Reference Type Logic Variables in Constraint-logic Object-oriented Programming
August 24, 2018 Β· Declared Dead Β· π Workshop on Functional and Constraint Logic Programming
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Jan C. DagefΓΆrde
arXiv ID
1808.08185
Category
cs.PL: Programming Languages
Citations
3
Venue
Workshop on Functional and Constraint Logic Programming
Last Checked
4 months ago
Abstract
Constraint-logic object-oriented programming, for example using Muli, facilitates the integrated development of business software that occasionally involves finding solutions to constraint-logic problems. The availability of object-oriented features calls for the option to use objects as logic variables as well, as opposed to being limited to primitive type logic variables. The present work contributes a concept for reference type logic variables in constraint-logic object-oriented programming that takes arbitrary class hierarchies of programs written in object-oriented languages into account. The concept discusses interactions between constraint-logic object-oriented programs and reference type logic variables, particularly invocations on and access to logic variables, type operations, and equality. Furthermore, it proposes approaches as to how these interactions can be handled by a corresponding execution environment.
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