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Traceability Link Recovery between Requirements and Models using an Evolutionary Algorithm Guided by a Learning to Rank Algorithm: Train control and management case

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Traceability Link Recovery between Requirements and Models using an Evolutionary Algorithm Guided by a Learning to Rank Algorithm: Train control and management case

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Marcén, AC.; Lapeña, R.; Pastor López, O.; Cetina, C. (2020). Traceability Link Recovery between Requirements and Models using an Evolutionary Algorithm Guided by a Learning to Rank Algorithm: Train control and management case. Journal of Systems and Software. 163:1-24. https://doi.org/10.1016/j.jss.2020.110519

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Título: Traceability Link Recovery between Requirements and Models using an Evolutionary Algorithm Guided by a Learning to Rank Algorithm: Train control and management case
Autor: Marcén, Ana C. Lapeña, Raúl Pastor López, Oscar Cetina, Carlos
Entidad UPV: Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació
Fecha difusión:
Resumen:
[EN] Traceability Link Recovery (TLR) has been a topic of interest for many years within the software engineering community. In recent years, TLR has been attracting more attention, becoming the subject of both fundamental ...[+]
Palabras clave: Traceability link recovery , Requirements engineering , Models , Evolutionary algorithm , Learning to rank
Derechos de uso: Reconocimiento - No comercial - Sin obra derivada (by-nc-nd)
Fuente:
Journal of Systems and Software. (issn: 0164-1212 )
DOI: 10.1016/j.jss.2020.110519
Editorial:
Elsevier
Versión del editor: https://doi.org/10.1016/j.jss.2020.110519
Código del Proyecto:
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-096411-B-I00/ES/ASISTENTES EVOLUTIVOS INTELIGENTES PARA INICIAR LINEAS DE PRODUCTO SOFTWARE/
info:eu-repo/grantAgreement/MINECO//TIN2016-80811-P/ES/UN METODO DE PRODUCCION DE SOFTWARE DIRIGIDO POR MODELOS PARA EL DESARROLLO DE APLICACIONES BIG DATA/
info:eu-repo/grantAgreement/GVA//PROMETEO%2F2018%2F176/ES/GISPRO-GENOMIC INFORMATION SYSTEMS PRODUCTION/
info:eu-repo/grantAgreement/GVA//ACIF%2F2018%2F171/
Agradecimientos:
This work has been developed with the financial support of the Spanish State Research Agency and the Generalitat Valenciana under the projects DataME TIN2016-80811-P, ALPS RT12018-096411-B-100, ACIF/2018/171 and ...[+]
Tipo: Artículo

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