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Table Oriented Metrics for Relational Databases

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Abstract

Developing and selecting high quality software applications are fundamental. It is important that the software applications can be evaluated for every relevant quality characteristic using validated metrics. Software engineers have been putting forward hundreds of quality metrics for software programs, disregarding databases. However, software data aspects are important because the size of data and their system nature contribute to many aspects of a systems quality. In this paper, we proposed some internal metrics to measure relational databases which influence its complexity. Considering the main characteristics of a relational table, we can propose the number of attributes (NA) of a table, the depth of the referential tree (DRT) of a table, and the referential degree (RD) of a table. These measures are characterized using measurement theory, particularly the formal framework proposed by Zuse. As many important issues faced by the software engineering community can only be addressed by experimentation, an experiment has been carried out in order to validate these metrics.

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References

  • Basili, V.R. and Weiss, D.M. 1984. A methodology for collecting valid software engineering data, IEEE Trans. Software Eng. SE-10(6).

  • Bourque P. and Côte V. 1991. An experiment in software sizing withstructured analysis metrics, J. Systems Software 15: 159-172.

    Google Scholar 

  • Briand L., Bunse C., Daly J., and Differing C. 1997. An experimental comparison of the maintainability of object-oriented and structured design documents. In Harrold, M.J., and Vissagid G. Eds., Proc. Int. Conf. on Software Maintenance, Bari, 1–3 October, pp. 130-138.

  • Briand, L.C., Morasca, S., and Basili, V. 1996. Property-based software engineering measurement, IEEE Trans. on Software Eng. 22(1): 68-85.

    Google Scholar 

  • Brilliant, S.S. and Kinght, J.C. 1999. Empirical research in software engineering, ACM Sigsoft 24(3): 45-52

    Google Scholar 

  • Calero, C., Piattini, M., Genero, M., Serrano, M., and Caballero, I. 2000. Metrics for Relational Databases Maintainability, UKAIS2000, Cardiff, UK, pp. 109-119.

  • Card, D.N. and Glas, R.L. 1990. Measuring Software Design Quality, Englewood Cliffs, Prentice Hall.

    Google Scholar 

  • Churcher, N.J. and Shepperd, M.J. 1995. Comments on “A metrics suite for object-oriented design,” IEEE Trans. Software Eng. 21(3): 263-265.

    Google Scholar 

  • Codd, E.F. 1970. A relational model of data for larged shared data banks, CACM 13(6): 377-387.

    Google Scholar 

  • Díaz, O. and Piattini, M. 1999. Metrics for Active Databases Maintainability, CAISE'99. Heidelberg, June 16–18.

  • Elmasri, R. and Navathe, S. 1999. Fundamentals of Database Systems, 3rd ed., Massachussets, Addison-Wesley.

    Google Scholar 

  • Fenton, N. 1994. Software measurement: A necessary scientific basis, IEEE Trans. on Software Eng. 20(3): 199-206.

    Google Scholar 

  • Fenton, N. and Pfleeger, S.L. 1997. Software Metrics: A Rigorous Approach, 2nd ed., London, Chapman & Hall.

    Google Scholar 

  • Glass, R. 1996. The relationship between theory and practice in software engineering, IEEE Software, November, 39(11): 11-13.

    Google Scholar 

  • Gray, R.H.M., Carey, B.N., McGlynn, N.A., and Pengelly. A.D. 1991, Design metrics for database systems, BT Tech. J. 9(4): 69-79

    Google Scholar 

  • Henderson-Sellers, B. 1996. Object-Oriented Metrics—Measures of Complexity, Upper Saddle River, NJ, Prentice-Hall.

    Google Scholar 

  • ISO. 1994. Software product evaluation-quality characteristics and guidelines for their use. ISO/IEC Standard 9126, Geneva.

  • Kitchenham, B. and Stell, J.G. 1997. The danger of using axioms in software metrics, IEE Proc.-Softw. Eng. 144(5–6): 279-285.

    Google Scholar 

  • Li, H.F. and Chen, W.K. 1987. An empirical study of software metrics, IEEE Trans. on Software Eng. 13(6): 679-708.

    Google Scholar 

  • MacDonell, S. G., Shepperd, M. J., and Sallis, P. J. 1997. Metrics for Database Systems: An empirical study. Proc. Fourth Int. Software Metrics Symp.—Metrics'97, Albuquerque. IEEE Computer Society, pp. 99-107.

    Google Scholar 

  • Melton, A. (ed.) 1996. Software Measurement, London, International Thomson Computer Press.

    Google Scholar 

  • Neil, M. 1994. Measurement as an alternative to bureaucracy for the achievement of software quality, Software Quality J. 3(2): 65-78.

    Google Scholar 

  • Pfleeger, S.L. 1995. Experimental design and analysis in software engineering, Ann. Software Eng., JC Baltzer AG, Science Publishers, pp. 219-253.

  • Piattini, M., Calero, C., Polo, M., and Ruiz, F. 1998. Maintainability in object-relational databases, in Van Huysduynenand Peeters (eds.), Proc. of The European Software Measurement Conf. FESMA 98, Antwerp, May 6–8, Coombes, pp. 223-230.

  • Pigoski, T.M. 1997. Practical Software Maintenance, New York, Wiley Computer Publishing.

    Google Scholar 

  • Rohatgi, V.K. (1976). An Introduction to Probability Theory and Mathematical Statistics, Wiley Series in Probability and Mathematical Statistics, New York, Wiley.

    Google Scholar 

  • Schneidewind N.F. 1997. Software metrics for quality control. Proc. of the Fourth Int. Software Metrics Symp., IEEE Computer Society Technical Council on Software Engineering, pp. 127-136.

  • Sneed, H.M. and Foshag, O. 1998. Measuring legacy database structures. Proc. European Software Measurement Conf. FESMA 98, Antwerp, May 6–8, Coombes, Van Huysduynen, and Peeters (eds.), pp. 199-211.

  • Weyuker, E.J. 1988. Evaluating software complexity measures, IEEE Trans. Software Eng. 14(9): 1357-1365.

    Google Scholar 

  • Zuse, H. 1998. A Framework of Software Measurement, Berlin, Walter de Gruyter.

    Google Scholar 

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Piattini, M., Calero, C. & Genero, M. Table Oriented Metrics for Relational Databases. Software Quality Journal 9, 79–97 (2001). https://doi.org/10.1023/A:1016670717863

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