What if writing tests was a joyful experience? (2023)

I was inspired by the jane street post and implemented exactly this in my Scala unit testing library uTest (http://www.lihaoyi.com/post/GoldenLiteralTestinginuTest090.h...). Can confirm that auto updating golden test assertions does make working with a test suite much more joyful than struggling with each assertion by hand

I realize that the example is contrived, but what is the point of writing a test of a fibonacci function if your test harness is designed to just take whatever it tells you and updates the assert to verify that what it told you is indeed what it just told you.

This assumes the code you wrote is already correct and giving the correct answer, so why bother writing tests? If, however you accept that you may have got it wrong, figure out the expected outcome through some reliable means (in this case, dig out your old TI-89), get the result and write your test to assert against a known correct value.

I wouldn't trust any tests that are written this way.

Recently, I have given up on writing unit tests, instead prompting an LLM to write them for me. I just sit back and keep prompting it until it gets it right. Sometimes it goes a little haywire in our Monorepo, but I don't have to accept its changes.

It feels ... strangely empowering.

If you’re a Swift programmer, the swift-snapshot-testing package is a great implementation of these ideas.

https://github.com/pointfreeco/swift-snapshot-testing

Discussed at the time:

What if writing tests was a joyful experience? - https://news.ycombinator.com/item?id=34350749 - Jan 2023 (122 comments)

> You start writing assert fibonacci(15) == ... and already you’re forced to think. What does fibonacci(15) equal? If you already know, terrific—but what are you meant to do if you don’t?

Um …duh? Get out a calculator. Consult a reference, etc. Otherwise compute the result, and ensure you've done that correctly, ideally as independent of the code under test as possible. A lot of even mathematical stuff has "test vectors"; e.g., the SHA algorithms.

> Here’s how you’d do it with an expect test:

  printf "%d" (fibonacci 15);
  [%expect {||}]

…you're kidding me. This is "fix the current state of the function — whether correct or not — as the expected output."

Yeah… no kidding that's easier.

We gloss over errors — "some things just looked incorrect" — well, but how do you know that any differently than fib(10)?

I really like this style of testing -- code that can be tested this way is also the most fun kind of code to work with and the most likely to behave predictably.

I love determinism and plain old data.

Amazing to see Jane Street uses Emacs. And property-based testing too.

> you don’t just get a build failure telling you that you want 610 instead of a blank string

So I had to scratch my head a bit because I was thinking: "Wait, the whole point is that you don't know whether what you're testing is correct or not, so how can you rely on that as input to your tests!?".

But even though I didn't understand everything they do yet I do see at least a big case where it makes lots of sense. And it happens to be a case where a lot of people see the benefits of test: before refactoring.

> What does fibonacci(15) equal? If you already know, terrific—but what are you meant to do if you don’t?

Yeah a common one is reuse a function in the same language which you believe is correct (you probably haven't proven it to be correct). Another typical one is you reuse a similar function from another language (once again, it's probably not been proven it is correct). But if two implementation differ, you know you have an issue.

> let d = create_marketdata_processor () in > ( Do some preprocessing to define the symbol with id=1 as "APPL" )

Typo. It's AAPL, not APPL. It's correctly used as AAPL later on.

FWIW writing tests better become a joyful experience for we're going to need a lot* of these with all our AI generated code.

This is a cool idea. I wish something like this existed for C#.

In my experience the lack of joy or difficulty with tests is almost always that the test environment is usually different enough from the real environment that you end up needing to kind of stretch your code to fit into the test env instead of actually testing what you are interested in.

This doesn't apply to very simple functions but tests on simple functions are the least interesting/ valuable.