linearscan: Linear scan register allocator, formally verified in Coq
|Versions||0.1.0.0, 0.2.0.0, 0.3.0.0, 0.3.0.1, 0.3.1.0, 0.4.0.0, 0.5.0.0, 0.5.1.0, 0.6.0.0, 0.7.0, 0.8.0, 0.9.0, 0.10.0, 0.10.1, 0.10.2, 0.11, 0.11.1, 1.0.0|
|Dependencies||base (>=4.7 && <5.0), containers, ghc‑prim, mtl, transformers [details]|
|Source repo||head: git clone https://github.com/jwiegley/linearscan|
|Uploaded||by JohnWiegley at Fri Nov 20 17:35:06 UTC 2015|
|Downloads||4037 total (61 in the last 30 days)|
|Rating||(no votes yet) [estimated by rule of succession]|
|Status||Docs available [build log]
Last success reported on 2016-11-29 [all 3 reports]
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linearscan library is an implementation -- in Coq, extracted to
Haskell -- of a register allocation algorithm developed by Christian Wimmer.
It is described in detail in his Masters thesis, which can be found at
Java implementation of this same algorithm, by that author, is used in
Oracle's Graal project. It has also been implemented in C++ by Mozilla.
This version of the algorithm was written and verified in Coq, containing over 231 proved lemmas, at over 10K LOC. It was funded as a research project by BAE Systems (http://www.baesystems.com), to be used in an in-house compiler written in Haskell.
In order for the Coq code to be usable from Haskell, it is first extracted from Coq as a Haskell library, during which many of Coq's fundamental types are mapped directly onto counterparts in the Haskell Prelude.
Note that not every conceivable property of this library has been proven. For some of the lower layers this is true, because the algebraic constraints on these components could be exhaustively described in the context of their use. However, higher-level components represent a great variety of use cases, and not every one of these cases has been proven correct. This represents an ongoing effort, with the hope that proofs will entirely replace the necessity for ad hoc unit testing, and that at some point we can know that any allocation produced by this library must either fail, or be mathematically sound. In the absence of some complete coverage, this version of the library provides an optional, runtime verifier to confirm expectations of correctness, since it is easier to prove the validity of generated data, than of how it was generated.
This library's sole entry point is the function
takes a list of basic blocks, and a functional characterization of those
blocks, and produces a new list, with register allocations applied to their
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