The first was that I worked on a rewrite of something (using GWT no less; it was more than a decade ago) and they decided to have a lot of test coverage and test requirements. That's fine but they way it was mandated and implemented, everybody just testing their service and DIed a bunch of mocks in.
The results were entirely predictable. The entire system was incredibly brittle and a service that existed for only 8 weeks behaved like legacy code. You could spend half a day fixing mocks in tests for a 30 minute change just because you switched backend services, changed the order of calls or just ended up calling a given service more times than expected. It was horrible and a complete waste of time.
Even the DI aspect of this was horrible because everything used Guice andd there wer emodules that installed modules that installed modules and modifying those to return mocks in a test environment was a massive effort that typically resulted in having a different environment (and injector) for test code vs production code so what are you actually testing?
The second was that about this time the Java engineers at the company went on a massive boondoggle to decide on whether to use (and mandate) EasyMock vs Mockito. This was additionally a waste of time. Regardless of the relative merits of either, there's really not that much difference. At no point is it worth completely changing your mocking framework in existing code. Who knows how many engineering man-yars were wasted on this.
Mocking encourages bad habits and a false sense of security. The solution is to have dummy versions of services and interfaces that have minimal correct behavior. So you might have a dummy Identity service that does simple lookups on an ID for permissions or metadata. If that's not what you're testing and you just need it to run a test, doing that with a mock is just wrong on so many levels.
I've basically never used mocks since, so much so that I find anyone who is strongly in favor of mocks or has strong opinions on mocking frameworks to be a huge red flag.
That's mocks in a nutshell. What other way would you use mocks?
Imagine one of your tests is if the user deletes their account. What pattern of calls should it make? You don't really care other than the record being deleted (or marked as deleted, depending on retention policy) after you're done.
In the mock world you might mock out calls like deleteUserByID and make suer it's called.
In the fake world, you simply check that the user record is deleted (or marked as such) after the test. You don't really care about what sequence of calls made that happen.
That may sound trivial but it gets less trivial the more complex your example is. Imagine instead you want to clear out all users who are marked for deletion. If you think about the SQL for that you might do a DELETE ... WHERE call so your API call might look like that. But if the logic is more complicated? Where if there's a change where EU and NA users have different retention periods or logging requirements so they're suddenly handled differently?
In a mokcing world you would have to change all your expected mocks. In fact, implementing this change might require fixing a ton of tests you don't care about at all and aren't really being broken by the change regardless.
In a fake world, you're testing what the data looks like after you're done, not the specific steps it took to get there.
Now those are pretty simple examples because there's not much to do the arguments used and no return values to speak of. Your code might branch differently based on those values, which then changes what calls to expects and with what values.
You're testing implementation details in a really time-consuming yet brittle way.
If the dependencies are proper interfaces, I don't care if it's a fake or a mock, as long as the interface is called with the correct parameters. Precisely because I don't want to test the implementation details. The assumption (correctly so) is that the interface provides a contract I can rely on.
In you example, the brittleness simply moves from mocks to data setup for the fake.
This is most obvious with complex interfaces where there are multiple ways to call the dependency that do the same thing. For example if my dependency was an SQL library, I could call it with a string such as `SELECT name, id FROM ...`, or `SELECT id, name FROM ...`. For the dependency itself, these two strings are essentially equivalent. They'll return results in a different order, but as long as the calling code parses those results in the right order, it doesn't matter which option I go for, at least as far as my tests are concerned.
So if I write a test that checks that the dependency was carried with `SELECT name, id FROM ...`, and later I decide that the code looks cleaner the other way around, then my test will break, even though the code still works. This is a bad test - tests should only fail if there is a bug and the code is not working as expected.
In practice, you probably aren't mocking SQL calls directly, but a lot of complex dependencies have this feature where there are multiple ways to skin a cat, but you're only interested in whether the cat got skinned. I had this most recently using websockets in Node - there are different ways of checking, say, the state of the socket, and you don't want to write tests that depend on a specific method because you might later choose a different method that is completely equivalent, and you don't want your tests to start failing because of that.
Check function XYZ is called, return abc when XYZ is called etc are the bad kind that people were bit badly by.
