Model-Driven Tool Interoperability: An Application in Bug Tracking

  • Marcos Didonet Del Fabro
  • Jean Bézivin
  • Patrick Valduriez
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4275)


Interoperability of heterogeneous data sources has been extensively studied in data integration applications. However, the increasing number of tools that produce data with very different formats, such as bug tracking, version control, etc., produces many different kinds of semantic heterogeneities. These semantic heterogeneities can be expressed as mappings between the tools metadata which describe the data manipulated by the tools. However, the semantics of complex mappings (n:1, 1:m and n:m relationships) is hard to support. These mappings are usually directly coded in executable transformations using arithmetic expressions. And there is no mechanism to create and reuse complex mappings. In this paper we propose a novel approach to capture different kinds of complex mappings using correspondence models. The main advantage is to use high level specifications for the correspondence models that enable representing different kinds of mappings. The correspondence models may be used to automatically produce executable transformations. To validate our approach, we provide an experimentation with a real world scenario using bug tracking tools.


complex mappings semantic heterogeneities tool interoperability MDE (Model Driven Engineering) 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Abiteboul, S., Cluet, S., Milo, T.: Correspondence and Translation for Heterogeneous Data. In: Afrati, F.N., Kolaitis, P.G. (eds.) ICDT 1997. LNCS, vol. 1186, pp. 351–363. Springer, Heidelberg (1996)Google Scholar
  2. 2.
    AMW: The ATLAS Model Weaver (June 2006), Ref. site:
  3. 3.
    ATL: ATLAS Transformation Language (June 2006), Ref. site:
  4. 4.
    Atzeni, P., Cappellari, P., Bernstein, P.A.: Model-independent schema and data translation. In: Ioannidis, Y., Scholl, M.H., Schmidt, J.W., Matthes, F., Hatzopoulos, M., Böhm, K., Kemper, A., Grust, T., Böhm, C. (eds.) EDBT 2006. LNCS, vol. 3896, pp. 368–385. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  5. 5.
    Bernstein, P.A.: Applying Model Management to Classical Meta Data Problems. In: Proc. of the 1st CIDR, pp. 209–220 (2003)Google Scholar
  6. 6.
    Bugzilla Bug Tracking Tool (June 2006), Reference site:
  7. 7.
    Cohen, W., Ravikumar, P., Fienberg, S.E.: A Comparison of String Distance Metrics for Name-Matching Tasks. In: Proc. of IIWeb 2003, pp. 73–78 (2003)Google Scholar
  8. 8.
    Dhamanka, R., Lee, Y., Doan, A., Halevy, A., Domingos, P.: iMAP: Discovering Complex Semantic Matches between Database Schemas. In: Proc. of SIGMOD 2004 (2004)Google Scholar
  9. 9.
    Didonet Del Fabro, M., Bézivin, J., Jouault, F., Valduriez, P.: Applying Generic Model Management to Data Mapping. In: proc. of BDA 2005, Saint-Malo, France, pp. 343–355 (2005)Google Scholar
  10. 10.
    Doan, A., Halevy, A.: Semantic Integration Research in the Database Community: A Brief Survey. AI Magazine, Special Issue on Semantic Integration, Spring, 83–94 (2005)Google Scholar
  11. 11.
    Ehrig, M., Haase, P., Hefke, M., Stojanovic, N.: Similarity for Ontologies - A Comprehensive Framework. In: Proc. of ECIS 2005 (2005)Google Scholar
  12. 12.
    EMF. Eclipse Modelling Framework (June 2006), Reference site:
  13. 13.
    Euzenat, J.: An API for Ontology Alignment. In: McIlraith, S.A., Plexousakis, D., van Harmelen, F. (eds.) ISWC 2004. LNCS, vol. 3298, pp. 698–712. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  14. 14.
