RUO Principal

Repositorio Institucional de la Universidad de Oviedo

Ver ítem 
  •   RUO Principal
  • Investigación
  • Datos de investigación
  • Ver ítem
  •   RUO Principal
  • Investigación
  • Datos de investigación
  • Ver ítem
    • español
    • English
JavaScript is disabled for your browser. Some features of this site may not work without it.

Listar

Todo RUOComunidades y ColeccionesPor fecha de publicaciónAutoresTítulosMateriasxmlui.ArtifactBrowser.Navigation.browse_issnPerfil de autorEsta colecciónPor fecha de publicaciónAutoresTítulosMateriasxmlui.ArtifactBrowser.Navigation.browse_issn

Mi cuenta

AccederRegistro

Estadísticas

Ver Estadísticas de uso

AÑADIDO RECIENTEMENTE

Novedades
Repositorio
Cómo publicar
Recursos
FAQs

Data from "The StaDyn programming language"

Autor(es) y otros:
Ortín Soler, FranciscoAutoridad Uniovi; García Rodríguez, MiguelAutoridad Uniovi; García Pérez-Schofield, José Baltasar; Quiroga Álvarez, JoséAutoridad Uniovi
Palabra(s) clave:

Hybrid static and dynamic typing

Compiler optimizations

.net platform

Programming language

StaDyn

Fecha de publicación:
2022-05-22
Resumen:

Hybrid static and dynamic typing languages are aimed at combining the benefits of both kinds of languages: the early type error detection and compile-time optimizations of static typing, together with the runtime adaptability of dynamically typed languages. The StaDyn programming language is a hybrid typing language, whose main contribution is the utilization of the type information gathered by the compiler to improve compile-time error detection and runtime performance. StaDyn has been evaluated as the hybrid typing language for the .Net platform with the highest runtime performance and the lowest memory consumption. Although most optimizations are performed statically by the compiler, compilation time is yet lower than the existing hybrid languages implemented on the .Net platform.

Hybrid static and dynamic typing languages are aimed at combining the benefits of both kinds of languages: the early type error detection and compile-time optimizations of static typing, together with the runtime adaptability of dynamically typed languages. The StaDyn programming language is a hybrid typing language, whose main contribution is the utilization of the type information gathered by the compiler to improve compile-time error detection and runtime performance. StaDyn has been evaluated as the hybrid typing language for the .Net platform with the highest runtime performance and the lowest memory consumption. Although most optimizations are performed statically by the compiler, compilation time is yet lower than the existing hybrid languages implemented on the .Net platform.

Descripción:

Data from the article "F. Ortin, M. Garcia, B. Garcia Perez-Schofield, J. Quiroga. The StaDyn Programming Language. SoftwareX (20), pp. 101211-101222, 2022. https://doi.org/10.1016/j.softx.2022.101211"

URI:
https://hdl.handle.net/10651/70836
DOI:
10.17811/ruo_datasets.70836
Enlace a recurso relacionado:
http://hdl.handle.net/10651/67620
Patrocinado por:

The StaDyn programming language was partially funded by Microsoft Research, United States with the project entitled Extending Dynamic Features of the SSCLI, awarded in the Phoenix and SSCLI, Compilation and Managed Execution Request for Proposals. It was also funded by the Spanish Department of Science, Innovation, and Universities (project RTI2018-099235-B-I00) and the University of Oviedo, Spain (GR-2011-0040).

Colecciones
  • Datos de investigación [79]
  • Informática [873]
  • Investigaciones y Documentos OpenAIRE [8377]
Ficheros en el ítem
untranslated
Dataset (8.493Mb)
untranslated
Readme.txt (2.630Kb)
Métricas
Compartir
Exportar a Mendeley
Estadísticas de uso
Estadísticas de uso
Metadatos
Mostrar el registro completo del ítem
Página principal Uniovi

Biblioteca

Contacto

Facebook Universidad de OviedoTwitter Universidad de Oviedo
El contenido del Repositorio, a menos que se indique lo contrario, está protegido con una licencia Creative Commons: Attribution-NonCommercial-NoDerivatives 4.0 Internacional
Creative Commons Image