Trading off Complexity for Expressiveness in Programming Languages: Visions and Preliminary Experiences
October 04, 2019 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Vincenzo De Florio, Chris Blondia
arXiv ID
1910.03001
Category
cs.PL: Programming Languages
Citations
0
Venue
arXiv.org
Last Checked
4 months ago
Abstract
When programming resource-scarce embedded smart devices, the designer often requires both the low-level system programming features of a language such as C and higher level capability typical of a language like Java. The choice of a particular language typically implies trade offs between conflicting design goals such as performance, costs, and overheads. The large variety of languages, virtual machines, and translators provides the designer with a dense trade off space, ranging from minimalistic to rich full-fledged approaches, but once a choice is made it is often difficult for the designer to revise it. In this work we propose a system of light-weighted and modular extensions as a method to flexibly reshape the target programming language as needed, adding only those application layer features that match the current design goals. In so doing complexity is made transparent, but not hidden: While the programmer can benefit of higher level constructs, the designer can deal with modular building blocks each characterized by a certain algorithmic complexity and therefore each accountable for a given share of the overhead. As a result the designer is given a finer control on the amount of resources that are consumed by the run-time executive of the chosen programming language.
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