Feature Models Preconfiguration Based on User Profiling | Zendy

Ikram Dehmouch | Zendy; Bouchra El Asri | Zendy; Maryem Rhanoui | Zendy; Mina El Maallam | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Feature Models Preconfiguration Based on User Profiling

Author(s) -

Ikram Dehmouch,

Bouchra El Asri,

Maryem Rhanoui,

Mina El Maallam

Publication year - 2019

Publication title -

computer and information science

Language(s) - English

Resource type - Journals

eISSN - 1913-8997

pISSN - 1913-8989

DOI - 10.5539/cis.v12n1p59

Subject(s) - profiling (computer programming) , computer science , software , feature model , software product line , feature (linguistics) , user requirements document , software engineering , data mining , human–computer interaction , software development , linguistics , philosophy , programming language , operating system

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.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research