taxoptimizer
alive2
| taxoptimizer | alive2 | |
|---|---|---|
| 1 | 5 | |
| - | 681 | |
| - | 2.1% | |
| - | 9.3 | |
| - | 8 days ago | |
| C++ | ||
| - | MIT License |
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taxoptimizer
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Programming in Z3 by learning to think like a compiler
I used it to do some tax optimization around ISOs at a newly public company (https://gitlab.com/mbryant/taxoptimizer/-/blob/master/amt.py). It gets pretty slow when you try to look more than a few years out, so I'm guessing writing some optimization logic by hand would've made more sense. Using Z3 here definitely beat me trying to do this on paper like I've seen other people do!
alive2
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CBMC: C bounded model checker. (2021)
Another problem with LLVM I’ve heard about is that it’s intermediate language or API or something is a moving, informally-specified target. People who know LLVM internals might weigh in on that claim. If true, it’s actually easier to target C or a subset of Rust just because it’s static and well-understood.
Two projects sought to mitigate these issues by going in different directions. One was a compiler backend that aimed to be easy to learn with well-specified IL. The other aimed to formalize LLVM’s IL.
http://c9x.me/compile/
https://github.com/AliveToolkit/alive2
There have also been typed, assembly languages to support verification from groups like FLINT. One can also compile language-specific analysis with a certified to LLVM IL compiler. Integrating pieces from different languages can have risks. That (IIRC) is being mitigated by people doing secure, abstract compilation.
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Basic SAT model of x86 instructions using Z3, autogenerated from Intel docs
You can use it to (mostly) validate small snippets are the same. See Alive2 for the application of Z3/formalization of programs as SMT for that [1]. As far as I'm aware there are some problems scaling up to arbitrarily sized programs due to a lack of formalization in higher level languages in addition to computational constraints. With a lot of time and effort it can be done though [2].
1. https://github.com/AliveToolkit/alive2
2. https://sel4.systems/
- John Regehr: Alive2 LLVM optims verification
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Verifying GCC optimizations using an SMT solver
Yeah, this kind of thing is nice.
Alive had been used for years (almost a decade actually) by people to verify LLVM instcombine transforms.
Alive2 (https://github.com/AliveToolkit/alive2) makes it easier to do the same with most optimization passes.
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Programming in Z3 by learning to think like a compiler
Alive/Alive2 [1] is one of the most famous frameworks for compiler transformation verification using BitVec logic
[1] https://github.com/AliveToolkit/alive2
What are some alternatives?
zz - 🍺🐙 ZetZ a zymbolic verifier and tranzpiler to bare metal C
CrossHair - An analysis tool for Python that blurs the line between testing and type systems.
klee - KLEE Symbolic Execution Engine
recreational-rosette - Some fun examples of solving problems with symbolic execution
Symbolica - Symbolica's open-source symbolic execution engine. [Moved to: https://github.com/Symbolica/Symbolica]
llvm-tutor - A collection of out-of-tree LLVM passes for teaching and learning
Cassius - A CSS specification and reasoning engine
sprdpl - Simple Python Recursive-Descent Parsing Library
angr - A powerful and user-friendly binary analysis platform!
coq - Coq is a formal proof management system. It provides a formal language to write mathematical definitions, executable algorithms and theorems together with an environment for semi-interactive development of machine-checked proofs.