Concepts-Based Traceability: Using Experiments to Evaluate Traceability Techniques

  • Rodrigo Perozzo Noll
  • Marcelo Blois Ribeiro
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 24)


Knowledge engineering brings direct benefits to software development through the cognitive mapping between user expectations and software solution, checking system consistency and requirements conformance. One of the potential benefits of knowledge representation could be the definition of a standard domain terminology to enforce artifacts traceability. This paper proposes a concepts-based approach to drive traceability by the integration of knowledge engineering activities into the Unified Process. This paper also presents an experiment and its replication to evaluate precision and effort variables from concepts-based traceability and conventional requirements-based traceability techniques.


Traceability Knowledge Engineering Experimental Software Engineering 


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  1. 1.
    Basili, V.R., Lanubile, F.: Building knowledge through families of experiments. IEEE Transactions on Software Engineering 25(4) (1999)Google Scholar
  2. 2.
    Guarino, N.: Formal Ontology in Information Systems. In: Proceedings of FOIS 1998, pp. 3–15. IOS Press, Amsterdam (1998)Google Scholar
  3. 3.
    Gruninger, M., Fox, M.S.: Methodology for the Design and Evaluation of Ontologies. In: Workshop on Basic Ontological Issues in Knowledge Sharing, pp. 234–241 (1995)Google Scholar
  4. 4.
    Fernández, M., Gómez-Pérez, A., Juristo, N.: Methontology: From Ontological Art towards Ontological Engineering. In: Proc. AAAI 1997, pp. 33–40 (1997)Google Scholar
  5. 5.
    Noy, N.F., McGuinness, D.L.: Ontology Development: A Guide to Creating Your First Ontology. Technical Report KSL-01-05, Stanford Knowledge Systems Laboratory and Stanford Medical Informatics (2001)Google Scholar
  6. 6.
    Sure, Y., Studer, R.: On-To-Knowledge Methodology - Final Version. On-To-Knowledge EU IST-1999-10132 Project Deliv. D18, University of Karlsruhe (2002)Google Scholar
  7. 7.
    ArgoUML - A UML design tool,
  8. 8.
    The Protègè Ontology Editor,
  9. 9.
    Falbo, R.A., Ruy, M.R.D.: Using Ontologies to Add Semantics to a Software Engineering Environment. In: Proc. of 17th International Conference on Software Engineering and Knowledge Engineering, pp. 151–156 (2005)Google Scholar
  10. 10.
    Wohlin, et al.: Experimentation in software engineering: an introduction. Kluwer Academic Publishers, USA (2000)Google Scholar
  11. 11.
    Basili, V.R., Caldiera, G., Rombach, H.D.: The Goal Question Metric Approach; Encyclopedia of Software Engineering. Wiley-Interscience, New York (1994)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Rodrigo Perozzo Noll
    • 1
  • Marcelo Blois Ribeiro
    • 1
  1. 1.Pontifical Catholic University of Rio Grande do Sul - PUCRSPorto AlegreBrazil

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