Rust Distilled: An Expressive Tower of Languages
June 07, 2018 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Aaron Weiss, Daniel Patterson, Amal Ahmed
arXiv ID
1806.02693
Category
cs.PL: Programming Languages
Citations
9
Venue
arXiv.org
Last Checked
3 months ago
Abstract
Rust represents a major advancement in production programming languages because of its success in bridging the gap between high-level application programming and low-level systems programming. At the heart of its design lies a novel approach to ownership that remains highly programmable. In this talk, we will describe our ongoing work on designing a formal semantics for Rust that captures ownership and borrowing without the details of lifetime analysis. This semantics models a high-level understanding of ownership and as a result is close to source-level Rust (but with full type annotations) which differs from the recent RustBelt effort that essentially models MIR, a CPS-style IR used in the Rust compiler. Further, while RustBelt aims to verify the safety of unsafe code in Rust's standard library, we model standard library APIs as primitives, which is sufficient to reason about their behavior. This yields a simpler model of Rust and its type system that we think researchers will find easier to use as a starting point for investigating Rust extensions. Unlike RustBelt, we aim to prove type soundness using progress and preservation instead of a Kripke logical relation. Finally, our semantics is a family of languages of increasing expressive power, where subsequent levels have features that are impossible to define in previous levels. Following Felleisen, expressive power is defined in terms of observational equivalence. Separating the language into different levels of expressive power should provide a framework for future work on Rust verification and compiler optimization.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Programming Languages
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Tensor Comprehensions: Framework-Agnostic High-Performance Machine Learning Abstractions
R.I.P.
π»
Ghosted
Glow: Graph Lowering Compiler Techniques for Neural Networks
R.I.P.
π»
Ghosted
Learnable Programming: Blocks and Beyond
R.I.P.
π»
Ghosted
Scenic: A Language for Scenario Specification and Scene Generation
R.I.P.
π»
Ghosted
Vandal: A Scalable Security Analysis Framework for Smart Contracts
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted