A Co-Evolution Analysis for Software Product Lines: An Approach based on Evolutionary Trees
Anissa Benlarabi,
Amal Khtira and
Bouchra El Asri
Additional contact information
Anissa Benlarabi: National School of Computer Science and Systems Analysis (ENSIAS), University Mohamed V, Rabat, Morocco
Amal Khtira: National School of Computer Science and Systems Analysis (ENSIAS), University Mohamed V, Rabat, Morocco
Bouchra El Asri: National School of Computer Science and Systems Analysis (ENSIAS), University Mohamed V, Rabat, Morocco
International Journal of Applied Evolutionary Computation (IJAEC), 2015, vol. 6, issue 3, 9-32
Abstract:
In this rapidly changing world, business strategies continuously evolve to meet customers' wishes. Hence, the ability to cope with the frequent business changes is becoming important criteria of a leading development paradigm. Software product line engineering is a development paradigm based on reuse that builds a common platform from which a set of applications can be derived. Despite its advantage of enhancing time to market and costs, it is exposed to the risk of falling into the aging phenomenon because of the complexity of its evolution. In this paper the authors present a co-evolution based approach for protecting the software product lines from the aging phenomenon. The approach uses cladistics and trees reconciliation that are mainly used in biology to analyze the co-evolution between organisms. The authors' major goal is to find out changes of products that were not propagated to the common platform at the aim of reconsidering them in the platform and thus protecting it from being obsolete.
Date: 2015
References: Add references at CitEc
Citations:
Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 018/IJAEC.2015070102 (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:igg:jaec00:v:6:y:2015:i:3:p:9-32
Access Statistics for this article
International Journal of Applied Evolutionary Computation (IJAEC) is currently edited by Sukhpal Singh Gill
More articles in International Journal of Applied Evolutionary Computation (IJAEC) from IGI Global
Bibliographic data for series maintained by Journal Editor ().