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Integrating specifications: A similarity reasoning approach

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Abstract

Requirements analysis usually results in a set of different specifications for the same system, which must be integrated. Integration involves the detection and elimination of discrepancies between them. Discrepancies may be due to differences in representation models, modeling perspectives or practices. As instances of the semantic heterogeneity problem (Gangopadhyay and Barsalou, 1991), discrepancies are broader than logical inconsistencies, and therefore not always detectable using theorem proving. This paper proposes an approach to their detection using meta-modeling and similarity analysis. Specification components are classified under a meta-model of domain independent semantic modeling abstractions and thereby compared according to a newly developed model of similarity. Similarity analysis results in an isomorphic mapping between them, which can be used as a basis for reconciling and merging them. The approach is extensible in the sense that it accommodates different models for representing specifications, and analysis scales up to manage large, complex specification because the complexity of similarity analysis is polynomial.

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References

  • Al-Fedaghi, S. and Scheuermann, P. 1981. Mapping considerations in the design of schemas for the relational model.IEEE Transactions on Software Engineering, 7(1).

  • Arens, Y. and Knoblock, C. 1992. Planning and reformulating queries for semantically-modeled multidatabase systems. InProceedings of the 1st International Conference on Information and Knowledge Management.

  • Batini, C., Lenzerini, M., and Navathe, S. 1986. A comparative analysis of methodologies for database schema integration.ACM Computing Surveys, 18(4).

  • Bright, M., Hurson, A., and Pakzad, S. 1994. Automated resolution of semantic heterogeneity in multidatabases.ACM Transactions on Database Systems, 19(2).

  • Casanova, M. and Vidal, M. 1983. Towards a sound view integration methodology. InProceedings of the 2nd ACM SIGART/SIGMOD Conference on Principles of Database Systems, ACM, New York.

    Google Scholar 

  • Codd, F. 1979. Extending the database relational model to capture more meaning.ACM Transactions on Database Systems, 4(4).

  • Collet, C. et al. 1991. Resource integration using a large knowledge base in carnot.IEEE Computer, 24(12).

  • Constantopoulos, P. et al. 1993. Repositories for software reuse: The software information base. InProceedings of the IFIP Conference on the Software Development Process, Como, Italy.

  • Constantopoulos, P. and Doerr, M. 1993. The semantic index system: A brief presentation. Institute of Computer Science, Foundation for Research and Technology-Hellas, Heraklion, Crete, Greece.

    Google Scholar 

  • Easterbrook, S. and Nuseibeh, B. 1995. Managing inconsistencies in an evolving specification. InProceedings of the IEEE International Conference on Requirements Engineering, York, England.

  • Falkenhainer, B. et al. 1990. The structure mapping engine: Algorithm and examples.Artificial Intelligence, 41.

  • Finkelstein, A. et al. 1994. Inconsistency handling in multi-perspective specifications.IEEE Transactions on Software Engineering, 20(8).

  • Furnas, G. et al. 1987. The vocabulary problem in human-system communication.Communications of the ACM, 30(11).

  • Gangopadhyay, D. and Barsalou, T. 1991. On the semantic equivalence of heterogeneous populations in multi-model.Multidatabase Systems, SIGMOD Record 20(4).

  • Goh, C., Madnick, S., and Siegel, M. 1994. Context interchange: Overcoming the challenges of large-scale interoperable database systems in a dynamic environment. InProceedings of the 3rd International Conference on Information and Knowledge Management, Gaithersurg, Maryland.

  • Gruber, T. and Olsen, G. 1994. An ontology for engineering mathematics. InProceedings of the 4th International Conference on Principles of Knowledge Representation and Reasoning, Bonn, Germany.

  • Heitmeyer, C. et al. 1995. Consistency checking of SCR-style requirements specifications. InProceedings of the IEEE International Conference on Requirements Engineering, York, England.

  • Hull, R. and King, R. 1987. Semantic database modeling: Survey, applications and research issues.ACM Computing Surveys, 19(3).

  • Johanneson, P. 1993. Schema transformations as an aid in view integration. InProceedings of CAiSE'93, LNCS 685.

  • Kotonya, G. and Sommerville, I. 1992. Viewpoints for requirements definition.Software Engineering Journal, 7(6).

  • Larson, J., Navathe, S., and Elmasri, R. 1989. A theory of attribute equivalence in databases with application to schema integration.IEEE Transactions on Software Engineering, 15(4).

  • Leite, J. and Freeman, P. 1991. Requirements validation through viewpoint resolution.IEEE Transactions on Software Engineering, 17(12).

  • Lenat, D. and Guha, R. 1990.Building Large Knowledge-Based Systems: Representation and Inference in the Cyc Project. Reading, Mass: Addison-Wesley.

