Resumo

UCAN-PECH, Juan-Pablo; AGUILAR-VERA, Raúl-Antonio; DIAZ-MENDOZA, Julio-César  e  GOMEZ-GOMEZ, Omar-Salvador. Learning Failures in Class Modeling and Use Cases: A Systematic Review. Rev. Cient. [online]. 2023, n.46, pp.93-106.  Epub 26-Abr-2023. ISSN 0124-2253.  https://doi.org/10.14483/23448350.19655.

This paper presents a review of the main studies that address the identification of faults during the learning of use case diagrams (DCU) and class diagrams (DC) in the last 10 years. This work is the beginning of a research project related to the detection of faults in UML diagrams. This paper presents an analysis of the state of the art regarding the typification of faults in DCU and DC, with the objective of identifying opportunities and research gaps. 20 documents were found according to the inclusion and exclusion criteria established through the methodology employed for the systematic review of the literature. Considering the relevance of the topic, it can be observed that there is limited research on fault detection in UML diagrams for both DCU and DC.

Palavras-chave : class diagrams; faults in software modeling; SLR; UML; use case diagrams..

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