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Computer Science > Programming Languages

arXiv:2011.07966 (cs)
[Submitted on 16 Nov 2020 (v1), last revised 25 Jan 2021 (this
version, v3)]

Title:A Modern Compiler for the French Tax Code

Authors:Denis Merigoux (PROSECCO), Raphael Monat (APR), Jonathan
Protzenko (MSR)
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    Abstract: In France, income tax is computed from taxpayers'
    individual returns, using an algorithm that is authored, designed
    and maintained by the French Public Finances Directorate (DGFiP).
    This algorithm relies on a legacy custom language and compiler
    originally designed in 1990, which unlike French wine, did not
    age well with time. Owing to the shortcomings of the input
    language and the technical limitations of the compiler, the
    algorithm is proving harder and harder to maintain, relying on
    ad-hoc behaviors and workarounds to implement the most recent
    changes in tax law. Competence loss and aging code also mean that
    the system does not benefit from any modern compiler techniques
    that would increase confidence in the implementation. We overhaul
    this infrastructure and present Mlang, an open-source compiler
    toolchain whose goal is to replace the existing infrastructure.
    Mlang is based on a reverse-engineered formalization of the
    DGFiP's system, and has been thoroughly validated against the
    private DGFiP test suite. As such, Mlang has a formal semantics;
    eliminates previous handwritten workarounds in C; compiles to
    modern languages (Python); and enables a variety of
    instrumentations, providing deep insights about the essence of
    French income tax computation. The DGFiP is now officially
    transitioning to Mlang for their production system.

Subjects: Programming Languages (cs.PL)
Cite as:  arXiv:2011.07966 [cs.PL]
          (or arXiv:2011.07966v3 [cs.PL] for this version)
          https://doi.org/10.48550/arXiv.2011.07966
          Focus to learn more
          arXiv-issued DOI via DataCite

Submission history

From: Denis Merigoux [view email] [via CCSD proxy]
[v1] Mon, 16 Nov 2020 13:57:00 UTC (69 KB)
[v2] Thu, 26 Nov 2020 10:53:30 UTC (69 KB)
[v3] Mon, 25 Jan 2021 10:19:30 UTC (69 KB)
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