I thought at first the compare option only appears for a test if the assertequals is between 2 strings, which makes sense. I believe i have also fired a failNotEquals(String1,String2) and the compare option comes up as well. I have done this when the object does not implement equals or perhaps i wish to compare for equality using my own rules and failing if that fails. However i have noticed a few times here and there sometimes failNotequals(String,String) does not enable the "compare" option. Am i missing something ???
CLARIFICATION of COMPARE option
The >compare< option is a menu option that is available when one right clicks on a failed junit item from the gui where it creates a tree with items for each "test". Often theres also a >print stack trace< option.
You get the "compare" option, when the end result of the test is a junit.framework.ComparisonFailure object. In that case you can see a visual comparison of the two objects (Strings for example) and check how they differ from each other.
Other types of results, such as a java.lang.IllegalAccessError, aren't parsed to that effect, as Eclipse doesn't know (and cannot deduce) that you were comparing two objects that lead to such a result, so it doesn't offer you the same visual boons.
I am not entirely sure what you mean by
failNotEquals does not enable the "compare" option
Here are a couple of thoughts.
failNotEquals takes three arguments, not two:
failNotEquals(message, expected, actual);
Even if strings would print out the same, they are NOT the same object. You need to tell JUnit how to compare them.
Consider this small, working test case.
import junit.framework.TestCase;
public class DemoTest extends TestCase {
public void testSomething() {
String a = "Hello";
assertTrue("Strings should be the same", "Hello".equals(a));
failNotEquals("Strings should be the same", "Hello", a);
}
}
The assertTrue works, but the failNotEquals does not.
The assertTrue is probably what you want. The "Hello".equals(a) will compare the strings properly. You can also use a equalsIgnoreCase here.
I'm guessing that the failNotEquals is probably close to what you are using. It fails with a java.lang.IllegalAccessError.
Related
I'm currently working on my functional programming - I am fairly new to it. Am i using Options correctly here? I feel pretty insecure on my skills currently. I want my code to be as safe as possible - Can any one point out what am I doing wrong here or is it not that bad? My code is pretty straight forward here:
def main(args: Array[String]): Unit =
{
val file = "myFile.txt"
val myGame = Game(file) //I have my game that returns an Option here
if(myGame.isDefined) //Check if I indeed past a .txt file
{
val solutions = myGame.get.getAllSolutions() //This returns options as well
if(solutions.isDefined) //Is it possible to solve the puzzle(crossword)
{
for(i <- solutions.get){ //print all solutions to the crossword
i.solvedCrossword foreach println
}
}
}
}
-Thanks!! ^^
When using Option, it is recommended to use match case instead of calling 'isDefined' and 'get'
Instead of the java style for loop, use higher-order function:
myGame match {
case Some(allSolutions) =>
val solutions = allSolutions.getAllSolutions
solutions.foreach(_.solvedCrossword.foreach(println))
case None =>
}
As a rule of thumb, you can think of Option as a replacement for Java's null pointer. That is, in cases where you might want to use null in Java, it often makes sense to use Option in Scala.
Your Game() function uses None to represent errors. So you're not really using it as a replacement for null (at least I'd consider it poor practice for an equivalent Java method to return null there instead of throwing an exception), but as a replacement for exceptions. That's not a good use of Option because it loses error information: you can no longer differentiate between the file not existing, the file being in the wrong format or other types of errors.
Instead you should use Either. Either consists of the cases Left and Right where Right is like Option's Some, but Left differs from None in that it also takes an argument. Here that argument can be used to store information about the error. So you can create a case class containing the possible types of errors and use that as an argument to Left. Or, if you never need to handle the errors differently, but just present them to the user, you can use a string with the error message as the argument to Left instead of case classes.
In getAllSolutions you're just using None as a replacement for the empty list. That's unnecessary because the empty list needs no replacement. It's perfectly fine to just return an empty list when there are no solutions.
