revng-qa

Source for rev.ng test cases (by revng)

Revng-qa Alternatives

Similar projects and alternatives to revng-qa

  • QEMU

    Official QEMU mirror. Please see https://www.qemu.org/contribute/ for how to submit changes to QEMU. Pull Requests are ignored. Please only use release tarballs from the QEMU website.

  • rizin

    UNIX-like reverse engineering framework and command-line toolset.

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

    InfluxDB logo
  • revng

    revng: the core repository of the rev.ng project

  • remill

    Library for lifting machine code to LLVM bitcode

  • rellume

    Lift machine code to performant LLVM IR

  • WorkOS

    The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

    WorkOS logo
NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a better revng-qa alternative or higher similarity.

revng-qa reviews and mentions

Posts with mentions or reviews of revng-qa. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-01-12.
  • Revng translates (i386, x86-64, MIPS, ARM, AArch64, s390x) binaries to LLVM IR
    7 projects | news.ycombinator.com | 12 Jan 2024
    > the binary code to LLVM IR uplifting loses a lot of context

    Losing context is good in order to ensure you properly decoupled the frontend from the rest of the pipeline.

    We don't even keep track of what a "call" instruction is, we re-detect it on the LLVM IR.

    One reason you may want to preserve context is to let the user know where a specific piece of lifted code originated from. In order to preserve this information, we exploit LLVM's debugging metadata and it works pretty well. There's some loss there, but LLVM transformations strive to preserve it.

    After all, imagine you have `add rax, 4; add rax, 4`, you'll want to optimize it to a +8 and you'll either have to decide if you want to associate your +8 operation with the first or the second instruction.

    > the binary code to LLVM IR uplifting loses a lot of [...] semantics information

    Not sure what you mean here, we use QEMU as a lifter and that's very accurate in terms of semantics.

    I'm not sure what MIR and Swift IR have to do with the discussion, those are higher level IRs for specific languages. LLVM is rather low level and it's language agnostic.

    However, for going beyond lifting, i.e., decompilation, it's true that LLVM shows some significant limitations. That's why we're rolling our own MLIR dialect, but we can still benefit of all the MLIR/LLVM infrastructure, optimizations and analyses. We're not starting from scratch.

    > emulating pieces of the code sparsely to figure out indirect jumps and so on

    It's hard to emulate without starting from the beginning. Maybe you're thinking about symbolic execution?

    In any case, rev.ng does not emulate and does not do any symbolic execution: we have a data-flow analysis that detects destinations of indirect jumps and it's pretty scalable and effective. Example of things we handle: https://github.com/revng/revng-qa/blob/master/share/revng/te...

Stats

Basic revng-qa repo stats
1
6
8.2
10 days ago

revng/revng-qa is an open source project licensed under GNU General Public License v3.0 only which is an OSI approved license.

The primary programming language of revng-qa is Python.


Sponsored
SaaSHub - Software Alternatives and Reviews
SaaSHub helps you find the best software and product alternatives
www.saashub.com