    Google Scholar 

  • Litwin, W. and Abdellatif, A. 1987. An overview of the multi-database manipulation language MDSL. InProceedings of the IEEE, 75(4).

  • Maiden, N. and Sutcliffe, A. 1994. Requirements critiquing using domain abstractions. InProceedings of the IEEE Conference on Requirements Engineering, 1994.

  • Maiden, N. et al. 1994. Distributed requirements engineering within NATURE, ESPRIT BRA NATURE, Nature Report Series.

  • Maiden, N. et al. 1995. Computational mechanisms for distributed requirements engineering. InProceedings of the 7th International Conference on Software Engineering & Knowledge Engineering (SEKE'95), USA.

  • Mannino, M. and Effelsberg, W. 1984. Matching techniques in global schema design. InProceedings of the IEEE COMPDEC Conference, Los Angeles, California.

  • Meyers, S. and Reiss, S. 1991. A system for multiparadigm development of software systems. InProceedings of the 6th International Workshop on Software Specification and Design (IWSSD-6), Como, Italy.

  • Monarchi, D. and Puhr, G. 1992. A research typology for object oriented analysis and design.Communications of the ACM, 35(9).

  • Motro, A. and Buneman, P. 1981. Constructing superviews. InProceedings of the International Conference on Management of Data, ACM, New York.

    Google Scholar 

  • Motschnig-Pitrik, P. 1993. The semantics of parts vs. aggregates in data knowledge modeling. InProceedings of CAiSE'93, LNCS 685, Paris, France.

  • Mylopoulos, J. et al. 1990. Telos: Representing knowledge about information systems.ACM Transactions on Information Systems, 8(4).

  • Navathe, S. and Gadgil, S. 1982. A methodology for view integration in logical data base design. InProceedings of the 8th International Conferences on Very Large Data Bases, VLDB Endowment, Saratoga, California.

    Google Scholar 

  • Nuseibeh, B. et al. 1993. Expressing the relationship between multiple views in requirements specification. InProceedings of 15th International Conference on Software Engineering.

  • Papadimitriou, C. and Steiglitz, K. 1982.Combinatorial Optimization: Algorithms and Complexity, Englewood Cliffs, New Jersey: Prentice-Hall, Inc.

    Google Scholar 

  • Peckham, J. and Maryanski, F. 1988. Semantic data models.ACM Computing Surveys, 20(3).

  • Robinson, W. and Fickas, S. 1994. Supporting multi-perspective requirements engineering. InProceedings of the IEEE Conference on Requirements Engineering.

  • Sciore, E., Siegel, M., and Rosenthal, A. 1994. Using semantic values to facilitate the interoperability among heterogeneous information systems.ACM Transactions on Database Systems, 19(2).

  • Sheth, A. and Larson, J. 1990. Federated database systems for managing distributed, heterogeneous and autonomous databases.ACM Computing Surveys, 22(3).

  • Smith, E. 1989.Concepts and Induction, Foundations of Cognitive Science, A Bradford Book, The MIT Press.

  • Spanoudakis, G. and Constantopoulos, P. 1994a. Similarity for analogical software reuse: A computational model. InProceedings of the 11th European Conference on Artificial Intelligence (ECAI'94), Amsterdam, The Netherlands.

  • Spanoudakis, G. and Constantopoulos, P. 1994b. On evidential feature salience. InProceedings of the 5th International Conference on Database & Expert Systems Applications (DEXA'94), Athens, Greece.

  • Spanoudakis, G. 1994a. Analogical similarity of objects: A conceptual modeling approach, Ph.D. Dissertation, Department of Computer Science, University of Crete, Heraklion, (available from http://web.cs.city.ac.uk/homes/gespan/info.html).

    Google Scholar 

  • Spanoudakis, G. 1994b. Similarity analyser: An implementation overview. Working Paper 12, Institute of Computer Science, Foundation for Research and Technology-Hellas, Heraklion, Crete, Greece, (available from http://web.cs.city.ac.uk/homes/gespan/info.html).

    Google Scholar 

  • Storey, V. 1993. Understanding semantic relations.VLDB Journal 3.

  • Turner, M. 1988.Categories and Analogies, Analogical Reasoning: Perspectives of Artificial Intelligence, Cognitive Science and Philosophy. D.H. Helman (Ed.), Dordrecht, The Netherlands: Kluwer Academic Pub.

    Google Scholar 

  • Yao, S., Waddle, V., and Bousel, B. 1982. View modeling and integration using the functional data model.IEEE Transactions on Software Engineering, 8(6).

  • Zave, P. and Jackson, M. 1993. Conjunction as composition.ACM Transactions on Software Engineering and Methodology, 2(4).

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Spanoudakis, G., Constantopoulos, P. Integrating specifications: A similarity reasoning approach. Autom Software Eng 2, 311–342 (1995). https://doi.org/10.1007/BF00871803

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