The good kind are a minimally correct fake implementation that doesn't really need any mocking library to build.
Tests should not be brittle and rigidly restate the order of function calls and expected responses. That's a whole lot of ceremony that doesn't really add confidence in the code because it does not catch many classes of errors, and requires pointless updates to match the implementation 1-1 everytime it is updated. It's effectively just writing the implementation twice, if you squint at it a bit.
Why is a minimally correct fake any better than a mock in this context?
Mocks are not really about order of calls unless you are talking about different return values on different invocations. A fake simply moves the cheese to setting up data correctly, as your tests and logic change.
Not a huge difference either way.
(And IMO this should only be done for heavyweight or difficult to precisely control components of the system where necessary to improve test runtime or expand the range of testable conditions. Always prefer testing as close to the real system as reasonably practical)
Of course getting overly pedantic leads to its own issues, much like the distinctions between types of tests.
At my last Java job I used to commonly say things like "mocks are a smell", and avoided Mockito like GP, though it was occasionally useful. PowerMock was also sometimes used because it lets you get into the innards of anything without changing any code, but much more rarely. Ideally you don't need a test double at all.
If you aren’t doing this with mocks then you’re doing mocks wrong.
People often use the word "mock" to describe all of these things interchangeably², and mocking frameworks can be useful for writing stubs or fakes. However, I think it's important to distinguish between them, because tests that use mocks (as distinct from stubs and fakes) are tightly coupled to implementation, which makes them very fragile. Stubs are fine, and fakes are fine when stubs aren't enough, but mocks are just a bad idea.
[1]: https://martinfowler.com/articles/mocksArentStubs.html
[2]: The generic term Fowler prefers is "test double."
Going further, there’s the whole test containers movement of having a real version of your dependency present for your tests. Of course, in a microservices world, bringing up the whole network of dependencies is extremely complicated and likely not warranted.
It is a hassle a lot of the time, but I see it as a necessary evil.
That said, there is a massive difference between writing mocks and using a mocking library like Mockito — just like there is a difference between using dependency injection and building your application around a DI framework.
How to reconcile the differences in this discussion?
The comment at the root of the thread said "my experience with mocks is they were over-specified and lead to fragile services, even for fresh codebases. Using a 'fake' version of the service is better". The reply then said "if mocking doesn't provide a fake, it's not 'mocking'".
I'm wary of blanket sentiments like "if you ended up with a bad result, you weren't mocking". -- Is it the case that libraries like mockito are mostly used badly, but that correct use of them provides a good way of implementing robust 'fake services'?
For example, let's say you want to test that some handler is properly adding data to a cache. IMO the traditional mock approach that is supported by mocking libraries is to go take your RedisCache implementation and create a dummy that does nothing, then add assertions that say, the `set` method gets called with some set of arguments. You can add return values to the mock too, but I think this is mainly meant to be in service of just making the code run and not actually implementing anything.
Meanwhile, you could always make a minimal "test" implementation (I think these are sometimes called "fakes", traditionally, though I think this nomenclature is even more confusing) of your Cache interface that actually does behave like an in-memory cache, then your test could assert as to its contents. Doing this doesn't require a "mocking" library, and in this case, what you're making is not really a "mock" - it is, in fact, a full implementation of the interface, that you could use outside of tests (e.g. in a development server.) I think this can be a pretty good middle ground in some scenarios, especially since it plays along well with in-process tools like fake clocks/timers in languages like Go and JavaScript.
Despite the pitfalls, I mostly prefer to just use the actual implementations where possible, and for this I like testcontainers. Most webserver projects I write/work on naturally require a container runtime for development for other reasons, and testcontainers is glue that can use that existing container runtime setup (be it Docker or Podman) to pretty rapidly bootstrap test or dev service dependencies on-demand. With a little bit of manual effort, you can make it so that your normal test runner (e.g. `go test ./...`) can run tests normally, and automatically skip anything that requires a real service dependency in the event that there is no Docker socket available. (Though obviously, in a real setup, you'd also want a way to force the tests to be enabled, so that you can hopefully avoid an oopsie where CI isn't actually running your tests due to a regression.)
edit: of course google was an unusual case because you had access to all the source code. I daresay there are cases where only a mock will work because you can't satisfy type signatures with a fake.
