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Software & Systems Modeling

, Volume 14, Issue 1, pp 287–306 | Cite as

A fine-grained analysis of the support provided by UML class diagrams and ER diagrams during data model maintenance

  • Gabriele Bavota
  • Carmine Gravino
  • Rocco Oliveto
  • Andrea De Lucia
  • Genoveffa Tortora
  • Marcela Genero
  • José A. Cruz-Lemus
Special Section Paper

Abstract

This paper presents the results of an empirical study aiming at comparing the support provided by ER and UML class diagrams during maintenance of data models. We performed one controlled experiment and two replications that focused on comprehension activities (the first activity in the maintenance process) and another controlled experiment on modification activities related to the implementation of given change requests. The results achieved were analyzed at a fine-grained level aiming at comparing the support given by each single building block of the two notations. Such an analysis is used to identify weaknesses (i.e., building blocks not easy to comprehend) in a notation and/or can justify the need of preferring ER or UML for data modeling. The analysis revealed that the UML class diagrams generally provided a better support for both comprehension and modification activities performed on data models as compared to ER diagrams. Nevertheless, the former has some weaknesses related to three building blocks, i.e., multi-value attribute, composite attribute, and weak entity. These findings suggest that an extension of UML class diagrams should be considered to overcome these weaknesses and improve the support provided by UML class diagrams during maintenance of data models.

Keywords

Data Model Composite Attribute Comprehension Task Comprehension Level Comprehension Activity 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

We would like to thank all the students participated as subjects to the controlled experiments. We would also like to thank the anonymous reviewers for their detailed, constructive, and thoughtful comments that helped us to improve the presentation of the results in this paper. This research has been partially funded by the following projects: ORIGIN (CDTI-MICINN and FEDER,IDI-2010043(1-5)) and GEODAS-BC (Ministerio de Econom’a y Competitividad and FEDER, TIN2012-37493-C03-01).

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Gabriele Bavota
    • 1
  • Carmine Gravino
    • 1
  • Rocco Oliveto
    • 2
  • Andrea De Lucia
    • 1
  • Genoveffa Tortora
    • 1
  • Marcela Genero
    • 3
  • José A. Cruz-Lemus
    • 3
  1. 1.University of SalernoFiscianoItaly
  2. 2.University of MolisePescheItaly
  3. 3.University of CastillaLa ManchaSpain

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