2026-05-28T18:30:39Zhttps://riuma.uma.es/rest/oai/requestoai:riuma.uma.es:10630/409902026-02-03T11:49:15Zcom_10630_2254col_10630_37959
RIUMA. Repositorio Institucional de la Universidad de Málaga
author
Muñoz-Guerra, Daniel Jesús
author
Gurov, Dilian
author
Pinto-Alarcón, Mónica
author
Fuentes-Fernández, Lidia
2025-12-04T09:47:20Z
2025-12-04T09:47:20Z
2021-06-24
978-3-030-79382-1
1611-3349
https://hdl.handle.net/10630/40990
10.1007/978-3-030-79382-1_24
In Software Product Line (SPL) engineering one uses Variability Models (VMs) as input to automated reasoners to generate optimal products according to certain Quality Attributes (QAs). Variability models, however, and more specifically those including numerical features (i.e., NVMs), do not natively support QAs, and consequently, neither do automated reasoners commonly used for variability resolution. However, those satisfiability and optimisation problems have been covered and refined in other relational models such as databases.
Category Theory (CT) is an abstract mathematical theory typically used to capture the common aspects of seemingly dissimilar algebraic structures. We propose a unified relational modelling framework subsuming the structured objects of VMs and QAs and their relationships into algebraic categories. This abstraction allows a combination of automated reasoners over different domains to analyse SPLs. The solutions’ optimisation can now be natively performed by a combination of automated theorem proving, hashing, balanced-trees and chasing algorithms. We validate this approach by means of the edge computing SPL tool HADAS.
eng
Ingeniería del software
Category Theory Framework for Variability Models with Non-Functional Requirements.
conference output
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URL
https://riuma.uma.es/bitstreams/87257a4a-5ecc-4641-b532-b855c0ea6762/download
File
MD5
c08bf326cad73e1668195bac6e9272ed
1204994
application/pdf
CAISE_21_Daniel_Jesus_Munoz.pdf