Mostrar el registro sencillo del ítem

dc.contributor.author
Araujo, Pedro Bernabé  
dc.contributor.author
Rodriguez, Sebastian Alberto  
dc.contributor.author
Hilaire, Vincent  
dc.date.available
2018-09-07T19:23:51Z  
dc.date.issued
2018-02  
dc.identifier.citation
Araujo, Pedro Bernabé; Rodriguez, Sebastian Alberto; Hilaire, Vincent; A metamodeling approach for the identification of organizational smells in multi-agent systems: application to ASPECS; Springer; Artificial Intelligence Review; 49; 2; 2-2018; 183-210  
dc.identifier.issn
0269-2821  
dc.identifier.uri
http://hdl.handle.net/11336/58809  
dc.description.abstract
Software Quality is one of the most important subjects in the Process Development Software, especially in large and complex systems. Much effort has been devoted to the development of techniques and concepts to improve software quality over the years. We are especially interested on smells, which represent anomalies or flaws in the design/code that can have serious consequences in maintenance or future development of the systems. These techniques have a strong development in the Object Oriented paradigm, however, very few studies were conducted in the agent oriented paradigm. In this paper we focus on the detection of design smells applied to multi-agent systems models based on the organizational approach, named Organizational Design Smells (ODS). Early and automatic detection of these ODS allows reducing the costs and development times, while increasing the final product’s quality. To achieve this objective, validation rules were defined based in the EVL language. The approach is illustrated with two examples, their validation rules, and the refactoring solutions proposed.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
Springer  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.subject
Agent Oriented Software Engineering  
dc.subject
Design Smells  
dc.subject
Organization Approach  
dc.subject
Validation Rules  
dc.subject.classification
Ciencias de la Computación  
dc.subject.classification
Ciencias de la Computación e Información  
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS  
dc.title
A metamodeling approach for the identification of organizational smells in multi-agent systems: application to ASPECS  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2018-09-04T16:35:57Z  
dc.journal.volume
49  
dc.journal.number
2  
dc.journal.pagination
183-210  
dc.journal.pais
Alemania  
dc.journal.ciudad
Berlín  
dc.description.fil
Fil: Araujo, Pedro Bernabé. Universidad Tecnológica Nacional. Facultad Regional Tucumán. Centro de Investigación en Tecnologías Avanzadas de Tucumán; Argentina  
dc.description.fil
Fil: Rodriguez, Sebastian Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán; Argentina. Universidad Tecnológica Nacional. Facultad Regional Tucumán. Centro de Investigación en Tecnologías Avanzadas de Tucumán; Argentina  
dc.description.fil
Fil: Hilaire, Vincent. Universite de Technologie de Belfort-Montbéliard. Institut de Recherche sur les Transports, l'Energie et la Société; Francia  
dc.journal.title
Artificial Intelligence Review  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://link.springer.com/article/10.1007%2Fs10462-016-9521-7  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/https://dx.doi.org/10.1007/s10462-016-9521-7