Rule-based handling of software quality and productivity models

  • Hans-Ludwig Hausen
Software Metrics
Part of the Lecture Notes in Computer Science book series (LNCS, volume 387)


Each software system and each software project is unique. Modeling software quality or productivity therefore has to be product or project specific. A rule-based modeling technique is proposed, which uses weight functions to define factors of quality or productivity in terms of evaluation factors and which takes environment parameters to represent validity ranges. Objectives and applications are also defined by such rules. A third category of rules, namely interrelation rules, are used to define the ‘implementation’ of objectives in terms of quality factors and applications. Each set of rules might be viewed as an acyclic decomposition graph. Quality or productivity then is to be defined as the distance of an actual graph and a required graph.


software quality software productivity rule-based system 


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  1. [Remark]
    Referred literature and selected further readings.Google Scholar
  2. [Albr83]
    A. Albrecht: Software Function, Source Lines of Code and Development Effort Prediction. In: Trans. on S.E., Vol. 9, Nr. 6, Nov., 1983Google Scholar
  3. [Boeh84]
    B. Boehm Software Engineering Ecconomics. Prentice Hall, New York: 1984Google Scholar
  4. [Haus88]
    Generic Modeling of Software Quality. in: B. Littlewood, B. Kitchenham (ed.), Measurement for Software Control and Assurance, Elsevier Applied Science Publishers Ltd. London, Nov. 1988, p. 201–241Google Scholar
  5. [Haus87]
    H.L. Hausen An Effectively Implementable Life Cycle Model. in: H. Schumny, J. Mølgaard (eds.) Proceedings EUROMICRO'87, Southsea-Portsmouth, Sept. 14.–17., 1987, North Holland, Amsterdam, 1987Google Scholar
  6. [Levy87]
    L.S. Levy Tarning the Tiger, Software Engineering and Software Economics. Springer, New York, 1987Google Scholar
  7. [McCa76]
    T. McCabe: A Complexity Measure. In: IEEE Transactions on Software Engineering, Vol. SE-2, No. 4, December 1976, pp. 308–320Google Scholar
  8. [McCa77]
    J.A. McCall; P.K. Richards; G.F. Walters: Concepts and Definitions of Software Quality. Factors in Software Quality, Vol. 1 Springfield, Va.: NTIS, Nov. 1977Google Scholar
  9. [Nasa84]
    Nasa Measures and Metrics for Software Development. Nasa-TM-85605, N84-26323, (microfiche)Google Scholar
  10. [Putn79]
    L. Putnam; A. Fritzsimmons: Estimation Software Costs. In: DATAMATION, Sept., 1979Google Scholar
  11. [Romb87]
    H.D. Rombach, V.R. Basili Quantitative Software-Qualitätssicherung. in: Informatik Spektrum, Heft 3, 1987, Bd.10: 145–158Google Scholar
  12. [Zuse85]
    H. Zuse Meßtheoretische Analyse von statischen Softwarekomplexitätsmaßen. Dissertation, TU Berlin, 1985Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1989

Authors and Affiliations

  • Hans-Ludwig Hausen
    • 1
  1. 1.GMD, Schloss BirlinghovenSt.Augustin 1FRG

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