It should never be the first tool. But when you need it, it’s very useful.
I've been using Mockito for about 4 years, all in Kotlin. I always found it to be "plenty good" for like 99% of the cases I needed it; and things more complicated or confusing or messy were usually my fault (poor separation of concerns, etc).
I regularly found it quite helpful in both its spy() and mock() functionality.
I never found it meaningfully more or less useful than MockK, though I have heard MockK is the "one that's better for Kotlin". It's mostly just vocabulary changes for me, the user.
I'm going to have to monitor Mockito's future and see if I'll need to swap to MockK at some point if Mockito becomes unmaintained.
If I was OP I'd retire happy knowing that a very thankless job is well done! Given what it does: the more outrage the better. Projects like Mockito call out the lazy and indolent for whom they are and the hissing and spitting in return can simply be laughed at.
10 years this bloke has given his time and effort to help people. He states: nearly a third of his life.
I'll raise a glass and say "was hale" or perhaps wassail as an Englander might.
1. Kotlin is a hack and 2. Rust is more fun.
Pretty understandable why one would simply want to move on to greener pastures.
Here are some examples that have hit the graveyard: It's been 2 years since exception handling in switch was proposed [0], 3 years since null-restricted types were proposed [1], 4 years since string templates [2], 8 years since concise method bodies [3], and 11 years for JSON parsing [4].
[0] https://inside.java/2023/12/15/switch-case-effect/
[1] https://openjdk.org/jeps/8303099
[2] https://openjdk.org/jeps/430
Based on your other comment you prefer "fat" languages like kotlin and C# - and that's fair. I find languages with less, but more powerful features far more elegant and while Java has its fair share of historic warts, modern additions are made in a very smart way.
E.g. switch expressions seamlessly support sum and product types, meanwhile kotlin's `when` really is just syntactic sugar.
All in all, with too many features you have to support and understand the complete matrix of their interactions as well, and that gets complicated quickly. And Kotlin is growing towards that.
PS: personally I really like Swift, I would suggest giving it a try for fun
I don’t think it’s for me though. It’s very Apple centric and I’m a Windows gamer and PowerShell user at heart.
Java was stagnant and ripe for being kicked off the top.
Scala was the hack that showed why Java was starting to suck but Scala suffered from no direction. Every single idea a PhD ever had was implemented in the language with no thought other than it seems cool to be able to do that too. Which is why all the Scala codebases fell apart, because you could write anything, anyway you want, and it was impossible to maintain without extremely strict guidelines on what parts of the language you were allowed to use. Also the build times were atrocious.
Kotlin designers evaluated language features across the ecosystem and chose what made sense to make Java better when it came out and now has easily surpassed Java. They are still thoughtful in what they choose to add to the language and it is now very powerful. However they smartly imitate Python by having clear guidelines on what choices you should be making when writing code so that other developers can easily dive in.
Well, I absolutely disagree with this take. Scala actually builds on top of a couple of its powerful primitives. Especially Scala 3 is a beautiful language.
The problem is, engineers love to solve problems, and the funnest types of problems are hypothetical ones!
Yep, I was guiltily of taking DI and writing a spider web of code. It's not the tools fault, it was my attitude. I _wanted_ something hard to work on, so I created something hard to work on. Nowadays, my team and I work on a 4-5 layer deep limit and our code base is tight, consistent, and has near 99% test coverage naturally. We use mock testing for testing the single class, and of course integration test for testing requirements. Not everyone will do it this way, and that's fine, but the most important thing is actually just creating a plan and sticking to it so as to be consistent.
In the end, don't blame the tool, when you (or your coworkers) simply lack discipline.
You should be using it in rare cases when you want to verify very complex code that needs to be working with strict requirements (like calling order is specified, or some calls cannot be made during execution of the method).
Usually it is used for pointless unit tests of simple intermediary layers to test if call is delegated correctly to deeper layer. Those tests usually have negative value (they test very little but make any modification much harder).
This is kinda how we build software right? A little bit of "our logic" (calculation), represented as objects/actors/modules which "do things", but intermingled with million-LoC dependencies like databases and web servers.
