VariaMos

Author:

Mazo Raúl1,Muñoz-Fernández Juan C.2,Rincón Luisa3,Salinesi Camille1,Tamura Gabriel4

Affiliation:

1. Université Paris Panthéon, Sorbonne, Paris, France

2. Universidad Icesi, Cali, Colombia and Université Paris Panthéon, Sorbonne - Paris, France

3. Universidad Javeriana, Cali, Colombia

4. Universidad Icesi, Cali, Colombia

Publisher

ACM

Reference13 articles.

1. The DOPLER meta-tool for decision-oriented variability modeling: a multiple case study

2. B. Gonzales-Baixauli J. C. S. Prado Leite and J. Mylopoulos "Visual variability analysis for goal models " in Requirements Engineering(RE) Conference 2004. 10.1109/RE.2004.56 B. Gonzales-Baixauli J. C. S. Prado Leite and J. Mylopoulos "Visual variability analysis for goal models " in Requirements Engineering(RE) Conference 2004. 10.1109/RE.2004.56

3. Constraints

4. Defects in Product Line Models and how to identify them," in Software Product Line - Advanced Topic, A. Elfaki;Salinesi C.;Ed. InTech,2012

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1. Variability Management in Self-Adaptive Systems through Deep Learning: A Dynamic Software Product Line Approach;Electronics;2024-02-27

2. A Self-Adaptation Mechanism for Variability Management in Dynamic Software Product Lines;Proceedings of the 17th Brazilian Symposium on Software Components, Architectures, and Reuse;2023-09-25

3. Feature models to boost the vulnerability management process;Journal of Systems and Software;2023-01

4. From feature models to feature toggles in practice;Proceedings of the 26th ACM International Systems and Software Product Line Conference - Volume A;2022-09-12

5. Improving Variabilty Analysis through Scenario-Based Incompatibility Detection;Information;2022-03-11

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