When it comes to interacting with the Options, you're using isDefined + get, which is a bit of an anti pattern. get can be used as a shortcut if you know that the option you have is never None, but should generally be avoided. isDefined should generally only be used in situations where you need to know whether an option contains a value, but don't need to know the value.
In cases where you need to know both whether there is a value and what that value is, you should either use pattern matching or one of Option's higher-order functions, such as map, flatMap, getOrElse (which is kind of a higher-order function if you squint a bit and consider by-name arguments as kind-of like functions). For cases where you want to do something with the value if there is one and do nothing otherwise, you can use foreach (or equivalently a for loop), but note that you really shouldn't do nothing in the error case here. You should tell the user about the error instead.
If all you need here is to print it in case all is good, you can use for-comprehension which is considered quite idiomatic Scala way
for {
myGame <- Game("mFile.txt")
solutions <- myGame.getAllSolutions()
solution <- solutions
crossword <- solution.solvedCrossword
} println(crossword)
I'm new to BDD, even to whole testing world.
I'm trying to take BDD practices when writing a simple linear algebra library in swift. So there would be many value object types like Matrix, Vector etc. When writing code, I suppose I still need to stick to the TDD principle (am I right?):
Not writing any single line of code without a failing test
To implement a value object type, I need to make it conform to Equatable protocol and implement its == operator. This is adding code, so I need a failing test. How to write spec for this kinda scenarios ?
One may suggest some approach like:
describe("Matrix") {
it("should be value object") {
let aMatrix = Matrix<Double>(rows: 3, cols:2)
let sameMatrix = Matrix<Double>(rows: 3, cols:2)
expect(sameMatrix) == aMatrix
let differentMatrix = Matrix<Double>(rows: 4, cols: 2)
expect(differentMatrix) != aMatrix
}
}
This would be an ugly boilerplate for two reasons:
There may be plenty of value object types and I need to repeat it for all of them
There may be plenty of cases that would cause two objects being not equal. Taking the spec above for example, an implementation of == like return lhs.rows == rhs.rows would pass the test. In order to reveal this "bug", I need to add another expectation like expect(matrixWithDifferentColmunCount) != aMatrix. And again, this kinda repetition happens for all value object types.
So, how should I test this "isEqual" ( or operator== ) method elegantly ? or shouldn't I test it at all ?
I'm using swift and Quick for testing framework. Quick provides a mechanism called SharedExample to reduce boilerplates. But since swift is a static typing language and Quick's shared example doesn't support generics, I can't directly use a shared example to test value objects.
I came up with a workaround but don't consider it as an elegant one.
Elegance is the enemy of test suites. Test suites are boring. Test suites are repetitive. Test suites are not "DRY." The more clever you make your test suites, the more you try to avoid boilerplate, the more you are testing your test infrastructure instead of your code.
The rule of BDD is to write the test before you write the code. It's a small amount of test code because it's testing a small amount of live code; you just write it.
Yes, that can be taken too far, and I'm not saying you never use a helper function. But when you find yourself refactoring your test suite, you need to ask yourself what the test suite was for.
As a side note, your test doesn't test what it says it does. You're testing that identical constructors create Equal objects and non-identical constructors create non-Equal objects (which in principle is two tests). This doesn't test at all that it's a value object (though it's a perfectly fine thing to test). This isn't a huge deal. Don't let testing philosophy get in the way of useful testing; but it's good to have your titles match your test intent.
Im working with scalatest and scalacheck, alsso working with FeatureSpec.
I have a generator class that generate object for me that looks something like this:
object InvoiceGen {
def myObj = for {
country <- Gen.oneOf(Seq("France", "Germany", "United Kingdom", "Austria"))
type <- Gen.oneOf(Seq("Communication", "Restaurants", "Parking"))
amount <- Gen.choose(100, 4999)
number <- Gen.choose(1, 10000)
valid <- Arbitrary.arbitrary[Boolean]
} yield SomeObject(country, type, "1/1/2014", amount,number.toString, 35, "something", documentTypeValid, valid, "")
Now, I have the testing class which works with FeatureSpec and everything that I need to run the tests.