After a while it gets frustrating setting up the robot hand and OCR equipment for each test case. Maybe it's just easier to test manually, or skip testing entirely.
At this point you can have an epiphany, and realise you only care about the numbers going in and out of the calculator, not the button pushes and pixels.
Mockito swoops in and prevents you from having that epiphany, by making it easier to keep doing things the stupid way.
Instead isolating the calculation from any IO, you can now write things like: when(finger.pushbutton(1)).then(calculator.setState(1)) when(calculator.setAnswer(3)).then(camera.setOcr(3))
(I've mostly worked in Java, but it seems like other languages typically don't let you intercept calls and responses this way)
I’ve been on projects where mocking _literally made the project less reliable_ because people ended up “testing” against mocks that didn’t accurately reflect the behavior of the real APIs.
It left us with functionality that wasn’t actually tested and resulted in real bugs and regressions that shipped.
Mocking is one of these weird programmer pop-culture memetic viruses that spread in the early 2000s and achieved complete victory in the 2010s, like Agile and OOP, and now there are entire generations of devs who it’s not that they’re making a bad or a poorly argued choice, it’s that they literally don’t even know there are other ways of thinking about these problems because these ideas have sucked all the oxygen out of the room.
Ha.
I think there's room to argue "Agile" is a popular bastardisation of what's meant by "agile software development", and with "OOP" we got the lame Java interpretation rather than the sophisticated Smalltalk interpretation. -- Or I might think that these ideas aren't that good if their poor imitations win out over the "proper" ideas.
With mocking.. I'm willing to be curious that there's some good/effective way of doing it. But the idea of "you're just testing that the compiler works" comes to mind.
Testing is hard. I’ve tried with AI today: No, it is still not capable of handling that kind of (straightforward) task (Using Claude).
doTheThing(foo: Fooable) { ... }
So Mockito and friends are a nice alternative to that.
That is just my experience and opinion though, and there are definitely more valid or equally valid alternatives.
But this name is weird in the specific language it’s imitating (both the -ito termination for diminutives and the drink on which I assumed the name is based are Spanish).
I don't know why owners/maintainers show grace like this.
For me; I would say I'm done and hand it over or just archive the repo.
Hope Tim finds a measure of sanity after he steps down.
Id like to hear the platform team's perspective on this. As it stands, it is a pretty sad state of affairs that such a prominent library in the ecosystem was made out to be the scapegoat for the adoption of a platform change. It is not a healthy thing to treat the library maintainer community like this.
Wouldn't this hold back enterprise adoption, the same way breaking changes meant that Java 8 was widely used for a long time?
Most places are just about getting rid of 8 for 17.
If you've got a running java process on your local machine right now, you can use 'jconsole' to see the stack traces of all threads, inspect various memory statistics, trigger an immediate garbage collection or heap dump, and so on. And of course, if the tool is an instrumenting profiler - it needs the power to modify the running code, to insert its instrumentation. Obviously you need certain permissions on the host to do this - just like attaching gdb to a running process.
This capability is used not just by for profiling, debugging and instrumentation but also by mockito to do its thing.
Java 21 introduced a warning [1] saying this will be disabled in a forthcoming version, unless the process is started with '-XX:+EnableDynamicAgentLoading' - whereas previously it was enabled by default and '-XX:+DisableAttachMechanism' was used to disable it.
The goal of doing this is "platform integrity" - preventing the attachment of debugging tools is useful in applications like DRM.
Spy's on the other hand, are a pain in the neck. I think they should be good in theory, but in practice they are difficult, the debuggers really don't work correctly, setting breakpoints, stepping, etc, is just broken in many cases. Would love to know if this is just a difficult bug, or something that is baked into spying.
Also, F Kotlin and their approach of "we'll reinvent the wheel with slightly different syntax and call it a new thing". Good riddance I say, let them implement their mockk, or whatever it is called, with ridiculous "fluent" syntax.
90% of the time, needing to use a mock is one of the clearest code warning smells you have of there being an issue in the design your code.
It took a while, but the industry seems to be finally (although slowly) coming to this realization. And hopefully with it almost all of this can go away.
What you're describing is a very limited subset of testing, which presumably is fine for the projects you work on, but that experience does not generalise well.
Integration testing is of course useful, but generally one would want to create unit tests for every part of the code, and by definition it's not a unit test if hits multiple parts of the code simultaneously.
Apart from that, databases and file access may be fast but they still take resources and time to spin up; beyond a certain project and team size, it's far cheaper to mock those things. With a mock you can also easily simulate failure cases, bad data, etc. - how do you test for file access issues, or the database server being offline?
Using mocks properly is a sign of a well-factored codebase.
The common pitfall with this style of testing is that you end up testing implementation details and couple your tests to your code and not the interfaces at the boundaries of your code.
I prefer the boundary between unit and integration tests to be the process itself. Meaning, if I have a dependency outside the main process (eg database, HTTP API etc) then it warrants an integration test where i mock this dependency somehow. Otherwise, unit tests test the interfaces with as much coverage of actual code execution as possible. In unit tests, out of process dependencies are swapped with a fake implementation like an in-memory store instead of a full of fledged one that covers only part of interface that i use. This results in much more robust tests that I can rely on during refactoring as opposed to “every method or function is a unit, so unit tests should test these individual methods”.
Well-factored codebase doesn’t need mocks.
Even funnier, this was all hypothetical and yet taken as gospel. We hadn't even written the tests yet, so it was impossible to say whether they were slow or not. Nothing had been measured, no performance budget had been defined, no prototype of the supposedly slow tests had been written to demonstrate the point.
We ended up writing - no joke - less than 100 tests total, almost all of which hit the database, including some full integration tests, and the entire test suite finished in a few seconds.
I'm all for building in a way that respects performance as an engineering value, but we got lost somewhere along the way.
Why fake it when an integration test tests the real thing.
I’ve seen what you clearly have. Mocked ResultSets, mocked JDBC templates. “When you get SQL, it should be this string. These parameters should be set. Blah blah.”
It’s so much work. And it’s useless. Where does that SQL to check come from? Copy and paste, so it won’t catch a syntax error.
Test data is faked in each result. You can’t test foreign keys.
Just a bad idea. You’re so right. I find it odd some people are so anti-mock. Yeah it gets abused but that’s not the tool’s fault.
But DB calls are not a good spot to mock out.
Hopefully one day you'll back at that, and realise what an immature attitude that was.
More broadly, suppose foo() has an implementation that depends on Bar, but Bar is complicated to instantiate because it needs to know about 5 external services. Fortunately foo() only depends on a narrow sliver of Bar's functionality. Why not wrap Bar in a narrow interface—only the bits foo() depends on—and fake it?
I'm not a maximalist about test doubles. I prefer to factor out my I/O until it's high-level enough that it doesn't need unit tests. But that's not always an option, and I'd rather be flexible and use a test double than burden all my unit tests with the full weight of their production dependencies.
you could extend this to say 85% of the tome just write the code directly to prod and dont have any tests. if you broke something, an alarm will go off
To easily simulate failure cases, a range of possible inputs, bad data etc.
To make the testing process faster when you have hundreds or thousands of tests, running on multiple builds simultaneously across an organisation.
Off the top of my head :-)
> but when it was communicated with Mockito I perceived it as "Mockito is holding the JVM ecosystem back by using dynamic attachment, please switch immediately and figure it out on your own".
Who did the communication? Why is dynamic attachment through a flag a problem, and what was the solution? Why is "enable a flag when running tests" not a satisfactory solution? Why do you even need a _dynamic_ agent; don't you know ahead of time exactly what agent you need when using Mockito?
> While I fully understand the reasons that developers enjoy the feature richness of Kotlin as a programming language, its underlying implementation has significant downsides for projects like Mockito. Quite frankly, it's not fun to deal with.
Why support Kotlin in the first place? If it's a pain to deal with, perhaps the Kotlin user base is better served by a Kotlin-specific mocking framework, maintained by people who enjoy working on those Kotlin-specific code paths?
Some complexities are discovered along the way, people don't know everything when they start.
They could also drop the support after some time, but then it would have created other set of problems for adoption and trustworthiness of the project.
