Toward Recovering Component-based Software Product Line Architecture from Object-Oriented Product Variants - LIRMM - Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier Accéder directement au contenu
Communication Dans Un Congrès Année : 2016

Toward Recovering Component-based Software Product Line Architecture from Object-Oriented Product Variants

Résumé

Usually, companies meet different customer needs in a particular domain by developing variants of a software product. This is often performed by ad-hoc copying and modifying of various existing variants to fit purposes of new one. As the number of product variants grows, such an ad-hoc development causes severe problems to maintain these variants. Software Product Line Engineering (SPLE) can be helpful here by supporting a large-scale reuse in a systematic way. SPL architecture (SPLA) is a key asset as it is used to derive architecture for each product in SPL. Unfortunately, developing SPLA from scratch is a costly task. In this paper, we propose an approach to contribute for recovering SPLA from existing product variants. This contribution is two-fold. Firstly, identifying common features and variation points of features of a given collection of product variants. Secondly, exploiting commonality and variability in terms of features to identify mandatory components and variation points of components as an important step in this recovering process. To validate the proposed approach, we applied it to two case studies. The experimental results proved the effectiveness of our approach.
Fichier principal
Vignette du fichier
973ad975ef2d461af11fe344d047bd14df1a.pdf (287.08 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

lirmm-01376027 , version 1 (09-05-2019)

Identifiants

Citer

Hamzeh Eyal-Salman, Abdelhak-Djamel Seriai. Toward Recovering Component-based Software Product Line Architecture from Object-Oriented Product Variants. SEKE: Software Engineering and Knowledge Engineering, Jul 2016, San Francisco, United States. pp.1-7, ⟨10.18293/SEKE2016-066⟩. ⟨lirmm-01376027⟩
162 Consultations
102 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More