coq VS Spring Boot

The page summarizing the considered new names and their pros/cons is interesting: https://github.com/coq/coq/wiki/Alternative-names

Naming is hard...

Are those more important than, say:

- Proven with Coq, a formal proof management system: https://coq.inria.fr/

See in the real world: https://aws.amazon.com/security/provable-security/

And check out Computer-Aided Verification (CAV).

To be ruthlessly, uselessly pedantic - after all, we're mathematicians - there's reasonable definitions of "academic" where logical unsoundness is still academic if it never interfered with the reasoning behind any proofs of interest ;)

But: so long as we're accepting that unsoundness in your checker or its underlying theory are intrinsically deal breakers, there's definitely a long history of this, perhaps more somewhat more relevant than the HM example, since no proof checkers of note, AFAIK, have incorporated mutation into their type theory.

For one thing, the implementation can very easily have bugs. Coq itself certainly has had soundness bugs occasionally [0]. I'm sure Agda, Lean, Idris, etc. have too, but I've followed them less closely.

But even the underlying mathematics have been tricky. Girard's Paradox broke Martin-Löf's type theory, which is why in these dependently typed proof assistants you have to deal with the bizarre "Tower of Universes"; and Girard's Paradox is an analogue of Russell's Paradox which broke more naive set theories. And then Russell himself and his system of universal mathematics was very famously struck down by Gödel.

But we've definitely gotten it right this time...

[0] https://github.com/coq/coq/issues/4294

Dafny and Whiley are two examples with explicit verification support. Idris and other dependently typed languages should all be rich enough to express the required predicate but might not necessarily be able to accept a reasonable implementation as proof. Isabelle, Lean, Coq, and other theorem provers definitely can express the capability but aren't going to churn out much in the way of executable programs; they're more useful to guide an implementation in a more practical functional language but then the proof is separated from the implementation, and you could also use tools like TLA+.

https://dafny.org/

https://whiley.org/

https://www.idris-lang.org/

https://isabelle.in.tum.de/

https://leanprover.github.io/

https://coq.inria.fr/

http://lamport.azurewebsites.net/tla/tla.html

Still, there are many useful tools based on these ideas, used by programmers and mathematicians alike. What you describe sounds rather like Datalog (e.g. Soufflé Datalog), where you supply some rules and an initial fact, and the system repeatedly expands out the set of facts until nothing new can be derived. (This has to be finite, if you want to get anywhere.) In Prolog (e.g. SWI Prolog) you also supply a set of rules and facts, but instead of a fact as your starting point, you give a query containing some unknown variables, and the system tries to find an assignment of the variables that proves the query. And finally there is a rich array of theorem provers and proof assistants such as Agda, Coq, Lean, and Twelf, which can all be used to help check your reasoning or explore new ideas.

What ever happened to the effort [1] to rename Coq in order to make it less offensive? There were a number of excellent proposals [2] that seemed to die on the vine.

[1] https://github.com/coq/coq/wiki/Alternative-names

[2] https://github.com/coq/coq/wiki/Alternative-names#c%E1%B5%A3...

Information about the Coq proof assistant: https://coq.inria.fr/ , https://en.wikipedia.org/wiki/Coq

This type of thing can help you formally verify code.

So, if your proof is correct, and your description of the (language/CPU) is correct, you can prove the code does what you think it does.

Formal proof systems are still growing up, though, and they are still pretty hard to use. See Coq for an introduction: https://coq.inria.fr/

Most of the proof assistants out there: Lean, Coq, Dafny, Isabelle, F*, Idris 2, and Agda. And the main concepts are dependent types, Homotopy Type Theory AKA HoTT, and Category Theory. Warning: HoTT and Category Theory are really dense, you're going to really need to research them.

- Usually manually wired and configured vs the spring boot "starter" pattern of having libraries that automatically do some of the manual setup work for you: https://github.com/spring-projects/spring-boot/blob/main/spr...

I wish more client library sets had the feature-matrix that the pulsar one does, because in practice most end up being the same: Java supports everything because it's either built in the same codebase or is the most used client and gets the most support, while the dotnet client codebase has many feature-requests or performance improvement issues, often leading to a "third-party client" being created.

https://github.com/spring-projects/spring-boot/pull/39754/co...

If you’re currently running with an earlier version of Spring Boot, I recommend that you upgrade to Spring Boot 2.7 before migrating to Spring Boot 3.0. It minimizes compatibility issues as much as possible.

Okay, we need to build the game? No problem, we will use Spring Boot and Swing!

It's weird that some people including you directly attack my competence. As a power user you should have plenty of experience getting something to work that is not properly document, does not work how the documentation promised it to, or has weird problems on top of it. Look at idiotic things like this:

https://github.com/spring-projects/spring-boot/issues/33044

Take any similar issue and you'll see a bunch of people who try to find a solution for them because they just aren't repeatable at all. The underlying issue is the auto configuration doing things you can't follow quite properly. It's like it wasn't mean to be understood. Issues like the one I linked above also show me that the spring dev crowd also doesn't understand the ecosystem anymore. The problem is complexity and automagic.

An interested reader can decide for themselves:

https://github.com/spring-projects/spring-boot/tree/main/spr...

Explicitly decoding URL query parameters occurs less often because many frameworks, including Spring Boot, handle decoding automatically.

https://aws.amazon.com/lambda/ https://aws.amazon.com/api-gateway/ https://aws.amazon.com/serverless/sam/ https://aws.amazon.com/cloudformation/ https://aws.amazon.com/s3/ https://spring.io/projects/spring-boot https://start.spring.io