom, right ? You're only testing the Foo constructor. But you can then move up to the next level:
public void testFooReaderGivenBytesBuildsFoo() {
FooReader fr = new FooReader();
byte[] fooData = {1};
fr.consumeBytes(fooData);
Foo myFoo = fr.buildFoo();
assertEquals(1, myFoo.bar());
}
And so on...
'The best testing framework is the application itself'
I believe that a common misconception amongst developers is, they mistakenly make a strong association between testing frameworks and TDD principles. I would advise re-reading the official docs on TDD; bearing in mind that, there is no real relationship between testing frameworks and TDD. After all, TDD is a paradigm not a framework.
Upon reading the wiki on TDD (https://en.wikipedia.org/wiki/Test-driven_development), I've come to realise that to an extent things are a little bit open to interpretation.
There are various personal styles of TDD mainly due to the fact that TDD principles are open to interpretation.
I'm not here to say anyone is wrong, but I would like to share my techniques with you and explain how they have served me well. Bear in mind that I have been programming for 36 years; making my programming habits very well evolved.
Code reuse is over rated. Reuse code too much and you'll end up with bad abstraction and it will become very difficult to fix or change something without it affecting something else. The obvious advantage being less code to manage.
Repeating too much code leads to code management problems and oversized code bases. However it does have the advantage of good separation of concerns (the ability to tweak, change and fix things without affecting other parts of the app).
Don't repeat/refactor too much, don't reuse too much. Code needs to be maintainable. It’s important to understand and respect the balance between code reuse and abstraction/separation of concerns.
When deciding whether to reuse code I base the decision on: .... Will the nature of this code change in context throughout the app codebase? If the answer is no, then I reuse it. If the answer is yes or I'm not sure, I repeat/refactor it. I will however revise my codebases from time to time and see if any of my repeated code can be merged without compromising separation of concerns/abstraction.
As far as my basic programming habits are concerned, I like to write the conditions (if then else switch case etc) first; test them, then fill the conditions with the code and test again. Keep in mind there's no rule that you have to do this in a unit test. I refer to this as the low level stuff.
Once my low level stuff is done, I'll either reuse the code or refactor it into another part of the app, but not after testing it very thoroughly. Problem with repeating/refactoring badly tested code is that, if it’s broken, you have to fix it in multiple places.
BDD To me is a natural follow on from TDD. Once my code base is well tested I can easily tweak behaviours by moving entire blocks of code around. Cool thing is about my programming habits is that sometimes I move code around and discover useful behaviours that I didn’t even intend. It can sometimes even be useful for rebranding stuff to seem like a completely different code base.
To this end my code bases tend to start out a bit slow and pick up momentum because as I advance toward the end of development I have more and more code to refactor from or reuse.
The advantages for me in the way that I code is that, I am able to take on very high levels of complexity as this is promoted by good separation of concerns. It’s also awesome for writing highly optimised code. However the well optimised code tends to be a bit bloated, but to my knowledge there is no way to write optimized code without a bit of bloating. If the app doesn't need high processor efficiency, there's nothing stopping me from de-bloating my code. I'm of the opinion that server side code should be optimised and most client side code normally doesn't require it.
Going back to the topic of testing frameworks, I use them to just save a bit of compiler time.
As far as following story boards is concerned, that comes naturally to me without actually considering it. I've noticed most devs develop in the natural order of story boards even when they are not available.
As a general separation of concerns strategy, in most apps I separate concerns based on UI forms. For example I’ll reuse code within a form and repeat/refactor across forms. This is only a generalistic rule. There are times when I have to think outside the box. Sometimes repeating code can serve well for making code processor efficient.
As a little addendum to my TDD habits; I do optimizations and fault tolerance last. I will try to avoid using try catch blocks as much as possible and write my code in such a way as to not need them. For example rather than catch a null, I will check for null, or rather than catch an index out of bounds, I will scrutinise my code so that it never happens. I find that error trapping too early in app development, leads to semantic errors (behavioural errors that don't crash the app). Semantic errors can be very hard to trace or even notice.
Well that’s my 10 cents. Hope it helps.
Test Driven Development ?
So, this means you should start with writing a test first.
Write a test which contains the code like 'how you want to use your class'. This class or method that you are going to test with this test, is not even there yet.
For instance, you could write a test first like this:
[Test]
public void CanReadDataFromSocket()
{
SocketReader r = new SocketReader( ... ); // create a socketreader instance which takes a socket or a mock-socket in its constructor
byte[] data = r.Read();
Assert.IsTrue (data.Length > 0);
}
For instance; I'm just making up an example here.
Next, once you're able to read data from a socket, you can start thinking on how you'll parse it, and write a test in where you use the 'Parser' class which takes the data that you've read, and outputs an instance of your data class.
etc...
Knowing where to start writing tests and when to stop writing tests while using TDD, is a common problem when starting out.
I have found that it can sometimes help to write an integration test first. Doing so will help create some of the common objects you will be using. It will also allow you to focus your thoughts and tests, since you will need to start writing tests to make the integration test pass.
When I was starting with TDD, I read these 3 rules by Uncle Bob that really helped me out:
You are not allowed to write any production code unless it is to
make a failing unit test pass.
You are not allowed to write any more of a unit test than is sufficient to fail; and compilation failures are failures.
You are not allowed to write any more production code than is sufficient to pass the one failing unit test.
In a shorter version it would be:
Write only enough of a unit test to fail.
Write only enough production code to make the failing unit test pass.
as you can see, this is very simple.
