Trestle

Trestle is a collection of utilities for SAT work. It includes:

• Encoding utilities
• Solver APIs
• Printers and parsers for common file formats

This repository is an active research code base using the Research Codebase Manifesto, and the core library (in Trestle/) is not very stable yet.

We would love to hear from any projects using Trestle! Contact @JamesGallicchio by email or mastodon.

Getting it

Add the following to your project's lakefile:

require «trestle» from git
  "https://github.com/FormalSAT/Trestle" @ "main"

The main branch currently uses Lean v4.15.0, but Lean still has breaking changes every minor revision, so don't expect it to compile on other versions of Lean.

Since this project relies on mathlib, we recommend running lake exe cache get after modifying your lakefile. This downloads a precompiled version of mathlib.

Usage

In your files, import Trestle will import everything in the library.

Everything in the library is under the Trestle namespace, so we generally assume you also have open Trestle at the top of your files.

Important types:

• PropFun: The mathematical model of a propositional formula. Two PropFuns are equal iff they have the same interpretation under all assignments.
• EncCNF: The encoding monad. This monad allows you to build up a CNF via do-notation. See Examples/Encoding for example usage.
• VEncCNF: Verified encoding. Similar to EncCNF, constrained to provably encode some predicate over assignments. This connects EncCNF to the PropFun math model.
• Solver, Solver.ModelCount, Solver.ModelSample: Solver interfaces. These are each typeclasses. The idea is that you should have an instance of the Solver typeclass in scope when you go to solve a CNF formula. See Examples/Cadical.lean for how to declare a solver instance.

Notation

TODO(JG): describe available notation for PropFun, PropForm

Planned scope

• Support (verified?) encoding to non-CNF formulas (KNF, d-DNNF, XOR-CNF, ...)
• Add verified checkers for sat certificates
  • See e.g. here and here
• Add verified model counting
  • See Bryant et al 2023
• Add verified pre-processing

License

This project is licensed under the Apache 2.0 license (see LICENSE). If you want to use the library but need it to be released under different terms, please contact us or open an issue.

Contributing

PRs are welcome and appreciated. That said, because the repository is quite unstable, please open an issue or comment on an existing one to let us know what you are working on!

Contributors

@vtec234 @ccodel @JamesGallicchio