2026-06-01T09:55:43Zhttps://riuma.uma.es/rest/oai/request

oai:riuma.uma.es:10630/409912026-02-03T12:18:44Zcom_10630_2254col_10630_37959

Nemo: A Tool to Transform Feature Models with Numerical Features and Arithmetic Constraints. Muñoz-Guerra, Daniel Jesús Oh, Jeho Pinto-Alarcón, Mónica Fuentes-Fernández, Lidia Batory, Don Ingeniería del software Real-world Software Product Lines (SPLs) need Numerical Feature Models (NFMs) whose features not only have boolean values satisfying boolean constraints, but also have numeric attributes satisfying arithmetic constraints. A key operation on NFMs finds near-optimal performing products, which requires counting the number of SPL products. Typical constraint satisfaction solvers perform poorly on counting. Nemo (Numbers, features, models) supports NFMs by bit-blasting, the technique that encodes arithmetic as boolean clauses. Nemo translates NFMs to propositional formulas whose products can be counted efficiently by #SAT solvers, enabling near-optimal products to be found. We evaluate Nemo with a diverse set of real-world NFMs, complex arithmetic constraints, and counting experiments in this paper. 2025-12-04T10:13:03Z 2025-12-04T10:13:03Z 2025-12-04T10:13:03Z 2022-06-10 conference output 978-3-031-08129-3 1611-3349 https://hdl.handle.net/10630/40991 10.1007/978-3-031-08129-3_4 eng 20th International Conference on Software and Systems Reuse, ICSR 2022 Montpellier, Francia 15 a 17 Junio info:eu-repo/grantAgreement/EC/H2020/101017109/EU/Network intelligence for aDAptive and sElf-learning MObile Networks/DAEMON info:eu-repo/grantAgreement/Junta de Andalucia/FEDER/UMA18-FEDERJA-15/ES/LEIA/LEIA info:eu-repo/grantAgreement/Ministerio de Ciencia e Innovacion/Retos Investigacion/RTI2018-099213-B-I00/ES/Metodologías para el Desarrollo de Aplicaciones IoT de Extremo a Extremo/MEDEA info:eu-repo/grantAgreement/Junta de Andalucia/PAIDI 2020/P18-FR-1081/ES/Reingeniería para la Heterogeneidad y Evolución de Aplicaciones/Rhea info:eu-repo/grantAgreement/Ministerio de Ciencia e Innovacion/FPI/PRE2019-087496/ES/Ayudas para contratos predoctorales para la formación de doctores/PRE2019 open access Springer Nature