Refinements for Multiparty Message-Passing Protocols: Specification-agnostic theory and implementation
July 12, 2024 Β· Declared Dead Β· π Dagstuhl Artifacts Ser.
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Vassor Martin, Yoshida Nobuko
arXiv ID
2407.09106
Category
cs.PL: Programming Languages
Citations
5
Venue
Dagstuhl Artifacts Ser.
Last Checked
3 months ago
Abstract
Multiparty message-passing protocols are notoriously difficult to design, due to interaction mismatches that lead to errors such as deadlocks. Existing protocol specification formats have been developed to prevent such errors (e.g. multiparty session types (MPST)). In order to further constrain protocols, specifications can be extended with refinements, i.e. logical predicates to control the behaviour of the protocol based on previous values exchanged. Unfortunately, existing refinement theories and implementations are tightly coupled with specification formats. This paper proposes a framework for multiparty message-passing protocols with refinements and its implementation in Rust. Our work decouples correctness of refinements from the underlying model of computation, which results in a specification-agnostic framework. Our contributions are threefold. First, we introduce a trace system which characterises valid refined traces, i.e. a sequence of sending and receiving actions correct with respect to refinements. Second, we give a correct model of computation named refined communicating system (RCS), which is an extension of communicating automata systems with refinements. We prove that RCS only produce valid refined traces. We show how to generate RCS from mainstream protocol specification formats, such as refined multiparty session types (RMPST) or refined choreography automata. Third, we illustrate the flexibility of the framework by developing both a static analysis technique and an improved model of computation for dynamic refinement evaluation. Finally, we provide a Rust toolchain for decentralised RMPST, evaluate our implementation with a set of benchmarks from the literature, and observe that refinement overhead is negligible.
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