Ok am I being stupid or is the pragmatic solution not to just to enable this flag for test runs etc. and leave it off in prod?
Not security, but integrity, although security (which is the #1 concern of companies relying on a platform responsible for trillions of dollars) is certainly one of the primary motivations for integrity (others being performance, backward compatibility or "evolvability", and correctness). Integrity is the ability of code to locally declare its reliance on some invariant - e.g. that a certain class must not be extended, that a method can only be called by other methods in the same class, or that a field cannot be reassigned after being assigned in the constructor - and have the platform guarantee that the invariant is preserved globally throughout the lifetime of the program, no matter what other code does. What we call "memory safety" is an example of some invariants that have integrity.
This is obviously important for security as it significantly reduces the blast radius of a vulnerability (some attacks that can be done in JS or Python cannot be done in Java), but it's also important for performance, as the compiler needs to know that certain optimisations preserve meaning. E.g. strings cannot be constant-folded if they can't be relied upon to be truly immutable. It's also important for backward-compatibility or "evolvability", as libraries cannot depend on internals that are not explicitly exposed as public APIs; libraries doing that was the cause of the migration pain from Java 8 to 9+, as lots of libraries depended on internal, non-API methods that have changed when the JDK's evolution started picking up steam.
In Java, we've adopted a policy we call Integrity by Default (https://openjdk.org/jeps/8305968), which means that code in one component can violate invariants established by code in another component only if the application is made aware of it and allows it. What isn't allowed is for a library - which could be some fourth-level dependency - to decide for itself at some point during the program's execution, without the application's knowledge, that actually strings in this program should be mutable. We were, and are, open to any ideas as long as this principle is preserved.
Authors of components that do want to do such things find the policy inconvenient because their consumers need to do something extra that isn't required when using normal libraries. But this is a classic case of different users having conflicting requirements. No matter what you do, someone will be inconvenienced. We, the maintainers of the JDK, have opted for a solution that we believe minimises the pain and risk overall, when integrated over all users: Integrity is on by default, and components that wish to break it need an explicit configuration option to allow that.
> built on a solid foundation with ByteBuddy
ByteBuddy's author acknowledges that at least some aspects of ByteBuddy - and in particular the self-loading agent that Mockito used - weren't really a solid foundation, but now it should be: https://youtu.be/AzfhxgkBL9s?t=1843. We are grateful to Rafael for explaining his needs to us so that we could find a way to satisfy them without violating Integrity by Default.
I keep a large production Java codebase and its deployments up-to-date. Short of upstreaming fixes to every major dependency, the only feasible way to continue upgrading JDK/JVM versions has often been to carry explicit exceptions to new defaults.
JPMS is a good example: --add-opens still remains valuable today for important infra like Hadoop, Spark, and Netty. If other, even more core projects (e.g. Arrow) hadn't modernized, the exceptions would be even more prolific.
If libraries so heavily depended upon like Mockito are unable to offer a viable alternative in response to JEP 451, my reaction would be to re-enable dynamic agent attachment rather than re-architect many years of test suites. I can't speak for others, but if this reaction holds broadly it would seem to defeat the point of by-default changes.
Of course, but keep in mind that all these changes were and are being done in response to feedback from other users, and we need to balance the requirements of mocking frameworks with those of people asking for better performance, better security, and better backward compatibility. When you have such a large ecosystem, users can have contradictory demands and sometimes it's impossible to satisfy everyone simultaneously. In those cases, we try to choose whatever we think will do the most good and the least harm over the entire ecosystem.
> JPMS is a good example: --add-opens still remains valuable today for important infra like Hadoop, Spark, and Netty. If other, even more core projects (e.g. Arrow) hadn't modernized, the exceptions would be even more prolific.
I think you have answered your own question. Make sure the libraries you rely on are well maintained, and if not - support them financially (actually, support them also if they are). BTW, I think that Netty is already in the process of abandoning its hacking of internals.
Anyone who has hacked internals agreed to a deal made in the notice we had in the internal files for many years prior to encapsulation [1], which was that the use of internals carries a commitment to added maintenance. Once they use the new supported mechanisms, that added burden is gone but they need to get there. I appreciate the fact that some open source projects are done by volunteers, and I think their users should compensate them, but they did enter into this deal voluntarily.
