| dc.contributor.author | King’ori, Ann Wambui | |
| dc.contributor.author | Muketha, Geoffrey Muchiri.; | |
| dc.contributor.author | Ndia, John Gichuki | |
| dc.date.accessioned | 2025-01-16T14:25:37Z | |
| dc.date.available | 2025-01-16T14:25:37Z | |
| dc.date.issued | 2024 | |
| dc.identifier.issn | 2180-1320, | |
| dc.identifier.uri | https://www.cscjournals.org/journals/IJSE/description.php | |
| dc.identifier.uri | http://repository.mut.ac.ke:8080/xmlui/handle/123456789/6503 | |
| dc.description.abstract | As software systems become more complex, software modeling is crucial. Software engineers
are adopting UML behavioral diagrams to model the dynamic features of a system. These
dynamic diagrams keep changing for further improvement, hence becoming more complex. In
this case, there is a need to define the measurement attributes used to measure the complexity of
these diagrams. Several researchers have addressed the quality of these diagrams by
developing measurement frameworks. However, the existing frameworks in the literature are
limited since they do not capture the perspective complexity of these diagrams. In this paper, we
establish the taxonomy complexity of UML behavioral diagrams, we then modify Kaner’s and
Briand’s framework to propose measurement attributes namely, element, control flow, and
interaction based on the taxonomy complexity of behavioral diagrams. Finally, we test the
applicability of the proposed framework using behavioral diagram metrics. Results indicate that
the proposed framework represents parameters vital to evaluate and validate the complexity
measures of behavioral diagrams. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | International Journal of Software Engineering (IJSE) | en_US |
| dc.subject | Software Quality, UML Behavioral Diagrams, Measurement Framework, Metrics, Theoretical Validation. | en_US |
| dc.title | A Framework for Analyzing UML Behavioral Metrics based on Complexity Perspectives | en_US |
| dc.type | Article | en_US |
