Cited By
View all- Ben Sassi SEdded SMazo RBen Ghezala HSalinesi C(2023)Colla-ConfigJournal of Systems and Software10.1016/j.jss.2022.111586197:COnline publication date: 1-Mar-2023
Runtime collaborative-based configuration of software product lines
Pages 94 - 96
Abstract
Software Product Line (SPL) configuration practices have been employed by industries as a mass customization process. However, the inherent variability of large SPLs leads to configuration spaces of exponential sizes. Thus, scalability and performance concerns start to be an issue when facing runtime environments, since it is usually infeasible to explore the entire configuration space exhaustively. In this context, the aim of my research is therefore to propose an efficient collaborative-based runtime approach that relies on recommender techniques to provide accurate and scalable configurations to users. To demonstrate the efficiency of the proposed approach, I conduct series of experiments on real-world SPLs. In addition, I plan empirically verify through a user case study the usability of the proposed approach. My expected contribution is to support the adoption of SPL configuration practices in industrial scenarios.
References
[1]
M. Asadi, S. Soltani, D. Gasevic, M. Hatala, and E. Bagheri. Toward Automated Feature Model Configuration with Optimizing Non-Functional Requirements. Inform. and Software Technology, 56(9):1144--1165, 2014.
[2]
E. Bagheri and F. Ensan. Dynamic Decision Models for Staged Software Product Line Configuration. Req. Engineering, 19(2):187--212, 2014.
[3]
K. Constantino, J. A. Pereira, J. Padilha, P. Vasconcelos, and E. Figueiredo. An Empirical Study of Two Software Product Line Tools. In Proceedings of the International Conference on Evaluation of Novel Approaches to Software Engineering (ENASE), pp. 164--171, 2016.
[4]
J. A. Galindo, D. Dhungana, R. Rabiser, D. Benavides, G. Botterweck, and P. Grünbacher. Supporting Distributed Product Configuration by Integrating Heterogeneous Variability Modeling Approaches. Information and Software Technology, 62:78--100, 2015.
[5]
L. Ochoa, J. A. Pereira, o. González-Rojas, H. Castro, and G. Saake. A Survey on Scalability and Performance Concerns in Extended Product Lines Configuration. In Proceedings of the Workshop on Variability Modelling of Software-intensive Systems (VaMoS), pp. 5--12. ACM, 2017.
[6]
J. A. Pereira, K. Constantino, and E. Figueiredo. A Systematic Literature Review of Software Product Line Management Tools. In Proceedings of the International Conference on Software Reuse (ICSR), pp. 73--89. Springer, 2015.
[7]
J. A. Pereira, S. Krieter, J. Meinicke, R. Schröter, G. Saake, and T. Leich. FeatureIDE: Scalable Product Configuration of Variable Systems. In Proceedings of the International Conference on Software Reuse (ICSR), pp. 397--401. Springer, 2016.
[8]
J. A. Pereira, P. Matuszyk, S. Krieter, M. Spiliopoulou, and G. Saake. A Feature-Based Personalized Recommender System for Product-Line Configuration. In Proceedings of the International Conference on Generative Programming and Component Engineering (GPCE), pp. 120-- 131. ACM, 2016.
[9]
J. A. Pereira, C. Souza, E. Figueiredo, R. Abilio, G. Vale, and H. A. X. Costa. Software Variability Management: An Exploratory Study with Two Feature Modeling Tools. In Proceedings of the Brazilian Symposium on Software Components, Architectures and Reuse (SBCARS), pp. 20--29. IEEE, 2013.
[10]
L. Tan, Y. Lin, and L. Liu. Quality Ranking of Features in Software Product Line Engineering. In Proceedings of the Asia-Pacific Software Engineering Conference (APSEC), volume 2, pp. 57--62. IEEE, 2014.
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Published In
May 2017
558 pages
ISBN:9781538615898
- General Chair:
- Sebastian Uchitel,
- Program Chairs:
- Alessandro Orso,
- Martin Robillard
Sponsors
- SIGSOFT: ACM Special Interest Group on Software Engineering
- IEEE-CS: Computer Society
- SADIO: SADIO
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IEEE Press
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Published: 20 May 2017
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ICSE '17
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- SIGSOFT
- IEEE-CS
- SADIO
ICSE '17: 39th International Conference on Software Engineering
May 20 - 28, 2017
Buenos Aires, Argentina
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View all- Ben Sassi SEdded SMazo RBen Ghezala HSalinesi C(2023)Colla-ConfigJournal of Systems and Software10.1016/j.jss.2022.111586197:COnline publication date: 1-Mar-2023
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