Programming in Z3 by learning to think like a compiler

This page summarizes the projects mentioned and recommended in the original post on news.ycombinator.com

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  • alive2

    Automatic verification of LLVM optimizations

  • Alive/Alive2 [1] is one of the most famous frameworks for compiler transformation verification using BitVec logic

    [1] https://github.com/AliveToolkit/alive2

  • recreational-rosette

    Some fun examples of solving problems with symbolic execution

  • I don't know about "practical," but you might enjoy this: https://github.com/kach/recreational-rosette

  • InfluxDB

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  • zz

    Discontinued πŸΊπŸ™ ZetZ a zymbolic verifier and tranzpiler to bare metal C

  • This post reminds me that I've been wanting to try out ZetZ[0]. It incorporates Z3 into a high-level programming language, and seems to do a lot of what the post talks about automatically.

    [0] https://github.com/zetzit/zz

  • 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!

  • angr

    A powerful and user-friendly binary analysis platform!

  • angr uses z3.

    https://github.com/angr/angr

    Supposedly, the DoD has used angr for some use cases.

  • CrossHair

    An analysis tool for Python that blurs the line between testing and type systems.

  • There's a tool for verification of Python programs based on contracts which uses Z3: https://github.com/pschanely/CrossHair

    You can use it as part of your CI or during the development (there's even a neat "watch" mode, akin to auto-correct).

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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