Tag: Integration tests

Key Software Factory Tools in the Java World

Here are some popular free and/or freemium tools for creating a software factory for a Java project :

I’ve written about these build tools before.

Here’s a chart showing the relative popularity of these 3 tools.

There are many more unit test facilitators available for free, and I’ve developed some lesser-known open-source unit test facilitators myself.

  • Integration test facilitators
    • Arquillian – allows you to run a test on a Java EE server (either a remote server or one configured and launched by your test code)
    • OpenEJB – a lightweight EJB framework implementation that can be launched in a test
    • DBUnit – set up and clean up after tests that use real database connections
    • Docker – actually, Docker is a facilitator for just about any sort of automation you want to do, but I put it in the integration test category because it allows you to spin up a database or other server from a test.

Note: do not mix the Arquillian and OpenEJB together in the same test suite – jar conflicts can ensue when tests are run manually in Eclipse

There are surely other tools I’ve left out.  Feel free to mention your favorites in the comments.


Does TDD “damage” your design?

I recently came across a couple articles that challenged some of my beliefs about best practices.

In this article, Simon Brown makes the case for components tightly coupling a service with its data access implementation and for testing each component as a unit rather than testing the service with mocked-out data access. Brown also cites David Heinemeir Hansson, the creator of Rails, who has written a couple of incendiary articles discouraging isolated tests and even TDD in general. Heinemeir Hansson goes so far as to suggest that TDD results in “code that is warped out of shape solely to accomodate testing objectives.Ouch.

These are thought-provoking articles written by smart, accomplished engineers, but I disagree with them.

For those unfamiliar with the (volatile and sometimes confusing and controversial) terminology, isolated tests are tests which mock out dependencies of the unit under test. This is done both for performance reasons (which Heinemeir Hansson calls into question) and for focus on the unit (if a service calls the database and the test fails, is the problem in the service or the SQL or the database tables or the network connection?). There’s also a question of the difficulty of setting up and maintaining tests with database dependencies. There are tools for that, but there’s a learning curve and some set-up required (which hopefully can be Dockerized to make life easier). And there’s one more very important reason which I’ll get to later…

Both Brown and Heinemeir Hansson argue against adding what they consider unnecessary layers of indirection. If your design is test-driven, the need for unit tests will nudge you to de-couple things that Brown and Heinemeir Hansson think should remain coupled. The real dilemma is where should we put the inevitable complexity in any design? As an extreme example, to avoid all sorts of “unnecessary” code you could just put all your business logic into stored procedures in the database.

“Gang of Four” member Ralph Johnson described a paradox:

There is no theoretical reason that anything is hard to change about software. If you pick any one aspect of software then you can make it easy to change, but we don’t know how to make everything easy to change. Making something easy to change makes the overall system a little more complex, and making everything easy to change makes the entire system very complex. Complexity is what makes software hard to change. That, and duplication.

TDD, especially the “mockist” variety, nudges us to add layers of indirection to separate responsibilities cleanly. Johnson seems to be implying that doing this systematically can add unnecessary complexity to the system, making it harder to change, paradoxically undermining one of TDD’s goals.

I do not think that lots of loose coupling makes things harder to change. It does increase the number of interfaces, but it makes it easier to swap out implementations or to limit behavior changes to a single class.

And what about the complexity of the test code? Brown and Heinemeir Hansson seem to act as if reducing the complexity of the test code does not matter. Or rather, that you don’t need to write tests for code that’s hard to test because you should just expand the scope of the tests to do verification at the level of whole components.

Here’s where I get back to that other important reason why “isolated” tests are necessary: math. J.B. Rainsberger simply destroys the arguments of the kind that Brown and Heinemeir Hansson make and their emphasis on component-level tests. He points out that there’s an explosive multiplicative effect on the number of tests needed when you test classes in combination. For an oversimplified example, if your service class has 10 execution paths and its calls to your storage class have 10 execution paths on average, testing them as a component, you may need to write as may as 100 tests to get full coverage of the component. Testing them as separate units, you only need 20 tests to get the same coverage. Imagine your component has 10 interdependent classes like that… Do you have the developer bandwidth to write all those tests? If you do write them all, how easy is it to change something in your component? How many of those tests will break if you make one simple change?

