jsverify VS Preact

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.

In this post, we get to know more about Preact, one of this year's trending libraries. And we'll compare it to React to see which one suits better for our projects.

Similarly to Promises/A+, this effort focuses on aligning the JavaScript ecosystem. If this alignment is successful, then a standard could emerge, based on that experience. Several framework authors are collaborating here on a common model which could back their reactivity core. The current draft is based on design input from the authors/maintainers of Angular, Bubble, Ember, FAST, MobX, Preact, Qwik, RxJS, Solid, Starbeam, Svelte, Vue, Wiz, and more…

Those who want to develop a library that can be used by any other reactive framework. I often see SignalLike type that tries to subtype it.

https://github.com/preactjs/preact/blob/757746a915d186a90954...

The official Preact documentation.

At the very bottom of the image, there are 3 blocks that I chose to call application components. If you are building a cross-framework library, these can be built with whatever tools you want! Only catch is, all the tools you use to build it, will be needed by everyone consuming it. So choose wisely, and be mindful of how many kilobytes of third party code you will need in order to ship. In Schedule-X, I chose to use Preact. You will probably be fine with most lightweight virtual DOM libraries, and just like with frameworks there are a few to pick from.

>> React is not traditionally used for making games, but that's part of the fun and the challenge. R

> MS Flight Simulator cockpits are built with MSFS Avionics Framework which is React-like and MIT licensed:

https://github.com/microsoft/msfs-avionics-mirror/tree/main/...

preactjs may or may not be faster: https://preactjs.com/

Million.js is faster than preact, and lists a number of references under Acknowledgements: https://github.com/aidenybai/million#acknowledgments

https://million.dev/docs :

> We use a novel approach to the virtual DOM called the block virtual DOM. You can read more on what the block virtual DOM is with Virtual DOM: Back in Block and how we make it happen in React with Behind the block().*

React API reference > Components > Profiler:

DEV is a Rails monolith, which uses Preact in the front-end using islands architecture. The reason why I mention all this is that it's not a full-stack JavaScript application, and there is no state management library like Redux or Zustand in use. The data store, for the most part on the front end, is all data attributes.