    Euzenat, J., Valtchev, P.: Similarity-based ontology alignment in OWL-Lite. In: Proc. of ECAI 2004, Valencia, Spain, August 2004, pp. 333–337 (2004)Google Scholar
  15. 15.
    Flanakin, M.: Web Log. Comments and complaints on software and technology in general. Comparison: Web-based Tracker (08/08/2005),
  16. 16.
    Jouault, F., Kurtev, I.: Transforming Models with ATL. In: Bruel, J.-M. (ed.) MoDELS 2005. LNCS, vol. 3844, pp. 128–138. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  17. 17.
    Jouault, F., Bézivin, J.: KM3: A DSL for Metamodel Specification. In: Gorrieri, R., Wehrheim, H. (eds.) FMOODS 2006. LNCS, vol. 4037, pp. 171–185. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  18. 18.
    Kashyap, V., Sheth, A.P.: Semantic and Schematic Similarities Between Database Objects: A Context-Based Approach. VLDB J. 5(4), 276–304 (1996)CrossRefGoogle Scholar
  19. 19.
    Kedad, Z., Xue, X.: Mapping discovery for XML data integration. In: Proc. of CoopIS 2005, Agia Napa, Cyprus, November 2005, pp. 166–182 (2005)Google Scholar
  20. 20.
    Kensche, D., Quix, C., Chatti, M.A., Jarke, M.: GeRoMe: A Generic Role Based Metamodel for Model Management. In: OTM Conferences, (2), pp. 1206–1224 (2005)Google Scholar
  21. 21.
    Lenzerini, M.: Data Integration: A Theoretical Perspective. In: PODS 2002, pp. 233–246 (2002)Google Scholar
  22. 22.
    Maedche, A., Motik, B., Silva, N., Volz, R.: MAFRA – A mApping fRAmework for distributed ontologies. In: Gómez-Pérez, A., Benjamins, V.R. (eds.) EKAW 2002. LNCS, vol. 2473, pp. 235–250. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  23. 23.
    Mantis Bug Tracking System (June 2006), Reference site: Google Scholar
  24. 24.
    Melnik, S.: Generic Model Management: Concepts and Algorithms. In: Melnik, S. (ed.) Generic Model Management. LNCS, vol. 2967. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  25. 25.
    Melnik, S., Bernstein, P.A., Halevy, A., Rahm, E.: Supporting Executable Mappings in Model Management. In: Proc. of SIGMOD 2005, Maryland, US, pp. 167–178 (2005)Google Scholar
  26. 26.
    Miller, R.J., Hernandez, M.A., Haas, L.M., Yan, L.-L., Ho, C.T.H., Fagin, R., Popa, L.: The Clio Project: Managing Heterogeneity. SIGMOD Record 30(1), 78–83 (2001)CrossRefGoogle Scholar
  27. 27.
    Milo, T., Zohar, S.: Using Schema Matching to Simplify Heterogeneous Data Translation. In: Proc. of VLDB, pp. 122–133 (1998)Google Scholar
  28. 28.
    Mitra, P., Wiederhold, G., Kersten, M.L.: A graph-oriented model for articulation of ontology interdependencies. In: Zaniolo, C., Grust, T., Scholl, M.H., Lockemann, P.C. (eds.) EDBT 2000. LNCS, vol. 1777, p. 86. Springer, Heidelberg (2000)CrossRefGoogle Scholar
  29. 29.
    OMG (Object Management Group). Human Usable Textual Notation (HUTN) Specification, Final Adopted Specification (ptc-02-12-01)Google Scholar
  30. 30.
    Pottinger, R.A., Bernstein, P.A.: Merging Models Based on Given Correspondences. In: Proc. of VLDB 2003, pp. 862–873 (2003)Google Scholar
  31. 31.
    Sheth, A.P., Thacker, S., Patel, S.: Complex relationships and knowledge discovery support in the InfoQuilt system. VLDB Journal 12(1), 2–27 (2003)CrossRefGoogle Scholar
  32. 32.
    Shvaiko, P., Euzenat, J.: A Survey of Schema-Based Matching Approaches. Journal of Data Semantics IV, 146–171 (2005)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Marcos Didonet Del Fabro
    • 1
  • Jean Bézivin
    • 1
  • Patrick Valduriez
    • 1
  1. 1.ATLAS GroupINRIA and LINA University of NantesNantes cedex 3France

Personalised recommendations