> If libraries so heavily depended upon like Mockito are unable to offer a viable alternative in response to JEP 451
But they have, and we advised them on how: https://github.com/mockito/mockito/issues/3037
The main "ergonomic" issue was lack of help from build tools like Gradle/Maven.
[1]: The notice was some version of:
WARNING: The contents of this source file are not part of any supported API.
Code that depends on them does so at its own risk: they are subject to change or removal without notice.
Examples?
Presumably this might miss some edge case (where something else also needs the flag?) though an explicit allow of the mockito agent in the jvm arg would have solved for that.
You can and should explicitly specify Mockito as an agent in the JVM configuration, as it is one.
At the moment I can't see anything Mokckito gives that you technically couldn't implement yourself via subclassing and overriding, but it'd be a lot of boilerplate to proxy things and record the arguments.
Mockito shouldn't change whether or not this is possible; the code shouldn't have the prod creds (or any external resource references) hard coded in the compiled bytecode.
On the one hand, you should just design things to be testable from the start. On the other... I'm already working in this codebase with 20 years of legacy untestable design...
Probably because they zealously followed "Effective Java" book.
You write an adapter.
Not mentioning of course needless copy-pasting dosens of members in the adapter. And it must be in prod code, not tests, even though it's documentation would say "Adapter for X, exists only for tests, to be able to mock X".
The cost is the pain - sometimes nightmarish - for other contributors to the code base since tests depending on mocking are far more brittle.
Someone changes code to check if the ResultSet is empty before further processing and a large number of your mock based tests break as the original test author will only have mocked enough of the class to support the current implementation.
Working on a 10+ year old code base, making a small simple safe change and then seeing a bunch of unit tests fail, my reaction is always “please let the failing tests not rely on mocks”.
In my view, one of the biggest mistakes when working with Mockito is relying on answers that return default values even when a method call has not been explicitly described, treating this as some kind of "default implementation". Instead, I prefer to explicitly forbid such behavior by throwing an `AssertionError` from the default answer. Then, if we really take "one method" literally, I explicitly state that `next()` must return `false`, clearly declaring my intent that I have implemented tests based on exactly this described behavior, which in practice most often boils down to a fluent-style list of explicitly expected interactions. Recording interactions is also critically important.
How many methods does `ResultSet` have today? 150? 200? As a Mockito user, I don't care.
So this change doesn't allow an empty result set, something that is no longer allowed by the new implementation but was allowed previously. Isn't that the sort of breaking change you want your regression tests to catch?
If tests (authored by someone else) break, I now have to figure out whether the breakage is due to the fact that not enough behavior was mocked or whether I have inadvertently broken something. Maybe it’s actually important that code avoid using “isEmpty”? Or do I just mock the isEmpty call and hope for the best? What if the existing mocked behavior for size() is non-trivial?
Typically you’re not dealing with something as obvious.
When I use mocking, I try to always use real objects as return values. So if I mock a repository method, like userRepository.search(...) I would return an actual list and not a mocked object. This has worked well for me. If I actually need to test the db query itself, I use a real db
For example, one alternative is to let my IDE implement the interface (I don’t have to “write” a complete implementation), where the default implementations throw “not yet implemented” type exceptions - which clearly indicate that the omitted behavior is not a deliberate part of the test.
Any “mocked” behavior involves writing normal debuggable idiomatic Java code - no need to learn or use a weird DSL to express the behavior of a method body. And it’s far easier to diagnose what’s going on or expected while running the test - instead of the backwards mock approach where failures are typically reported in a non-local manner (test completes and you get unexpected invocation or missing invocation error - where or what should have made the invocation?).
My test implementation can evolve naturally - it’s all normal debuggable idiomatic Java.
If the code being mocked changes its invariants the code under test that depends on that needs to be carefully re-examined. A failing unit test will alert one to that situation.
(I'm not being snarky, I don't understand your point and I want to.)
1. Initially codeUnderTest() calls a dependency's dep.getFoos() method, which returns a list of Foos. This method is expensive, even if there are no Foos to return.
