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https://repositorio.usj.es/handle/123456789/894
Título : | Evaluating the benefits of empowering model-driven development with a machine learning classifier |
Autor: | Marcén Terraza, Ana Cristina
Pérez Pérez, Francisca Pastor Lopez, Oscar Cetina, Carlos |
Palabras clave : | Data-oriented software systems; Machine learning; Model-driven development |
Fecha de publicación: | 6-ago-2022 |
Editorial : | Wiley |
Citación : | Marcén AC, Pérez F, Pastor Ó, Cetina C. Evaluating the benefits of empowering model-driven development with a machine learning classifier. Softw Pract Exper. 2022;52(11):2439-2455. doi: 10.1002/spe.3133 |
Resumen : | Increasingly, the model driven engineering (MDE) community is paying more attention to the techniques offered by the machine learning (ML) community. This has led to the application ofML techniques to MDE related tasks in hope of increasing the current benefits of MDE.Nevertheless, there is a lack of empirical experiments that evaluate the benefits that ML brings to MDE. In this work, we evaluate the benefits of empowering model engineers of model-driven development (MDD) with an ML classifier. To do this, we tackled how to embed the ML classifier as part of the MDD. Then, this was evaluated using two different real industrial cases. Our results show that despite the ML part takes an extra effort, the use of theML classifier pays off in terms of the quality results, the perceived usefulness, and intention to use. |
URI : | https://repositorio.usj.es/handle/123456789/894 |
ISSN : | 1097-024X |
Aparece en las colecciones: | Artículos de revistas |
Ficheros en este ítem:
Fichero | Descripción | Tamaño | Formato | |
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Evaluating the benefits of empowering model-driven.pdf | 2,48 MB | Adobe PDF | Visualizar/Abrir |
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