So I reject the idea that TDD “damages” the design. If you think TDD would damage your design, maybe you just don’t know how bad your design is, because most of your code is not really tested.

As for Heinemeir Hansson’s contention that it’s outdated thinking to isolate tests from database access, he may be right about performance issues (not everyone has expensive development machines with fancy SSD drives, but there should be a way to run a modest number of database tests quickly). If a class’s single responsibility is closely linked to the database, I’m in favor of unit-testing it against a real database, but any other test that hits a real database should be considered an integration test. Brown proposes a re-shaped, “architecturally-aligned” testing pyramid with fewer unit tests and more integrated component tests. Because of the aforementioned combinatorial effect of coupling classes in the component, that approach would seem to require either writing (and frequently running) a lot more tests or releasing components which are not exhaustively tested.

Legacy Lexicon? Naming different types of tests

At a recent software craftsmanship meetup I attended, there was an hour-long group discussion of the definitions of the terms “unit test”, “integration test” and “acceptance test”. How can this be, 2 decades after Kent Beck started developing and using the automated test software that has now become xUnit, that the very people who are most interested in pursuing best practices in object-oriented software development have doubts or confusion about the meaning of these fundamental terms?

The confusion is, in fact, widespread. Even J.B. Rainsberger, one of the world’s finest experts on test-driven design, ran into problems with this lexical quicksand.

Unit Test

The term “unit test” comes from a paradigm of scope, but there is some disagreement of what that scope is. Some experts, such as Roy Osherove  and Michael Feathers, have tried to impose some precision on that notion of scope. Stack Overflow users seem to agree with them. There remains some ambiguity, however, as Martin Fowler has recognized and explained – particularly as a result of the differences between “mockist” and “classicist” testing approaches. Personally, I prefer Fowler’s more inclusive definition of unit tests (tests focused on a unit which assume that collaborators work – whether you mock them out or integrate them).

Integration Test vs. Integrated Test

Then there’s the term “integration test”. There is a paradigm of scope in this name, as well – the word “integration” implies combining multiple “unit” scopes (or at least combining 1 unit scope with a tool or service external to the code, such as a database). But is every test that involves more than 1 unit an integration test? There’s another paradigm involved, which is that there’s the notion of testing the integration of units rather than the logic of the units themselves. This is where Rainsberger mis-stepped. He now rightly makes a distinction between integration tests – tests which validate the integration of different components as well as databases, the file system, etc. – and integrated tests – tests which attempt to do the work of validating units without fully isolating those units (tests which he finds to be mostly counterproductive over time because they are often too heavy to use for thorough testing of the logic of individual units, and they give a false sense of security).

This is a more finessed approach than Osherove’s, who seems to say that any test which is not a “good” unit test by his definition is an integration test.

Acceptance Test

The third notion of scope is that of acceptance tests. The scope is the whole product (end-to-end), limiting the functionality tested to 1 user story.


So we have notions of 3 different categories of tests: unit, integration and acceptance. These 3 categories are not exhaustive. If we adhere to strict definitions and use Rainsberger’s term of “integrated tests” as a fourth category there are no longer ambiguities between unit and integration tests because those 2 categories of test serve different purposes (it’s no longer a question of scope). There remains an ambiguity between the notion of unit testing and integrated testing – over the notion of the boundaries of a unit (for example, testing a root aggregate may involve several non-mocked classes, but I would argue that it’s a unit test because the root aggregate and its aggregate elements form a single unit). Since Rainsberger has labeled integrated tests as often harmful (“a scam” in his words), defining this boundary can give a notion of the quality of testing.

