VIP: verifying real-world C idioms with integer-pointer casts

Low-level systems code often needs to interact with data, such as page table entries or network packet headers, in which multiple pieces of information are packaged together as bitfield components of a single machine integer and accessed via bitfield manipulations (e.g., shifts and masking). Most existing approaches to verifying such code employ SMT solvers, instantiated with theories for bit vector reasoning: these provide a powerful hammer, but also significantly increase the trusted computing base of the verification toolchain. In this work, we propose an alternative approach to the verification of bitfield-manipulating systems code, which we call BFF. Building on the RefinedC framework, BFF is not only highly automated (as SMT-based approaches are) but also foundational---i.e., it produces a machine-checked proof of program correctness against a formal semantics for C programs, fully mechanized in Coq. Unlike SMT-based approaches, we do not try to solve the general problem of arbitrary bit vector reasoning, but rather observe that real systems code typically accesses bitfields using simple, well-understood programming patterns: the layout of a bit vector is known up front, and its bitfields are accessed in predictable ways through a handful of bitwise operations involving bit masks. Correspondingly, we center our approach around the concept of a structured bit vector---i.e., a bit vector with a known bitfield layout---which we use to drive simple and predictable automation. We validate the BFF approach by verifying a range of bitfield-manipulating C functions drawn from real systems code, including page table manipulation code from the Linux kernel and the pKVM hypervisor.

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BFF: foundational and automated verification of bitfield-manipulating programs

Zhu

Sammler

Lepigre

et al. 2022

Proc. ACM Program. Lang.

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Quiver: Guided Abductive Inference of Separation Logic Specifications in Coq

Spies,

Gäher,

Sammler

et al. 2024

Proc. ACM Program. Lang.

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Over the past two decades, there has been a great deal of progress on verification of full functional correctness of programs using separation logic, sometimes even producing “foundational” proofs in proof assistants like Coq. Unfortunately, even though existing approaches to this problem provide significant support for automated verification, they still incur a significant specification overhead : the user must supply the specification against which the program is verified, and the specification may be long, complex, or tedious to formulate. In this paper, we introduce Quiver, the first technique for inferring functional correctness specifications in separation logic while simultaneously verifying foundationally that they are correct. To guide Quiver towards the final specification, we take hints from the user in the form of a specification sketch , and then complete the sketch using inference. To do so, Quiver introduces a new abductive deductive verification technique, which integrates ideas from abductive inference (for specification inference) together with deductive separation logic automation (for foundational verification). The result is that users have to provide some guidance, but significantly less than with traditional deductive verification techniques based on separation logic. We have evaluated Quiver on a range of case studies, including code from popular open-source libraries.

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A Two-Phase Infinite/Finite Low-Level Memory Model: Reconciling Integer–Pointer Casts, Finite Space, and undef at the LLVM IR Level of Abstraction

Beck,

Yoon,

Chen

et al. 2024

Proc. ACM Program. Lang.

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This paper provides a novel approach to reconciling complex low-level memory model features, such as pointer--integer casts, with desired refinements that are needed to justify the correctness of program transformations. The idea is to use a "two-phase" memory model, one with an unbounded memory and corresponding unbounded integer type, and one with a finite memory; the connection between the two levels is made explicit by a notion of refinement that handles out-of-memory behaviors. This approach allows for more optimizations to be performed and establishes a clear boundary between the idealized semantics of a program and the implementation of that program on finite hardware. The two-phase memory model has been incorporated into an LLVM IR semantics, demonstrating its utility in practice in the context of a low-level language with features like undef and bitcast. This yields infinite and finite memory versions of the language semantics that are proven to be in refinement with respect to out-of-memory behaviors. Each semantics is accompanied by a verified executable reference interpreter. The semantics justify optimizations, such as dead-alloca-elimination, that were previously impossible or difficult to prove correct.

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VIP: verifying real-world C idioms with integer-pointer casts

Cited by 4 publications

References 45 publications

BFF: foundational and automated verification of bitfield-manipulating programs

BFF: foundational and automated verification of bitfield-manipulating programs

Quiver: Guided Abductive Inference of Separation Logic Specifications in Coq

A Two-Phase Infinite/Finite Low-Level Memory Model: Reconciling Integer–Pointer Casts, Finite Space, and undef at the LLVM IR Level of Abstraction

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