Heuristic rules for transforming preconceptual schemas into uml 2.0 diagrams: a C# implementation
DOI:
https://doi.org/10.17533/udea.redin.18509Keywords:
Pre-conceptual schemas, class diagram, communication diagram, state machine diagram, UML 2.0, transformation rules, C# programming languageAbstract
From the mid-nineties, a new path for automatically generating UML conceptual schemas from controlled languages, by means of heuristic rules, has been proposed. This path still exhibit problems to be solved: ambiguity of heuristic rules, semi-automated expert-participation processes, difficulties in representing structural and dynamic features of the domain, focus on only one diagram, and lack of implementation. In this paper, we employ the socalled Pre-conceptual Schemas as a graphical language for representing the domain of a software application; also, we implement in the C# language the conversion rules from Pre-conceptual Schemas into UML 2.0 diagrams. C# implementation avoids ambiguity of some of the conversion rules; furthermore, C# implementation permits process automation without the need of experts. Finally, we show the functionality of C# rule-based prototype by means of a case study.
Downloads
References
OMG. “OMG Unified Modeling Language Specification”. Object Management Group. http:// www.omg.org/UML/. Consultada el 10 de Junio de 2007.
P. Chen. “English Sentence Structure and EntityRelationship Diagram”. Information Sciences. Vol. 1. 1983. pp. 127–149. DOI: https://doi.org/10.1016/0020-0255(83)90014-2
A. Gangopadhyay. “Conceptual modeling from natural language functional specifications”. Artificial Intelligence in Engineering. Vol. 15. 2001. pp. 207– 218. DOI: https://doi.org/10.1016/S0954-1810(01)00017-6
B. R. Bryant. “Object-Oriented Natural Language Requirements Specification”. 23rd Austalasian Computer Science Conference. Canberra. 2000. pp. 24–30.
S. Konrad, B. H. C. Cheng. “Automated Analysis of Natural Language Properties for UML Models”. Satellite Events at MoDELS 2005 Conference, Lecture Notes in Computer Science. N.° 3844. 2006. pp. 48–57. DOI: https://doi.org/10.1007/11663430_6
N. Juristo, J. Morant, A. Moreno. “A formal approach for generating OO specifications from natural language”. The Journal of Systems and Software. Vol. 48. 1999. pp. 139–153. DOI: https://doi.org/10.1016/S0164-1212(99)00052-7
G. Fliedl, Ch. Kop, H. Mayr, W. Mayerthaler, Ch. Winkler, “Linguistically Based Requirements Engineering: The Niba-Project”, Data Knowledge Engineering, Vol. 35. 1999. pp. 111–120. DOI: https://doi.org/10.1016/S0169-023X(00)00029-X
C. M. Zapata, A. Gelbukh, F. Arango. “Pre-conceptual Schema: A Conceptual-Graph-Like Knowledge Representation for Requirements Elicitation”. Lecture Notes in Computer Science. Vol. 4293. 2006. pp. 17–27. DOI: https://doi.org/10.1007/11925231_3
A. vanWijngaarden. “Orthogonal design and description of a formal language”. Technical report. Mathematisch Centrum. Amsterdam. 1965. pp. 1–25.
C. M. Zapata, A. Gelbukh, F. Arango. “UN-Lencep: Obtención Automática de Diagramas UML a partir de un Lenguaje Controlado”. A. Hernández, J. L. Zechinelli (Eds.) Avances en la Ciencia de la Computación. Guanajuato, Mexican Society of Computer Science, 2006. pp. 254–259.
C. M. Zapata, F. Arango, A. Gelbukh. “Pre-conceptual Schema: a UML isomorphism for automatic obtaining of UML conceptual schemas”. Research in Computing Science: Advances in Computer Science and Engineering. Vol. 19. 2006. pp. 3–13. 12. M. Fowler. UML Distilled. 3th ed. Boston. Pearson Education. 2004. pp. 1–112.
Downloads
Published
How to Cite
Issue
Section
License
Revista Facultad de Ingeniería, Universidad de Antioquia is licensed under the Creative Commons Attribution BY-NC-SA 4.0 license. https://creativecommons.org/licenses/by-nc-sa/4.0/deed.en
You are free to:
Share — copy and redistribute the material in any medium or format
Adapt — remix, transform, and build upon the material
Under the following terms:
Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
NonCommercial — You may not use the material for commercial purposes.
ShareAlike — If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.
The material published in the journal can be distributed, copied and exhibited by third parties if the respective credits are given to the journal. No commercial benefit can be obtained and derivative works must be under the same license terms as the original work.
Twitter