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One can write dependently typed functional programs in Coq, and prove them correct in Coq; one can write low-level programs in C, and prove them correct with a C verification tool. We demonstrate how to write programs partly in Coq and partly in C, and interface the proofs together. The Verified Foreign Function Interface (VeriFFI) guarantees type safety and correctness of the combined program. It works by translating Coq function types (and constructor types) along with Coq functional models into VST function-specifications; if the user can prove in VST that the C functions satisfy those specs, then the C functions behave according to the user-specified functional models (even though the C implementation might be very different) and the proofs of Coq functions that call the C code can rely on that behavior. To achieve this translation, we employ a novel, hybrid deep/shallow description of Coq dependent types. 

C program components verified for functional correctness in Coq using VST (Verified Software Toolchain) can now rely on a set of standard library components (math functions, malloc/free, atomic load/store, locks, threads) that have formal specifications. 

The development of sound and efficient tools that automatically perform floating-point round-off error analysis is an active area of research with applications to embedded systems and scientific computing. In this paper we describe VCFloat2, a novel extension to the VCFloat tool for verifying floating-point C programs in Coq. Like VCFloat1, VCFloat2 soundly and automatically computes round-off error bounds on floating-point expressions, but does so to higher accuracy; with better performance; with more generality for nonstandard number formats; with the ability to reason about external (user-defined or library) functions; and with improved modularity for interfacing with other program verification tools in Coq. We evaluate the performance of VCFloat2 using common benchmarks; compared to other state-of-the art tools, VCFloat2 computes competitive error bounds and transparent certificates that require less time for verification. 

The LAProof library provides formal machine-checked proofs of the accuracy of basic linear algebra operations: inner product using conventional multiply and add, inner product using fused multiply-add, scaled matrix-vector and matrix-matrix multiplication, and scaled vector and matrix addition. These proofs can connect to concrete implementations of low-level basic linear algebra subprograms; as a proof of concept we present a machine-checked correctness proof of a C function implementing sparse matrix-vector multiplication using the compressed sparse row format. Our accuracy proofs are backward error bounds and mixed backward-forward error bounds that account for underflow, proved subject to no assumptions except a low-level formal model of IEEE-754 arithmetic. We treat low-order error terms concretely, not approximating as O(u^2). 

Solving a sparse linear system of the form Ax = b is a common engineering task, e.g., as a step in approximating solutions of differential equations. Inverting a large matrix A is often too expensive, and instead engineers rely on iterative methods, which progressively approximate the solution x of the linear system in several iterations, where each iteration is a much less expensive (sparse) matrix-vector multiplication. We present a formal proof in the Coq proof assistant of the correctness, accuracy and convergence of one prominent iterative method, the Jacobi iteration. The accuracy and convergence properties of Jacobi iteration are well-studied, but most past analyses were performed in real arithmetic; instead, we study those properties, and prove our results, in floatingpoint arithmetic. We then show that our results are properly reflected in a concrete implementation in the C language. Finally, we show that the iteration will not overflow, under assumptions that we make explicit. Notably, our proofs are faithful to the details of the implementation, including C program semantics and floating-point arithmetic. 

Solving a sparse linear system of the form Ax = b is a common engineering task, e.g., as a step in approximating solutions of differential equations. Inverting a large matrix A is often too expensive, and instead engineers rely on iterative methods, which progressively approximate the solution x of the linear system in several iterations, where each iteration is a much less expensive (sparse) matrix-vector multiplication. We present a formal proof in the Coq proof assistant of the correctness, accuracy and convergence of one prominent iterative method, the Jacobi iteration. The accuracy and convergence properties of Jacobi iteration are well-studied, but most past analyses were performed in real arithmetic; instead, we study those properties, and prove our results, in floatingpoint arithmetic. We then show that our results are properly reflected in a concrete implementation in the C language. Finally, we show that the iteration will not overflow, under assumptions that we make explicit. Notably, our proofs are faithful to the details of the implementation, including C program semantics and floating-point arithmetic. 

The type-theoretic notions of existential abstraction, subtyping, subsumption, and intersection have useful analogues in separation-logic proofs of imperative programs. We have implemented these as an enhancement of the verified software toolchain (VST). VST is an impredicative concurrent separation logic for the C language, implemented in the Coq proof assistant, and proved sound in Coq. For machine-checked functional-correctness verification of software at scale, VST embeds its expressive program logic in dependently typed higher-order logic (CiC). Specifications and proofs in the program logic can leverage the expressiveness of CiC—so users can overcome the abstraction gaps that stand in the way of top-to-bottom verification: gaps between source code verification, compilation, and domain-specific reasoning, and between different analysis techniques or formalisms. Until now, VST has supported the specification of a program as a flat collection of function specifications (in higher-order separation logic)—one proves that each function correctly implements its specification, assuming the specifications of the functions it calls. But what if a function has more than one specification? In this work, we exploit type-theoretic concepts to structure specification interfaces for C code. This brings modularity principles of modern software engineering to concrete program verification. Previous work used representation predicates to enable data abstraction in separation logic. We go further, introducing function-specification subsumption and intersection specifications to organize the multiple specifications that a function is typically associated with. As in type theory, if 𝜙 is a of 𝜓, that is 𝜙<:𝜓, then 𝑥:𝜙 implies 𝑥:𝜓, meaning that any function satisfying specification 𝜙 can be used wherever a function satisfying 𝜓 is demanded. Subsumption incorporates separation-logic framing and parameter adaptation, as well as step-indexing and specifications constructed via mixed-variance functors (needed for C’s function pointers). 

We verify the functional correctness of an array-of-bins (segregated free-lists) single-thread malloc/free system with respect to a correctness specification written in separation logic. The memory allocator is written in standard C code compatible with the standard API; the specification is in the Verifiable C program logic, and the proof is done in the Verified Software Toolchain within the Coq proof assistant. Our "resource-aware" specification can guarantee when malloc will successfully return a block, unlike the standard Posix specification that allows malloc to return NULL whenever it wants to. We also prove subsumption (refinement): the resource-aware specification implies a resource-oblivious spec.