Treo: Textual Syntax for Reo Connectors
June 26, 2018 Β· Declared Dead Β· π MeTRiD@ETAPS
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Kasper Dokter, Farhad Arbab
arXiv ID
1806.09852
Category
cs.PL: Programming Languages
Cross-listed
cs.SE
Citations
12
Venue
MeTRiD@ETAPS
Last Checked
3 months ago
Abstract
Reo is an interaction-centric model of concurrency for compositional specification of communication and coordination protocols. Formal verification tools exist to ensure correctness and compliance of protocols specified in Reo, which can readily be (re)used in different applications, or composed into more complex protocols. Recent benchmarks show that compiling such high-level Reo specifications produces executable code that can compete with or even beat the performance of hand-crafted programs written in languages such as C or Java using conventional concurrency constructs. The original declarative graphical syntax of Reo does not support intuitive constructs for parameter passing, iteration, recursion, or conditional specification. This shortcoming hinders Reo's uptake in large-scale practical applications. Although a number of Reo-inspired syntax alternatives have appeared in the past, none of them follows the primary design principles of Reo: a) declarative specification; b) all channel types and their sorts are user-defined; and c) channels compose via shared nodes. In this paper, we offer a textual syntax for Reo that respects these principles and supports flexible parameter passing, iteration, recursion, and conditional specification. In on-going work, we use this textual syntax to compile Reo into target languages such as Java, Promela, and Maude.
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