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Software product line (SPL) now faces major scalability problems because of technical advances of the past decades. However, using traditional approaches of software engineering to deal with this increasing scalability is not feasible. Therefore, new techniques must be provided in order to resolve scalability issues. For such a purpose, we propose through this paper a modularization approach according to two dimensions: In the first dimension we use Island algorithm in order to obtain structural modules. In the second dimension we decompose obtained modules according to features binding time so as to obtain dynamic submodules.

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Feature modeling is used to express commonality and variability among a family of software products called the software product line. To offer customized products to their customers, organizations need to build packages of features taking into consideration customer needs and preferences. This paper presents a platform named SPLP (Software Product Line Profiling) which allows pre-configuring feature models through the restriction of the configuration space to meet the requirements of a specific market segment. Considering that concerns and preferences of this latter are a key criteria to achieve a tailored pre-configuration, authors propose the integration of user profiling in the SPLP platform through the definition of a user profile model describing information about the user and the products he is used to consume. This information is then exploited by the SPLP platform to perform an automated pre-configuration according to each user profile requirements and preferences.