Toward automated feature model configuration with optimizing non-functional requirements |
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| Affiliation: | 1. Simon Fraser University, 8888 University Dr, Burnaby, BC V5A 1S6, Canada;2. Athabasca University, 1 University Drive, Athabasca, AB T9S 3A3, Canada;3. Ryerson University, 350 Victoria St, Toronto, ON M5B 2K3, Canada;1. Hong Kong Institute of Vocational Education, Hong Kong, +852 60161161; kleung@computer.org;2. Siemens AG, Germany;3. University of Seville, Spain, Tel.: +34 954553866; splc2012specialsection@gmail.com;1. Technology Center of Software Engineering, Institute of Software, Chinese Academy of Sciences, Beijing 100190, China;2. Graduate University, Chinese Academy of Sciences, Beijing 100190, China;3. State Key Laboratory of Computer Science, Beijing 100190, China;1. AtlanMod, École des Mines de Nantes - INRIA - LINA, 4 rue Alfred Kastler, 44307 Nantes, France;2. ISSI-DSIC, Universitat Politècnica de València, Cno. de Vera, s/n, 46022 Valencia, Spain;3. Programa de Pós Graduação em Informática, Departamento de Ciência da Computação, Instituto de Matemática, Universidade Federal do Rio De Janeiro, Brazil;4. Instituto Tecnológico de Informática, Universitat Politècnica de València, Cno. de Vera, s/n, 46022 Valencia, Spain |
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| Abstract: | ContextA software product line is a family of software systems that share some common features but also have significant variabilities. A feature model is a variability modeling artifact, which represents differences among software products with respect to the variability relationships among their features. Having a feature model along with a reference model developed in the domain engineering lifecycle, a concrete product of the family is derived by binding the variation points in the feature model (called configuration process) and by instantiating the reference model.ObjectiveIn this work we address the feature model configuration problem and propose a framework to automatically select suitable features that satisfy both the functional and non-functional preferences and constraints of stakeholders. Additionally, interdependencies between various non-functional properties are taken into account in the framework.MethodThe proposed framework combines Analytical Hierarchy Process (AHP) and Fuzzy Cognitive Maps (FCM) to compute the non-functional properties weights based on stakeholders’ preferences and interdependencies between non-functional properties. Afterwards, Hierarchical Task Network (HTN) planning is applied to find the optimal feature model configuration.ResultOur approach improves state-of-art of feature model configuration by considering positive or negative impacts of the features on non-functional properties, the stakeholders’ preferences, and non-functional interdependencies. The approach presented in this paper extends earlier work presented in 1] from several distinct perspectives including mechanisms handling interdependencies between non-functional properties, proposing a novel tooling architecture, and offering visualization and interaction techniques for representing functional and non-functional aspects of feature models.Conclusionour experiments show the scalability of our configuration approach when considering both functional and non-functional requirements of stakeholders. |
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| Keywords: | Software product lines Feature model configuration Stakeholders’ preferences Non-functional interdependencies |
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