1y ago

Tests are code too

80 comments

Who tests the tests
- The Testmen?
- I've written some tests that got complex enough that I also wrote tests for the logic within the tests.
  
  We do that for some of the more complex business logic. We wrote libraries, which are used by our tests, and we wrote tests which test the library functions to ensure they provide correct results.
  What always worries me is that WE came up with that. It wasn't some higher up, or business unit, or anything. Only because we cared to do our job correctly. If we didn't - nobody would. Nobody is watching the testers (in my experience).
- Mutation testing is quite cool. Basically it analyzes you code and makes changes that should break something. For example if you have if (foo) { ... } it will remove the branch or make the branch run every time. It then runs your tests and sees if anything fails. If the tests don't fail then either you should add another test, or that code was truly dead and should be removed.
  Of course this has lots of "false positives". For example you may be checking if an allocation succeeded and don't need to test if every possible allocation in your code fails, you trust that you can write if (!mem) abort() correctly.
  
  Right,too much coverage is also a bad thing. It leads to having to work on the silly tests every time you change som implementation detail.
  Good tests let the insides of the unit change without breaking, as long as the behave the same to the outside world.
- Create tests to test the tests. Create tests to test those. Recurse to infinity
- Who tests the tests for the tests
  
  Unfortunately, if anyone, I do.

This is why you write the test before the code. You write the test to make sure something fails, then you write the code to make it pass. Then you repeat this until all your behaviors are captured in code. It’s called TDD
But, full marks for writing tests in the first place
- That supposes to have a clear idea of what you're going to code. Otherwise, it's a lot of time wasted to constantly rewrite both the code and tests as you better understand how you're going to solve the task while trying. I guess it works for very narrowed tasks rather than opened problems.
  
  100%. TDD is just not practicably applicable to a lot of scenarios and I wish evangelists were clearer on that detail.
  
  This is the reason I dislike TDD.
  
  The only projects I've ever found interesting in my career was the stuff where nobody had any idea yet how the problem was going to be handled, and you're right that starting with tests is not even possible in this scenario (prototyping is what's really important). Whenever I've written yet another text/email/calling/video Skype clone for yet another cable company, it's possible to start with tests because you already know everything that's going into it.
  
  constantly rewrite both the code and tests as you better understand how you’re going to solve the task while trying
  The tests should be decoupled from the "how" though. It's obviously not possible to completely decouple them, but if you're "constantly" rewriting, something is going wrong.
  Brilliant talk on that topic (with slight audio problems): https://www.youtube.com/watch?v=EZ05e7EMOLM
  
  TDD doesn't imply that you write all the tests first. It just mean you have to write a test before you write a line of production code.
  The idea is to ask yourself "what is the first step I need, where am I going to begin?". You then write a test that validate this first step and fail. Then you write the code to make it pass. Once your done with that, you ask yourself: "what's the next step? ". You, then, repeat the process for that step.
  This is a process you are going to do anyway. Might as well take the time to write some test along with it.
  
  The tests help you discover what needs to be written, too. Honestly, I can’t imagine starting to write code unless I have at least a rough concept of what to write.
  Maybe I’m being judgemental (I don’t mean to be) but what I am trying to say is that, in my experience, writing tests as you code has usually lead to the best outcomes and often the fastest delivery times.
  
  Everything is made up of narrow tasks, you "just" need to break it down more :)

This seems to happen quite often when programmers try to save time when writing tests, instead of writing very simple tests and allowing the duplication to accumulate before removing it. I understand how they feel: they see the pattern and want to skip the boring parts.
No worries. If you skip the boring parts, then much of the time you'll be less bored, but sometimes this will happen. If you want to avoid this, then you'll have to accept some boredom then refactor the tests later. Maybe never, if your pattern ends up with only two or three instances. If you want to know which path is shorter before you start, then so would I. I can sometimes guess correctly. I mostly never know, because I pick one path and stick with it, so I can never compare.
This also tends to happen when the code they're testing has painful hardwired dependencies on expensive external resources. The "bug" in the test is a symptom of the design of the production code. Yay! You learned something! Time to roll up your sleeves and start breaking things apart... assuming that you need to change it at all. Worst case, leave a warning for the next person.
If you'd like a simple rule to follow, here's one: no branching in your tests. If you think you want a branch, then split the tests into two or more tests, then write them individually, then maybe refactor to remove the duplication. It's not a perfect rule, but it'll take you far....
- the code they’re testing has painful hardwired dependencies on expensive external resources
  I've told this story elsewhere, but I had a coworker who wrote an app to remote-control a baseball-throwing machine from a PDA (running WinCE). These machines cost upwards of $50K so he only very rarely had physical access to one. He loved to write tests, which did him no good when his code fired a 125 mph knuckleball a foot over a 10-year-old kid's head. This resulted in the only occasion in my career when I had to physically restrain a client from punching a colleague.
  
  Ah, the ol’ off-by-one-foot problem.
  
  Wow. I love that story and I'm glad nobody was hurt.
  I wonder whether that happened as a result of unexpected behavior by the pitching machine or an incorrect assumption about the pitching machine in that coworker's tests.
  I find this story compelling because it illustrates the points about managing risk and the limits of testing, but it doesn't sound like the typical story that's obviously hyperbole and could never happen to me.
  Thank you for sharing it.

turned out to be a semicolon
- The tests wouldn't even run of that was the issue, pretty sure (depends on the language I suppose)
  
  fun situations can arise when you write , instead of ; For those not in the know, in c++ the comma operator evaluates the left expression, discards the value, then evaluates the right expression and returns the value. if you now have a a situation like this
  c++
  
  int i = 0, printf("some message");
  i has a completely different value, since it actually uses the return value of printf instead
- And in python, no less. Sloppy.
- I'll just write thousands of lines of code inside a global object... I'm sure I won't put a semicolon where a comma should be...
  