When doing TDD, how to tell "that's enough tests for this class / feature"?
I.e. when could you tell that you completed testing all edge cases?
With Test Driven Development, you’ll write a test before you write the code it tests. Once you’re written the code and the test passes, then it’s time to write another test. If you follow TDD correctly, you’ve written enough tests once you’re code does all that is required.
As for edge cases, let's take an example such as validating a parameter in a method. Before you add the parameter to you code, you create tests which verify the code will handle each case correctly. Then you can add the parameter and associated logic, and ensure the tests pass. If you think up more edge cases, then more tests can be added.
By taking it one step at a time, you won't have to worry about edge cases when you've finished writing your code, because you'll have already written the tests for them all. Of course, there's always human error, and you may miss something... When that situation occurs, it's time to add another test and then fix the code.
Kent Beck's advice is to write tests until fear turns into boredom. That is, until you're no longer afraid that anything will break, assuming you start with an appropriate level of fear.
On some level, it's a gut feeling of
"Am I confident that the tests will catch all the problems I can think of
now?"
On another level, you've already got a set of user or system requirements that must be met, so you could stop there.
While I do use code coverage to tell me if I didn't follow my TDD process and to find code that can be removed, I would not count code coverage as a useful way to know when to stop. Your code coverage could be 100%, but if you forgot to include a requirement, well, then you're not really done, are you.
Perhaps a misconception about TDD is that you have to know everything up front to test. This is misguided because the tests that result from the TDD process are like a breadcrumb trail. You know what has been tested in the past, and can guide you to an extent, but it won't tell you what to do next.
I think TDD could be thought of as an evolutionary process. That is, you start with your initial design and it's set of tests. As your code gets battered in production, you add more tests, and code that makes those tests pass. Each time you add a test here, and a test there, you're also doing TDD, and it doesn't cost all that much. You didn't know those cases existed when you wrote your first set of tests, but you gained the knowledge now, and can check for those problems at the touch of a button. This is the great power of TDD, and one reason why I advocate for it so much.
Well, when you can't think of any more failure cases that doesn't work as intended.
Part of TDD is to keep a list of things you want to implement, and problems with your current implementation... so when that list runs out, you are essentially done....
And remember, you can always go back and add tests when you discover bugs or new issues with the implementation.
that common sense, there no perfect answer. TDD goal is to remove fear, if you feel confident you tested it well enough go on...
Just don't forget that if you find a bug later on, write a test first to reproduce the bug, then correct it, so you will prevent future change to break it again!
Some people complain when they don't have X percent of coverage.... some test are useless, and 100% coverage does not mean you test everything that can make your code break, only the fact it wont break for the way you used it!
A test is a way of precisely describing something you want. Adding a test expands the scope of what you want, or adds details of what you want.
If you can't think of anything more that you want, or any refinements to what you want, then move on to something else. You can always come back later.
Tests in TDD are about covering the specification, in fact they can be a substitute for a specification. In TDD, tests are not about covering the code. They ensure the code covers the specification, because the code will fail a test if it doesn't cover the specification. Any extra code you have doesn't matter.
So you have enough tests when the tests look like they describe all the expectations that you or the stakeholders have.
maybe i missed something somewhere in the Agile/XP world, but my understanding of the process was that the developer and the customer specify the tests as part of the Feature. This allows the test cases to substitute for more formal requirements documentation, helps identify the use-cases for the feature, etc. So you're done testing and coding when all of these tests pass...plus any more edge cases that you think of along the way
Alberto Savoia says that "if all your tests pass, chances are that your test are not good enough". I think that it is a good way to think about tests: ask if you are doing edge cases, pass some unexpected parameter and so on. A good way to improve the quality of your tests is work with a pair - specially a tester - and get help about more test cases. Pair with testers is good because they have a different point of view.
Of course, you could use some tool to do mutation tests and get more confidence from your tests. I have used Jester and it improve both my tests and the way that I wrote them. Consider to use something like it.
Kind Regards
Theoretically you should cover all possible input combinations and test that the output is correct but sometimes it's just not worth it.
Many of the other comments have hit the nail on the head. Do you feel confident about the code you have written given your test coverage? As your code evolves do your tests still adequately cover it? Do your tests capture the intended behaviour and functionality for the component under test?
There must be a happy medium. As you add more and more test cases your tests may become brittle as what is considered an edge case continuously changes. Following many of the earlier suggestions it can be very helpful to get everything you can think of up front and then adding new tests as the software grows. This kind of organic grow can help your tests grow without all the effort up front.
I am not going to lie but I often get lazy when going back to write additional tests. I might miss that property that contains 0 code or the default constructor that I do not care about. Sometimes not being completely anal about the process can save you time n areas that are less then critical (the 100% code coverage myth).
You have to remember that the end goal is to get a top notch product out the door and not kill yourself testing. If you have that gut feeling like you are missing something then chances are you are have and that you need to add more tests.
Good luck and happy coding.
You could always use a test coverage tool like EMMA (http://emma.sourceforge.net/) or its Eclipse plugin EclEmma (http://www.eclemma.org/) or the like. Some developers believe that 100% test coverage is a worthy goal; others disagree.
Just try to come up with every way within reason that you could cause something to fail. Null values, values out of range, etc. Once you can't easily come up with anything, just continue on to something else.
If down the road you ever find a new bug or come up with a way, add the test.
It is not about code coverage. That is a dangerous metric, because code is "covered" long before it is "tested well".