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Detecting commonality and variability in use-case diagram variants

Author(s)
RA'FAT AL-MSIE'DEEN, Department of Software Engineering, Faculty of IT, Mutah University, Mutah 61710, Karak, Jordan
ANAS H. BLASI, Department of Data Science, Faculty of IT, Mutah University, Mutah 61710, Karak, Jordan
HAMZEH EYAL SALMAN Department of Software Engineering, Faculty of IT, Mutah University, Mutah 61710, Karak, Jordan
SAQER S. ALJA’AFREH Department of Electrical Engineering, Faculty of Engineering, Mutah University, Karak, Jordan
AHMAD ABADLEH Department of Computer Science, Faculty of IT, Mutah University, Mutah 61710, Karak, Jordan
MOHAMMED A. ALSUWAIKET Department of CS and Engineering Technology, Hafar Batin University, Hafar Batin, Saudi Arabia
AWNI HAMMOURI Department of Data Science, Faculty of IT, Mutah University, Mutah 61710, Karak, Jordan
ASMAA JAMEEL AL NAWAISEH Department of Software Engineering, Faculty of IT, Mutah University, Mutah 61710, Karak, Jordan
WAFA TARAWNEH Department of Software Engineering, Faculty of IT, Mutah University, Mutah 61710, Karak, Jordan
SULEYMAN A. AL-SHOWARAH Department of Software Engineering, Faculty of IT, Mutah University, Mutah 61710, Karak, Jordan
Abstract
The use-case diagram is a software artifact. Thus, as with any software artifact, the use-case diagrams change across time through the software development life cycle. Therefore, several versions of the same diagram are existed at distinct times. Thus, comparing all use-case diagram variants to detect common and variable usecases becomes one of the main challenges in the product line reengineering field. The contribution of this paper is to suggest an automatic approach to compare a collection of use-case diagram variants and detect both commonality and variability. In our work, every use-case represents a feature. The proposed approach visualizes the detected features using formal concept analysis, where common and variable features are introduced to software engineers. The proposed approach was applied on a mobile media case study to be validated. The findings confirm the importance and the performance of the suggested approach as all common and variable features were precisely detected via formal concept analysis and latent semantic indexing.
Publication Details
Page(s) 1113-1126
DOI DOI not available
Published Journal: Journal of Theoretical and Applied Information Technology, Volume: 100, Issue: 4, Year: 2022

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Keywords
variability, Commonality, Formal Concept Analysis, Latent Semantic Indexing, Use-case Diagram Variants
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