  Easy solution:
  Find all: ;
  Replace with: ,

I remember being asked to make unit tests. I wasn't the programmer and for the better part of a week, they didn't even let me look at the code. Yeah, I can make some great unit tests that'll never fail without access to the stuff I'm supposed to test. /s
- I guess it would make sense if you're testing a public API? To make sure the documentation is sufficient and accurate.
  
  Yeah blackbox testing is a whole thing and it's common when you need something to follow a spec and be compatible
  
  He specifically said "unit tests" though, which aren't black box tests by definition
- It makes sense to do it like that if you are supposed to test requirements. Depending on the testing tools you have it might not be feasible unfortunately.

But this does mean, writing tests works.

now you have a group of very specific tests for later debugging

Contrats, you have discovered why in TDD you write the test, watch the test fail, then make the test pass, then refactor. AKA: Red, Green, Refactor
- I'm really having a hard time visualizing this. Do you have an example?
  
  Sure, so say so you have a requirement to add two numbers
  You write a test that has two two inputs and the output Run the test and watch it fail, check that the output is what you expect so you know the test is working
  At this point you have no implementation and you use this opportunity to confirm that the test will work, by checking it is failing how you expect. If you are pairing sometime I teach that you should call out what you expect, kinda like in American pool. Sometimes the test passed in this case, this is your opportunity to break the test and confirm it will fail (though this is often a sign you did too much work previously, and might need to check if you really are making the smallest possible change)
  Do the minimum to correct the problem described by the failing test (you can follow the transformation priority premises here if you are familiar with it)
  At this point you have only implemented the simplest possible code, this makes it really easy to spot if there is a problem with it because of some flaw in the test, and you have confirmed the it matches your test
  What's more you can confirm all, and only behaviours described in the test are implemented
  Look at the code and decide if you can simplify it, do any refactoring
  Got to clean the kitchen because if we don't clean the kitchen we will have to clean the garage and we don't want that because it's a bigger job.
  repeat
  Why this works is that the code is developed in a TDD style forces you to move in smaller steps meaning bugs are shallower when they do occur. You aren't dealing with a 20 complex lines, you are dealing with a return const, or selection, or etc. The scope for the test being wrong is reduced and the amount of implementation is reduced, generally the tests end up more concise and smaller too and the interfaces are user friendly too because you didn't think how do I calculate this, you thought what would be a nice way to call this.
  What's more it encourages an example driven approach that leads to developers thinking about the most sensible input data over and over again, and what that should output reducing the chance any one wrongly implemented test wouldn't be picked up by other examples.
  TL;DR, the driven word is the key, a test that is illogical will never drive you to the working code

And then in the end we realize the most important thing was the tests we wrote along the way.

Run the test a second time, test passes. silently move to the next step.

Lmao, I just had something similar

This is why you write the tests first before the actual code.

Meaning your tests where to complex.
- I always name my tests too complex 🥲.

I've seen some interesting thoughts on TDD with fail, pass, refactor assumptions. I'm curious if anyone here is writing functional code in order to then make a failing functional test pass i.e. BDD / ATDD. This follows similar logic without the refactor assumption. I've seen strong opinions on every side as far as this is concerned. On a team with Dev and QA competencies, I've heard a number of devs glad to get QA out of the bottleneck and put their knowledge to better use.
- Depends. If I'm working in an existing system and I know what the shape of the thing I'm writing is, then I might write the test first and tdd it out as that process is usually a bit faster for me.
  If I'm developing a new feature I'd probably spike out a solution and write an acceptance test to match it, then if I'm feeling pedantic I might throw away the spike code and tdd it back up from scratch but I haven't done that in a while now.
  This all depends on the language and the abstraction layer I'm at.

ChatGPT go brrrrrr

If you use your type system to make invalid states impossible to represent & your functions are pure, there less—maybe nothing—to test, which will save you from this scenario.
- You can't have any bugs if you don't write any code.
- Nothing to test? Lol what.
  def add(a: int, b: int) -> int: return a * b
  All types are correct. No side effects. Does the wrong thing.
  
  Maybe it's doing the right thing but is badly named
- It must be nice to work only with toy cases where this is feasible.
  
  Nothing toy-like about using ADTs to eliminate certain cases. When all cases are handled, your tests can move from a micro state to a macro state. Contraint types or linear types can be used to only allow certain sizes of inputs or require all file handles be closed when opened.
  Naturally if your language’s type system is bad you can’t make these compile-time guarantees tho. Heck, a lot of developers are still using piss-poor languages with null or the infernce sucks with any.

Just dont write tests lol, that's what QA is for.
- This guy's a business major.
  (He just fired half of QA)
  
  He works for Bungie?
  
  Hell no! I love QA, they find all the bugs I make since I dont bother with unit tests. I think every dev team should have 1:1 devs to testers.
- What do you do when QA finds a bug though? Just fix it without writing a test to ensure it doesn't happen again?
  
  Fix it then hire another QA

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