Skip to main navigation Skip to search Skip to main content

Verified Lustre Normalization with Node Subsampling

  • INRIA Institut National de Recherche en Informatique et en Automatique
  • PSL research University & IPSL

Research output: Contribution to journalArticlepeer-review

Abstract

Dataflow languages allow the specification of reactive systems by mutually recursive stream equations, functions, and boolean activation conditions called clocks. Lustre and Scade are dataflow languages for programming embedded systems. Dataflow programs are compiled by a succession of passes. This article focuses on the normalization pass which rewrites programs into the simpler form required for code generation.Vélus is a compiler from a normalized form of Lustre to CompCert's Clight language. Its specification in the Coq interactive theorem prover includes an end-to-end correctness proof that the values prescribed by the dataflow semantics of source programs are produced by executions of generated assembly code. We describe how to extend Vélus with a normalization pass and to allow subsampled node inputs and outputs. We propose semantic definitions for the unrestricted language, divide normalization into three steps to facilitate proofs, adapt the clock type system to handle richer node definitions, and extend the end-to-end correctness theorem to incorporate the new features. The proofs require reasoning about the relation between static clock annotations and the presence and absence of values in the dynamic semantics. The generalization of node inputs requires adding a compiler pass to ensure the initialization of variables passed in function calls.

Original languageEnglish
Article number98
JournalACM Transactions on Embedded Computing Systems
Volume20
Issue number5s
DOIs
Publication statusPublished - 1 Oct 2021

Keywords

  • Stream languages
  • interactive theorem proving
  • verified compilation

Fingerprint

Dive into the research topics of 'Verified Lustre Normalization with Node Subsampling'. Together they form a unique fingerprint.

Cite this