sorbet VS algebra-driven-design

Not part of the official language spec, but Ruby has Sorbet, from a company who employs Ruby core contributors and helped with the recently released JIT additions to the language, amount countless other contributions over the last couple decades.

https://sorbet.org/

First let's introduce the tool: Sorbet is a gem developed by Stripe that aims to bring type notation syntax and type checking support for the Ruby ecosystem by utilizing the "Gradual typing" philosophy, it also provide type generation from YARD comments via the tapioca gem, allowing to grow alongside the already built Ruby codebase.

We have hundreds of thousands of lines of ruby code spanning many services / monoliths. Even now I find it somewhat annoying to open a controller / component that is basically an empty class def but somehow executes a bunch of complex stuff via mixins, monkey patches etc, and you have to figure out how.

We are turning to https://sorbet.org/ to reign in the madness. I'm keen to know if others are doing the same, and how they are finding it (pros and cons)

According to https://sorbet.org/ , the vast majority of code at Stripe is written in ruby.

Caso de Stripe, que tuvo que inventar Sorbet para tener type checking en ruby.

> I guess what I'm asking is: do you see a future where there is more explicit control afforded to people who want to pick their own tradeoffs without resorting to writing everything performance-sensitive in extensions written in C/Rust/whatever?

An approach exists already in the present, and it's Stripe's Sorbet AOT compiler (https://github.com/sorbet/sorbet/tree/master/compiler).

That's incorrect. You may be thinking of Stripe, and AFAICT it's not very actively developed anymore: https://github.com/sorbet/sorbet/commits/master/compiler

You might want to read on Algebra-Driven Design and Data Oriented Design. If you are greedy, both books were pirated.

I would like to do this more. At the moment I don't do formal verification. However, I often borrow methodology from the excellent book Algebra-Driven Design (text available on GitHub but support the author if you find it useful!) when designing systems. This means I define algebraic data types to describe the program and the laws that relate the different types, and use that to guide implementation in a language that doesn't support ADTs.

Their approach might be to express their business logic as a carefully selected collection of types and laws, as described in Algebra-Driven Design (the full text is available on GitHub, please support the author if you find it useful though). I recommend this book to everyone because, even if you don't use this approach to design your programs, it's an excellent way to think about problems and better understand the problem space.

If you have an interest in computer science, category theory is very useful there. Here's a good book on the topic (Algebra-Driven Design, by Sandy Maguire).

This reminds me of QuickSpec (different from QuickCheck) in Haskell. It takes Haskell code and finds the Mathematical laws that the code supports. It does this using a sort of smart random search. I learned about this as part of the Algebra Driven Design book.

Sorry probably worth pointing out that I'm not referring to an Algebra in the pure math sense. I'm more referring to specifying algebraic laws that an API would have to satisfy as talked about in this book https://leanpub.com/algebra-driven-design.