Answer-Type Modification without Tears: Prompt-Passing Style Translation for Typed Delimited-Control Operators
June 21, 2016 Β· Declared Dead Β· π IASTED International Multi-Conference on Wireless and Optical Communications
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Ikuo Kobori, Yukiyoshi Kameyama, Oleg Kiselyov
arXiv ID
1606.06379
Category
cs.PL: Programming Languages
Cross-listed
cs.LO
Citations
8
Venue
IASTED International Multi-Conference on Wireless and Optical Communications
Last Checked
3 months ago
Abstract
The salient feature of delimited-control operators is their ability to modify answer types during computation. The feature, answer-type modification (ATM for short), allows one to express various interesting programs such as typed printf compactly and nicely, while it makes it difficult to embed these operators in standard functional languages. In this paper, we present a typed translation of delimited-control operators shift and reset with ATM into a familiar language with multi-prompt shift and reset without ATM, which lets us use ATM in standard languages without modifying the type system. Our translation generalizes Kiselyov's direct-style implementation of typed printf, which uses two prompts to emulate the modification of answer types, and passes them during computation. We prove that our translation preserves typing. As the naive prompt-passing style translation generates and passes many prompts even for pure terms, we show an optimized translation that generate prompts only when needed, which is also type-preserving. Finally, we give an implementation in the tagless-final style which respects typing by construction.
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