As an aside, I find that sometimes a test can start as a unit test and then become an integrated test because of a useful refactoring. Enforcing SRP can have this effect. You have a classicist-style test for a method that eventually does too much. So you delegate part of the method’s implementation to another class.  Do you also need to rewrite the test to mock out the new delegate, even though the test passes as-is? Probably the answer is to keep the original test unchanged and add additional focused unit tests to the delegate. I suppose Osherove would say in this case that either the original test’s definition of a unit was too broad (so for him, it’s an integration test from the start), or else the refactoring merely made the unit span multiple classes (so it remains a unit test).

More Useful Terms?

Are these terms the most useful ones? Maybe not, especially given the confusion they engender.

Rainsberger prefers to promote the idea of collaboration tests and contract tests. Collaboration tests are mockist-style tests where a test verifies the interactions between the method under test and its collaborators (which are mocked or otherwise replaced by test doubles). Contract tests verify that a method, given certain inputs, produces a certain output (or possibly an internal state change that can be verified). Generally, the contract test applies to an interface or abstract class, (that which was mocked out in the collaboration tests) and can be applied to any concrete subtype of the abstract type under test. The 2 categories are complementary: You test collaborations to verify high-level services and then you use contract tests to verify in detail the functionality that was mocked out in the collaboration tests. I believe that some contract tests can (and often should) be integrated tests – for example focused tests that touch a database to verify low-level data model logic (which goes beyond just checking that the database is integrated). This is a pattern which I came to use spontaneously in my exploration of the hexagonal architecture.

Rainsberger also prefers the term microtests over unit tests. The term does seem to give a clearer notion of scope than “unit”.

In Fowler’s article, we see 2 other interesting categorizations.

There’s Jay Fields’s distinction between “solitary” and “sociable” tests. In solitary tests, there are no collaborators which are not replaced by test doubles. Sociable tests generally involve at least one real collaborator.

Fowler also distinguishes between 2 test suites: a “compile” suite (run on every build) and a “commit” suite (run before a commit, or in continuous integration). This is a useful idea for TDD, and the categorization is less ambiguous: if it runs fast, it’s in “compile”, otherwise it’s in “commit”. The only ambiguity is in the speed threshold separating the 2 categories, and that’s more a question of practicality and personal or team preference – there isn’t a “right answer”.

Catch-all terms

There’s are also catch-all terms if you’re not sure which type of test you have:

  •  developer tests – this term is obviously about who is responsible for creating and maintaining the test rather than the purpose or scope of the test.
  • automated tests – this term is obviously about how the tests are performed, so it would include developer tests and, for example, selenium tests created by Q.A.

A picture’s worth 1000 words

Using Martin Fowler’s more inclusive view of “unit tests”:


The colored area seems to be a source of some confusion – if you have a collaborating or delegate class that is not mocked out it can still be considered a unit test. Feathers does not address this area in his definition. Osherove does: “A unit of work can span a single method, a whole class or multiple classes…”  So a unit test can be an integrated test. Whether it should is a different question based on notions of good design and the actual execution speed of the test.

London Mockists to the Rescue?

In “Growing Object-Oriented Software, Guided by Tests”, Steve Freeman and Nat Pryce manage, using simple questions, to define the major test scopes without getting hung up on details of things like unit boundaries:

  • Acceptance: Does the whole system work?
  • Integration: Does our code work against code we can’t change?
  • Unit: Do our objects do the right thing, are they convenient to work with?

That seems like enough of a definition to do some useful tests.


In conclusion, don’t lose sleep over these definitions or let them stop you from doing tests.  There exist terms which are clear and precise enough to describe the good practices you need, and we can live with some gray areas where the most commonly used terms are concerned. Just be careful when you’re discussing tests to make sure that everyone in the discussion has the same understanding of the terms.



I just discovered another interesting approach to this topic, by Simon Brown.