Completing the Functional Approach in Object-Oriented Languages
December 04, 2024 Β· Declared Dead Β· π A Second Soul
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Martin Pluemicke
arXiv ID
2412.03126
Category
cs.PL: Programming Languages
Citations
0
Venue
A Second Soul
Last Checked
4 months ago
Abstract
Over the last two decades practically all object-oriented programming languages have introduced features that are well-known from functional programming languages. But many features that were introduced were fragmentary. In Java-TX we address the latter features and propose a completion. Java-TX (i.e. Type eXtended) is a language based on Java. The predominant new features are global type inference and real function types for lambda expressions. Global type inference means that all type annotations can be omitted, and the compiler infers them without losing the static type property. We introduce the function types in a similar fashion as in Scala but additionally integrated them into the Java target-typing as proposed in the so-called strawman approach. In this paper, we provide an integrated presentation of all Java-TX features. The focus is therby on the automatic inference of type parameters for classes and their methods, and on the heterogeneous translation of function types, which permits the preservation of the argument and return types in bytecode.
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