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Memorias de investigación
Ponencias en congresos:
morph-GraphQL: GraphQL Servers Generation from R2RML Mappings
Año:2019
Áreas de investigación
  • Ciencias de la computación y tecnología informática
Datos
Descripción
REST has become in the last decade the most common manner to provide web services, yet it was not originally designed to handle typical modern applications (e.g., mobile apps). GraphQL was released publicly in 2015 and since then has gained momentum as an alternative approach to REST. However, generating and maintaining GraphQL resolvers is not easy. First, a domain expert has to analyse a dataset, design the corresponding GraphQL schema and map the dataset to the schema. Then, a software engineer (e.g., GraphQL developer) implements the corresponding GraphQL resolvers in a specific programming language. In this paper we present an approach that generates GraphQL resolvers from declarative mappings specification in the W3C Recommendation R2RML, hence, can be used both by a domain expert as without the need to involve software developers to implement the resolvers, and by software developers as the initial version of the resolvers to be implemented. Our approach is implemented in morph-GraphQL.
Internacional
Si
Nombre congreso
The 31st International Conference on Software Engineering & Knowledge Engineering
Tipo de participación
960
Lugar del congreso
Lisboa, Portugal
Revisores
Si
ISBN o ISSN
2325-9086
DOI
10.18293/SEKE2019-055
Fecha inicio congreso
10/07/2019
Fecha fin congreso
12/07/2019
Desde la página
291
Hasta la página
297
Título de las actas
The 31st International Conference on Software Engineering and Knowledge Engineering, SEKE 2019, Hotel Tivoli, Lisbon, Portugal, July 10-12, 2019.
Esta actividad pertenece a memorias de investigación
Participantes
  • Autor: Freddy Priyatna . (UPM)
  • Autor: David Chaves Fraga (UPM)
  • Autor: Ahmad Alobaid . (UPM)
  • Autor: Oscar Corcho Garcia (UPM)
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Ontology Engineering Group
  • Departamento: Inteligencia Artificial
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