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.
Lustre is a synchronous dataflow language designed for programming embedded systems. In the Vélus project, we use Coq to develop and formalize a compiler that accepts a normalized form of the language and produces imperative code. While this restricted form is suitable for code generated from a user interface based on block diagrams, we wanted to allow programmers to use the complete language.
In this article, we present the normalization pass that transforms the complete language into the normalized one. This transformation is divided into three steps so as to simplify the correctness proofs. To show that the semantics is preserved, it is necessary to prove that the three steps preserve certain static and dynamic properties of the language. In particular, the relation between the clock types and the dynamic semantic must be established.
Specifications based on block diagrams and state machines are used to design control software, especially in the certified development of safety-critical applications. Tools like SCADE Suite and Simulink/Stateflow are equipped with compilers that translate such specifications into executable code. They provide programming languages for composing functions over streams as typified by Dataflow Synchronous Languages like Lustre.
Recent work builds on CompCert to specify and verify a compiler for the core of Lustre in the Coq Interactive Theorem Prover. It formally links the stream-based semantics of the source language to the sequential memory manipulations of generated assembly code. We extend this work to treat a primitive for resetting subsystems. Our contributions include new semantic rules that are suitable for mechanized reasoning, a novel intermediate language for generating optimized code, and proofs of correctness for the associated compilation passes.
Lustre is a synchronous language for programming systems as block diagrams from which low-level imperative code is generated automatically. Recent work applies the Coq interactive proof assistant to specify a compiler from a core subset of Lustre to the Clight input language of CompCert from which assembly code is generated. The overall correctness proof connects the stream semantics of Lustre to the imperative semantics of the assembly code.
Every stream in a Lustre program is associated with a static ‘clock’ that represents when it is active. Compilation transforms the clocks into conditional statements that control when the corresponding value are calculated. Previous work made the simplifying assumption that the inputs and outputs of any given block shared the same static clock. This paper describes one way to lift this restriction. It requires enriching the static typing rules for clocks and the semantic model, and, to satisfy the Clight semantics, adding a compilation pass to ensure that any variable passed to a function call has been initialized.
This paper presents ongoing work to add a modular reset construct to a verified Lustre compiler. We present a novel formal specification for the construct and sketch our plans to integrate it into the compiler and its correctness proof.
The correct compilation of block diagram languages like Lustre, Scade, and a discrete subset of Simulink is important since they are used to program critical embedded control software. We describe the specification and verification in an Interactive Theorem Prover of a compilation chain that treats the key aspects of Lustre: sampling, nodes, and delays. Building on CompCert, we show that repeated execution of the generated assembly code faithfully implements the dataflow semantics of source programs.
We resolve two key technical challenges. The first is the change from a synchronous dataflow semantics, where programs manipulate streams of values, to an imperative one, where computations manipulate memory sequentially. The second is the verified compilation of an imperative language with encapsulated state to C code where the state is realized by nested records. We also treat a standard control optimization that eliminates unnecessary conditional statements.
Synchronous languages are used to program critical control applications. The Scade language, used in industry for these applications, is based on the Lustre language introduced by Caspi and Halbwachs. In this article we treat the formalization and proof, in the Coq proof assistant, of a key compilation pass: the translation of programs from Lustre into an imperative language. The challenge is to change from a synchronous dataflow semantics, where programs manipulate streams, to an imperative semantics, where the program manipulates memory sequentially. We specify and verify a simple code generator that treats core Lustre features: sampling, nodes, and delays. The proof uses an intermediate semantic model that mixes dataflow and imperative characteristics and allows the statement of an essential inductive invariant. We exploit this formalization to verify a classic optimization that fuses conditional structures in the generated imperative code.