Modeling and Selection of Interdependent Software Requirements Using Fuzzy Graphs

Article

Mougouei, Davoud and Powers, David M. W.. 2017. "Modeling and Selection of Interdependent Software Requirements Using Fuzzy Graphs." International Journal of Fuzzy Systems. 19 (6), pp. 1812-1828. https://doi.org/10.1007/s40815-017-0364-4
Article Title

Modeling and Selection of Interdependent Software Requirements Using Fuzzy Graphs

ERA Journal ID39678
Article CategoryArticle
AuthorsMougouei, Davoud (Author) and Powers, David M. W. (Author)
Journal TitleInternational Journal of Fuzzy Systems
Journal Citation19 (6), pp. 1812-1828
Number of Pages17
Year2017
Place of PublicationGermany
ISSN1562-2479
Digital Object Identifier (DOI)https://doi.org/10.1007/s40815-017-0364-4
Web Address (URL)https://link.springer.com/article/10.1007/s40815-017-0364-4
Abstract

Software requirement selection is to find an optimal set of requirements that gives the highest value for a release of software while keeping the cost within the budget. However, value-related dependencies among software requirements may impact the value of an optimal set. Moreover, value-related dependencies can be of varying strengths. Hence, it is important to consider both the existence and the strengths of value-related dependencies during a requirement selection. The existing selection models, however, either assume that software requirements are independent or they ignore strengths of requirement dependencies. This paper presents a cost-value optimization model that considers the impacts of value-related requirement dependencies on the value of selected requirements (optimal set). We have exploited algebraic structure of fuzzy graphs for modeling value-related requirement dependencies and their strengths. Validity and practicality of the work are verified through carrying out several simulations and studying a real world software project.

KeywordsDependency; Fuzzy; Requirement; Selection; Software
Contains Sensitive ContentDoes not contain sensitive content
ANZSRC Field of Research 2020460299. Artificial intelligence not elsewhere classified
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Byline AffiliationsFlinders University
Institution of OriginUniversity of Southern Queensland
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