dc.contributor.author | King’ori, Ann W. | |
dc.contributor.author | Muketha, Geoffrey M. | |
dc.contributor.author | Ndia, John G. | |
dc.date.accessioned | 2024-04-23T09:10:02Z | |
dc.date.available | 2024-04-23T09:10:02Z | |
dc.date.issued | 2024-03 | |
dc.identifier.citation | International Journal of Software Engineering & Applications (IJSEA), Vol.15, No.2, March 2024 | en_US |
dc.identifier.uri | chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://aircconline.com/ijsea/V15N2/15224ijsea01.pdf | |
dc.identifier.uri | http://repository.mut.ac.ke:8080/xmlui/handle/123456789/6435 | |
dc.identifier.uri | https://doi.org/10.5121/ijsea.2024.15201 | |
dc.description.abstract | Nowadays, software designers have adopted modelling languages that help to communicate the dynamic behavior of UML behavioral diagrams. As it is with other software artefacts, these diagrams tend to get more complex every-time they are modified. Although researchers have in the past proposed metrics to evaluate their complexity, these cannot be directly applied on UML behavioral diagrams due to their unique features. In this paper, we identify three complexity perspectives for UML behavioral diagrams, namely, element, control flow and interaction perspectives. We then define metrics under each complexity perspective. The metrics are either derived from existing UML metrics or from existing software metrics. Metrics values were computed from six behavioral diagrams, and the results reveal that they are intuitional. The metrics were also compared with existing metrics and results indicate that the proposed metrics are more complete when evaluating the behavior of an entire system in multiple perspectives. Finally, we validate the metrics using Weyuker’s nine properties. Results indicate that our metrics satisfy the theoretical requirements of soundness implying that they are correctly defined. | en_US |
dc.language.iso | en | en_US |
dc.publisher | International Journal of Software Engineering & Applications | en_US |
dc.subject | Software complexity, software metrics, UML behavioral diagrams, quality analysis, theoretical validations | en_US |
dc.title | A Suite of Metrics for UML Behavioral Diagrams Based on Complexity Perspectives | en_US |
dc.type | Article | en_US |