pub VS clingo

Agreed. Version resolution is the interesting problem.

Most package managers use a SAT solver to resolve dependencies. The Dart team has a detailed write up on their SAT-based approach which is worth a read [1]. For contrast, Russ Cox presents an algorithm that doesn't use a SAT solver (intended for Go) [2].

[1] https://github.com/dart-lang/pub/blob/master/doc/solver.md

[2] https://research.swtch.com/vgo-mvs

Official documentation.

As I understand Custom package repositories it's possible to host one's own package repository. The Repository Specification is public, but dart.dev only references cloud based paid services like Cloudsmith and OnePub.

As u/Which-Adeptness6908 already pointed out, the repository specification is small, and that's all you need to implement a server: https://github.com/dart-lang/pub/blob/master/doc/repository-spec-v2.md

https://docs.github.com/en/code-security/secret-scanning/sec...

A bit sad, they don't publish the list of regexes, etc.

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I added a similar thing to the package manager for Dart / Flutter, because we saw users accidentally publishing secrets. That code is public, it relies on regexes and entropy estimation:

https://github.com/dart-lang/pub/blob/eb8ee21a089ebe0f2c2dd8...

It was heavily inspired by the researchers in:

Heres are some issues I've faced when trying with the dart-version cli: - The installation - dart pub global activate needs to have flutter/dart global installed already. - Global activated fvm cli got invalid after flutter upgrade, see issue - The cli does not work with customized fork of flutter. - You should run fvm flutter , not flutter , this changes CI/CD workflow

This will add the args dependency in your pubspec file. We used the Darts package manager pub to add this dependency.

One of the easiest to get started on Datalog in my opinion is really clingo https://potassco.org/clingo/ , which can be pip installed and has python bindings. Answer Set Programming goes beyond datalog, but it holds datalog semantics as a sublanguage. It is unfortunate this is not well advertised.

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Love this article and the push to build awareness of what modern SAT solvers can do.

The thing it misses, though, is that there are higher level abstractions that are far more accessible than SAT. If I were teaching a course on this, I would start with either Answer Set Programming or Satisfiability Modulo Theories (SMT). The most widely used solvers for those are clingo [0] and Z3 [1]:

With ASP, you write in a much clearer Prolog-like syntax that does not require nearly as much encoding effort as your typical SAT problem. Z3 is similar -- you can code up problems in a simple Python API, or write them in the smtlib language.

Both of these make it easy to add various types of optimization, constraints, etc. to your problem, and they're much better as modeling languages than straight SAT. Underneath, they have solvers that leverage all the modern CDCL tricks.

We wrote up a paper [2] on how to formulate a modern dependency solver in ASP; it's helped tremendously for adding new types of features like options, variants, and complex compiler/arch dependencies to Spack [3]. You could not get good solutions to some of these problems without a capable and expressive solver.

[0] https://github.com/potassco/clingo

Answer Set Programming is an incredibly powerful tool to declaratively solve combinatorial problems. Clingo is one of the best open source implementations in my opinion: https://github.com/potassco/clingo