2. Calling the real dep.getFoos() is awkward, so we mock it for tests.
3. Someone changes codeUnderTest() to first call dep.getNumberOfFoos(), which is always quick, and subsequently call dep.getFoos() only if the first method's return value is nonzero. This speeds up the common case in which there are no Foos to process.
4. The test breaks because dep.getNumberOfFoos() has not been mocked.
You could argue that the original test creator should have defensively also mocked dep.getNumberOfFoos() -- but this quickly becomes an argument that the complete functionality of dep should be mocked.
Instead your mocks are all just inline in the test code: ephemeral, basically declarative therefore readily readable & grokable without too much diversion, and easily changed.
A really good usecase for Java's 'Reflection' feature.
Mocking's killer feature is the ability to partially implement/extend by having some default that makes some sense in a testing situation and is easily instantiable without calling a super constructor.
Magicmock in python is the single best mocking library though, too many times have I really wanted mockito to also default to returning a mock instead of null.
Yeah, it's funny, I'm often arguing in the corner of being verbose in the name of plain-ness and greater simplicity.
I realise it's subjective, but this is one of the rare cases where I think the opposite is true, and using the 'magic' thing that shortcuts language primitives in a sort-of DSL is actually the better choice.
It's dumb, it's one or two lines, it says what it does, there's almost zero diversion. Sure you can do it by other means but I think the (what I will claim is) 'truly' inline style code of Mockito is actually a material value add in readability & grokability if you're just trying to debug a failing test you haven't seen in ages, which is basically the usecase I have in mind whenever writing test code.
But when there are many tests where I instantiate a test fixture and return it from a mock when the method is called, I start to think that an in memory stub would have been less code duplication and boilerplate... When some code is refactored to use findByName instead of findById and a ton of tests fail because the mock knows too much implementation detail then I know it should have been an in memory stub implementation all along.
I prefer Mockito's approach.
Historically, open source meant "here's code, use it if it helps, fix it if it breaks." No support contracts, no timelines, no moral duty. GitHub-era norms quietly inverted that into unpaid service work, with entitlement enforced socially ("be nice", "maintainers owe users").
Intrinsic motivation is the only sustainable fuel here. Once you start optimizing for users, stars, adoption, or goodwill, pressure accumulates and burnout is inevitable. When you build purely because the work itself is satisfying, stopping is always allowed, and that's what keeps projects healthy.
Hard boundaries aren't hostility; they're corrective. Fewer projects would exist if more maintainers adopted them, but the ones that remain would be stronger, and companies would be forced to fund or own their forks honestly.
Open source doesn't need more friendliness. It needs less obligation
I (ironically enough) spent some time replacing usages of it in Kafka test code with Mockito because of this, IIRC there was only one situation where Mockito couldn't easily replace Powermock and I'm pretty sure it was mocking out a private static method, so the solution was to refactor the code under test so that you didn't need to mock a private static method to test it.
So funny, he essentially works for free for 10 years, then finally burns out because he doesn't want to put up with a bunch of annoying work? This is why you shouldn't work on open source unless you have a business strategy to get paid. Tons of stuff in life is 100x more annoying and exhausting if you aren't making any money. If he was making $1 million per year from this I doubt his energy would be drained.
If after ten years the spark was gone we should be happy for that ten year contribution, but I don't think there's any reason to assume that money would've prevented the problems that motivated him to step down. Maybe it could incentivize him to muscle through after the magic was gone, but that's a different sort of thing.
It’s more than annoying work, it’s pointless work needlessly created by people other than him.
It’s like migrating from Java 8 to newer versions, the decision makers placed backwards compatibility at the back of their priority list. Literally a decade later it’s still griefing migrating users, all because “Jakarta not javax” nonsense. I’m greatly simplifying but that’s the essence of it.
Now we have some genius decision to I guess protect against untrusted code doing unexpected things. And at the same time Applets are gone and Security Manager is gone. And the reality is that Java applications aren’t run with untrusted code. The run scripts define all the jars/classes used. If there was some malicious code that wanted to run, I’m fairly confident it would also just modify the run scripts to include this new flag.
So all we’ve gained is support headache and pain, and no real net gain in practice.
People quit all the time from highly paid jobs due to burnout. This absolutely does not follow.