jsverify VS TypeScript

Libraries like JSVerify or Fast-Check offer essential tools to facilitate property-based testing.

I tend to use anything that offers property-testing, since tests are much shorter to write and uncover lots more hidden assumptions.

My go-to choices per language are:

- Python: Hypothesis https://hypothesis.readthedocs.io/en/latest (also compatible with PyTest)

- Scala: ScalaCheck https://scalacheck.org (also compatible with ScalaTest)

- Javascript/Typescript: JSVerify https://jsverify.github.io

- Haskell: LazySmallCheck2012 https://github.com/UoYCS-plasma/LazySmallCheck2012/blob/mast...

- When I wrote PHP (over a decade ago) there was no decent property-based test framework, so I cobbled one together https://github.com/Warbo/php-easycheck

All of the above use the same basic setup: tests can make universally-quantified statements (e.g. "for all (x: Int), foo(x) == foo(foo(x))"), then the framework checks that statement for a bunch of different inputs.

Most property-checking frameworks generate data randomly (with more or less sophistication). The Haskell ecosystem is more interesting:

- QuickCheck was one of the first property-testing frameworks, using random genrators.

- SmallCheck came later, which enumerates data instead (e.g. testing a Float might use 0, 1, -1, 2, -2, 0.5, -0.5, etc.). That's cute, but QuickCheck tends to exercise more code paths with each input.

- LazySmallCheck builds up test data on-demand, using Haskell's pervasive laziness. Tests are run with an error as input: if they pass, we're done; if they fail, we're done; if they trigger the error, they're run again with slightly more-defined inputs. For example, if the input is supposed to be a list, we try again with the two forms of list: empty and "cons" (the arguments to cons are both errors, to begin with). This exercises even more code paths for each input.

- LazySmallCheck2012 is a more versatile "update" to LazySmallCheck; in particular, it's able to generate functions.

The usage of hypothesis is very intuitive and simple, and presents the concept of property-based testing perfectly. So I also wanted to find an equivalent alternative in Node. Two of them have high star ratings on Github, JSVerify with 1.6K stars and fast-check with 2.8K stars. So I took some time to study fast-check a little bit and try to get closer to my daily work.

Systems I've used for this include https://agda.readthedocs.io/en/v2.6.0.1/getting-started/what... https://coq.inria.fr https://www.idris-lang.org and https://isabelle.in.tum.de

An easier alternative is to try disproving the statement, by executing it on thousands of examples and seeing if any fail. That gives us less confidence than a full proof, but can still be better than traditional "there exists" tests. This is called property checking or property-based testing. Systems I've used for this include https://hypothesis.works https://hackage.haskell.org/package/QuickCheck https://scalacheck.org and https://jsverify.github.io

Using create-react-app, you’ll run npm test which uses Jest internally. If you are dealing with a lot of data on the UI, or using TypeScript, use JSVerify for property tests. For end to end tests, Cypress is a great choice.

Regular expressions are part of the language, so it's not so unreasonable that TypeScript should parse them and take their semantics into account. Indeed, TypeScript 5.5 will include [new support for syntax checking of regular expressions](https://github.com/microsoft/TypeScript/pull/55600), and presumably they'll eventually be able to solve the problem the GP highlighted on top of those foundations.

Dedicated syntax for creating unique subsets of a type that denote a particular refinement is a longstanding ask[2] - and very useful, we've experimented with implementations.[3]

I don't think it has any relation to runtime type checking at all. It's refinement types, [4] or newtypes[5] depending on the details and how you shape it.

[1] https://github.com/microsoft/TypeScript/blob/main/src/compil...

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