A Monte Carlo tree search conceptual framework for feature model analyses

Horcas, José Miguel, Galindo, José A., Heradio, Rubén, Fernández Amoros, David y Benavides, David . (2023) A Monte Carlo tree search conceptual framework for feature model analyses. Journal of Systems and Software, Volume 195, 2023

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Título A Monte Carlo tree search conceptual framework for feature model analyses
Autor(es) Horcas, José Miguel
Galindo, José A.
Heradio, Rubén
Fernández Amoros, David
Benavides, David
Materia(s) Ingeniería Informática
Abstract Challenging domains of the future such as Smart Cities, Cloud Computing, or Industry 4.0 expose highly variable systems with colossal configuration spaces. The automated analysis of those systems’ variability has often relied on SAT solving and constraint programming. However, many of the analyses have to deal with the uncertainty introduced by the fact that undertaking an exhaustive exploration of the whole configuration space is usually intractable. In addition, not all analyses need to deal with the configuration space of the feature models, but with different search spaces where analyses are performed over the structure of the feature models, the constraints, or the implementation artifacts, instead of configurations. This paper proposes a conceptual framework that tackles various of those analyses using Monte Carlo tree search methods, which have proven to succeed in vast search spaces (e.g., game theory, scheduling tasks, security, program synthesis, etc.). Our general framework is formally described, and its flexibility to cope with a diversity of analysis problems is discussed. We provide a Python implementation of the framework that shows the feasibility of our proposal, identifying up to 11 lessons learned, and open challenges about the usage of the Monte Carlo methods in the software product line context. With this contribution, we envision that different problems can be addressed using Monte Carlo simulations and that our framework can be used to advance the state-of-the-art one step forward.
Palabras clave automated analysis
configurable systems
feature models
Monte Carlo tree search
software product lines
variability
Editor(es) Elsevier
Fecha 2023-01
Formato application/pdf
Identificador bibliuned:DptoISSI-ETSI-Articulos-Rheradio-0002
http://e-spacio.uned.es/fez/view/bibliuned:DptoISSI-ETSI-Articulos-Rheradio-0002
DOI - identifier https://doi.org/10.1016/j.jss.2022.111551
ISSN - identifier 0164-1212; eISSN: 1873-1228
Nombre de la revista Journal of Systems and Software
Número de Volumen 195
Publicado en la Revista Journal of Systems and Software, Volume 195, 2023
Idioma eng
Versión de la publicación submittedVersion
Tipo de recurso Article
Derechos de acceso y licencia http://creativecommons.org/licenses/by-nc-nd/4.0
info:eu-repo/semantics/openAccess
Tipo de acceso Acceso abierto
Notas adicionales This is a Accepted Manuscript of an article published by Elsevier in "Journal of Systems and Software, Volume 195, 2023", available at: https://doi.org/10.1016/j.jss.2022.111551
Notas adicionales Este es el manuscrito aceptado del artículo publicado por Elsevier en "Journal of Systems and Software, Volume 195, 2023", disponible en línea: https://doi.org/10.1016/j.jss.2022.111551

 
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Creado: Fri, 03 May 2024, 20:24:36 CET