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International Conference on Computational Science and Its Applications

ICCSA 2013: Computational Science and Its Applications – ICCSA 2013 pp 43–58Cite as

Increasing the Rigorousness of Measures Definition through a UML/OCL Model Based on the Briand et al.’s Framework

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7973))

Abstract

The use of a formal definition of measures upon a metamodel assures that measures capture the software artifacts they intend for, improve repeatability and could facilitate the implementation of measures extraction tools. However, it does not assure that the measure captures the measurement concept it claims (like size, coupling, etc). For that purpose many formal frameworks had been defined. The well-known property-based framework proposed by Briand et al. defines the most important measurement concepts regardless the specific software artifacts to which these concepts are applied. In this article we define a UML/OCL model from the Briand’s framework and we relate it with the formal definition of measures upon metamodels. We describe a set of well-formed properties that a measure should verify when capturing a measurement concept (which are derived from the model). We exemplify our approach through a thorough formal definition of UML statechart diagrams measures and its well-formed constraints of size measures.

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Authors and Affiliations

  1. University of Comahue, Buenos Aires, 1400, Neuquén, Argentina

    Luis Reynoso, Marcelo Amaolo, Daniel Dolz & Claudio Vaucheret

  2. Patagonia San Juan Bosco University, Argentina, Belgrano y Rawson, 9100, Trelew, Chubut

    Mabel Álvarez

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  1. Luis Reynoso
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  2. Marcelo Amaolo
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  3. Daniel Dolz
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  4. Claudio Vaucheret
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  5. Mabel Álvarez
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Editor information

Editors and Affiliations

  1. L-I.S.U.T. - D.A.P.I.t. Facoltà Ingegneria, Università degli Studi della Basilicata, Viale dell’Ateneo Lucano, 10, 85100, Potenza, Italy

    Beniamino Murgante

  2. Covenant University, Canaanland, Ota, Nigeria

    Sanjay Misra

  3. Partimento di Scienze e Tecnologie per LAgricoltura, le Foreste, la Natura e lEnergia, Università degli Studi della Tuscia, Via S. Camillo de Lellis, snc, 01100, Viterbo, Italy

    Maurizio Carlini

  4. Dipartimento di Scienze dell’Ingegneria Civile e dell’Architecttura, Politecnico di Bari, Via Orabona, 4, 70125, Bari, Italy

    Carmelo M. Torre

  5. International University VNU-HCM, Quarter 6, Linh Trung, Thu Duc, Ho Chi Minh City, Vietnam

    Hong-Quang Nguyen

  6. School of Business Systems, Monash University, 3800, Clayton, VIC, Australia

    David Taniar

  7. Department of Intelligent Informatics, Kyushu Sangyo University, 2-3-1 Matsukadai, Higashi-ku, 813-8503, Fukuoka, Japan

    Bernady O. Apduhan

  8. Department of Mathematics and Computer Science, University of Perugia, Via Vanvitelli, 1, 06123, Perugia, Italy

    Osvaldo Gervasi

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Reynoso, L., Amaolo, M., Dolz, D., Vaucheret, C., Álvarez, M. (2013). Increasing the Rigorousness of Measures Definition through a UML/OCL Model Based on the Briand et al.’s Framework. In: Murgante, B., et al. Computational Science and Its Applications – ICCSA 2013. ICCSA 2013. Lecture Notes in Computer Science, vol 7973. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39646-5_4

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  • DOI: https://doi.org/10.1007/978-3-642-39646-5_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-39645-8

  • Online ISBN: 978-3-642-39646-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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