In this class I have scenarios, and in each scenario I want to generate a different object.
The thing is from what I understand is that to generate object is better to use forAll func, but for all will not sure to bring you an object so you can add minSuccessful(1) to make sure you get at list 1 obj....
I did it like this and it works:
scenario("some scenario") {
forAll(MyGen.myObj, minSuccessful(1)) { someObject =>
Given("A connection to the system")
loginActions shouldBe 'Connected
When("something")
//blabla
Then("something should happened")
//blabla
}
}
but im not sure exactly what it means.
What I want is to generate an invoice each scenario and do some actions on it...
im not sure why i care if the generation work or didnt work...i just want a generated object to work with.
TL;DR: To get one object, and only one, use myObj.sample.get. Unless your generator is doing something fancy that's perfectly safe and won't blow up.
I presume that your intention is to run some kind of integration/acceptance test with some randomly generated domain object—in other words (ab-)use scalacheck as a simple data generator—and you hope that minSuccessful(1) would ensure that the test only runs once.
Be aware that this is not the case!. scalacheck will run your test multiple times if it fails, to try and shrink the input data to a minimal counterexample.
If you'd like to ensure that your test runs only once you must use sample.
However, if running the test multiple times is fine, prefer minSuccessful(1) to "succeed fast" but still profit from minimized counterexamples in case the test fails.
Gen.sample returns an option because generators can fail:
ScalaCheck generators can fail, for instance if you're adding a filter (listingGen.suchThat(...)), and that failure is modeled with the Option type.
But:
[…] if you're sure that your generator never will fail, you can simply call Option.get like you do in your example above. Or you can use Option.getOrElse to replace None with a default value.
Generally if your generator is simple, i.e. does not use generators that could fail and does not use any filters on its own, it's perfectly safe to just call .get on the option returned by .sample. I've been doing that in the past and never had problems with it. If your generators frequently return None from .sample they'd likely make scalacheck fail to successfully generate values as well.
If all that you want is a single object use Gen.sample.get.
minSuccessful has a very different meaning: It's the minimal number of successful tests that scalacheck runs—which by no means implies
that scalacheck takes only a single value out of the generator, or
that the test runs only once.
With minSuccessful(1) scalacheck wants one successful test. It'll take samples out of the generator until the test runs at least once—i.e. if you filter the generated values with whenever in your test body scalacheck will take samples as long as whenever discards them.
If the test passes scalacheck is happy and won't run the test a second time.
However if the test fails scalacheck will try and produce a minimal example to fail the test. It'll shrink the input data and run the test as long as it fails and then provides you with the minimized counter example rather than the actual input that triggered the initial failure.
That's an important property of property testing as it helps you to discover bugs: The original data is frequently too large to lend itself for debugging. Minimizing it helps you discover the piece of input data that actually triggers the failure, i.e. corner cases like empty strings that you didn't think of.
I think the way you want to use Scalacheck (generate only one object and execute the test for it) defeats the purpose of property-based testing. Let me explain a bit in detail:
In classical unit-testing, you would generate your system under test, be it an object or a system of dependent objects, with some fixed data. This could e.g. be strings like "foo" and "bar" or, if you needed a name, you would use something like "John Doe". For integers and other data, you can also randomly choose some values.
The main advantage is that these are "plain" values—you can directly see them in the code and correlate them with the output of a failed test. The big disadvantage is that the tests will only ever run with the values you specified, which in turn means that your code is also only tested with these values.
In contrast, property-based testing allows you to just describe how the data should look like (e.g. "a positive integer", "a string of maximum 20 characters"). The testing framework will then—with the help of generators—generate a number of matching objects and execute the test for all of them. This way, you can be more sure that your code will actually be correct for different inputs, which after all is the purpose of testing: to check if your code does what it should for the possible inputs.
