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Metrics for Active Database Maintainability

  • Oscar Díaz
  • Mario Piattini
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1626)

Abstract

Databases are becoming more complex and it is necessary to measure schemata complexity in order understand, monitor, control, predict and improve software development and maintenance projects. Active databases are a case in point where several reports warned the difficulties to cope with large rule sets. This paper proposes three different metrics for measuring active databases complexity, based on the difficulty to ascertain the causes that make a given rule to be triggered. The measurement theory is used to characterise these metrics.

Keywords

Composite Event Active Database Primitive Event Maintenance Project Business Mathematic 
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.

References

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    J. Widom. Research issues in active database systems: Report from closing panel at ride-ads’ 94. In SIGMOD RECORD, volume 23(3), pages 41–43, 1994.CrossRefGoogle Scholar
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    H.F. Li and W.K. Chen. An empirical study of software metrics. IEEE Trans. on Software Engineering, 13(6):679–708, 1987.CrossRefGoogle Scholar
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    H. Zuse. A Framework of Software Measurement. Walter de Gruyter (Berlin), 1998.Google Scholar
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    A. Aiken, J.M. Hellerstein, and J. Widom. Static analysis techniqies for predicting the behaviour of active database rules. ACM Transactions on Databases, 20(1):3–41, 1995.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • Oscar Díaz
    • 1
  • Mario Piattini
    • 2
  1. 1.Departamento de Lenguajes y Sistemas InformáticosUniversity of the Basque CountrySan SebastiánSpain
  2. 2.Departamento de InformáticaUniversity of Castilla-La ManchaCiudad RealSpain

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