Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Optimized feature selection with crosscutting concerns in software product line feature model

Full metadata record
DC Field Value Language
dc.contributor.authorAbbas, Asad-
dc.contributor.authorWu, Zhiqiang-
dc.contributor.authorSiddiqui, Isma Farah-
dc.contributor.authorLee, Scott Uk-Jin-
dc.date.accessioned2021-06-22T17:23:30Z-
dc.date.available2021-06-22T17:23:30Z-
dc.date.issued2016-01-
dc.identifier.urihttps://scholarworks.bwise.kr/erica/handle/2021.sw.erica/14600-
dc.description.abstractSoftware Product Line Engineering (SPLE) is best paradigm to build new products with high reusability from existing resources. Feature model is commonly used for resource management with variable and common features under product line. Key idea of feature model is to manage commonalities and variabilities of resources with mandatory, alternative and optional features. Crosscutting concerns are tangled and scattered in overall system which reduce the reusability of resources because of dependency with other features. At modeling level, the identification of these features is an important task to construct them as a separate aspect module. As a result, the addition or deletion of these aspects do not affect the system. In this paper we present: (1) an approach to find crosscutting concerns by using union-find algorithm, (2) genetic algorithm for optimized feature selection with resource constraints and crosscutting concerns.-
dc.format.extent3-
dc.language영어-
dc.language.isoENG-
dc.publisherSociety of Convergence and Integrated Research-
dc.titleOptimized feature selection with crosscutting concerns in software product line feature model-
dc.typeArticle-
dc.publisher.location미국-
dc.identifier.bibliographicCitationProceedings of International Conference on Information and Convergence Technology for Smart Society, v.2, no.1, pp 19 - 21-
dc.citation.titleProceedings of International Conference on Information and Convergence Technology for Smart Society-
dc.citation.volume2-
dc.citation.number1-
dc.citation.startPage19-
dc.citation.endPage21-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassother-
dc.subject.keywordAuthorSoftware product line-
dc.subject.keywordAuthorFeature model-
dc.subject.keywordAuthorUnion-find algorithm-
dc.subject.keywordAuthorGenetic algorithm-
dc.subject.keywordAuthorOptimization-
dc.identifier.urlhttps://hhhwwwuuu.github.io/assets/pdf/Asad0.pdf-
Files in This Item
Go to Link
Appears in
Collections
COLLEGE OF COMPUTING > ERICA 컴퓨터학부 > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Lee, Scott Uk Jin photo

Lee, Scott Uk Jin
ERICA 소프트웨어융합대학 (ERICA 컴퓨터학부)
Read more

Altmetrics

Total Views & Downloads

BROWSE