I never really worked with Scalacheck, but a colleague explained it to me that it also tries to cover edge-cases, e.g. putting in a 0 and MAX_INT for a positive integer, or an empty string for the aforementioned string with max. 20 characters.
So, to sum it up: Running a property-based test only once for one generic object is the wrong thing to do. Instead, once you have the generator infrastructure in place, embrace the advantage you then have and let your code be checked a lot more times!
Let's say I have a non-sealed trait, Foo, and throughout my code I define some Objects that extend Foo.
Is there a way that I can, at compile time, look up all objects that extend Foo and print out some information about them (like printing out a string literal I have in a val?)
If so, how? If not, why not?
Seems like an obscure feature to have and it has problems since a lot of times only a few pieces of your code are re-compiled (and it only get's worse with libraries and dependencies). If I where you, I would just "find in files" for extends Foo or with Foo and check the results. You can even do a small script with regex to extract your val for each result if you are willing to do that work.
I'm working on an expression evaluator. There is an evaluate() function which is called many times depending on the complexity of the expression processed.
I need to break and investigate when this method returns null. There are many paths and return statements.
It is possible to break on exit method event but I can't find how to put a condition about the value returned.
I got stuck in that frustration too. One can inspect (and write conditions) on named variables, but not on something unnamed like a return value. Here are some ideas (for whoever might be interested):
One could include something like evaluate() == null in the breakpoint's condition. Tests performed (Eclipse 4.4) show that in such a case, the function will be performed again for the breakpoint purposes, but this time with the breakpoint disabled. So you will avoid a stack overflow situation, at least. Whether this would be useful, depends on the nature of the function under consideration - will it return the same value at breakpoint time as at run time? (Some s[a|i]mple code to test:)
class TestBreakpoint {
int counter = 0;
boolean eval() { /* <== breakpoint here, [x]on exit, [x]condition: eval()==false */
System.out.println("Iteration " + ++counter);
return true;
}
public static void main(String[] args) {
TestBreakpoint app = new TestBreakpoint();
System.out.println("STARTED");
app.eval();
System.out.println("STOPPED");
}
}
// RESULTS:
// Normal run: shows 1 iteration of eval()
// Debug run: shows 2 iterations of eval(), no stack overflow, no stop on breakpoint
Another way to make it easier (to potentially do debugging in future) would be to have coding conventions (or personal coding style) that require one to declare a local variable that is set inside the function, and returned only once at the end. E.g.:
public MyType evaluate() {
MyType result = null;
if (conditionA) result = new MyType('A');
else if (conditionB) result = new MyType ('B');
return result;
}
Then you can at least do an exit breakpoint with a condition like result == null. However, I agree that this is unnecessarily verbose for simple functions, is a bit contrary to flow that the language allows, and can only be enforced manually. (Personally, I do use this convention sometimes for more complex functions (the name result 'reserved' just for this use), where it may make things clearer, but not for simple functions. But it's difficult to draw the line; just this morning had to step through a simple function to see which of 3 possible cases was the one fired. For today's complex systems, one wants to avoid stepping.)
Barring the above, you would need to modify your code on a case by case basis as in the previous point for the single function to assign your return value to some variable, which you can test. If some work policy disallows you to make such non-functional changes, one is quite stuck... It is of course also possible that such a rewrite could result in a bug inadvertently being resolved, if the original code was a bit convoluted, so beware of reverting to the original after debugging, only to find that the bug is now back.
You didn't say what language you were working in. If it's Java or C++ you can set a condition on a Method (or Function) breakpoint using the breakpoint properties. Here are images showing both cases.
In the Java example you would unclik Entry and put a check in Exit.
Java Method Breakpoint Properties Dialog
!
C++ Function Breakpoint Properties Dialog
This is not yet supported by the Eclipse debugger and added as an enhancement request. I'd appreciate if you vote for it.
https://bugs.eclipse.org/bugs/show_bug.cgi?id=425744