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A Metrics-Driven Approach to the Automatic Acquisition of Software Engineering Knowledge

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Empirical Foundations of Information and Software Science V

Abstract

The goal of the Partial Metrics Project is to develop a quantitative basis within which to describe the development of software modules using the stepwise refinement of pseudocode.

Metrics-based acquisition of the knowledge structures needed by a model of module design process is outlined. Partial metrics are used to guide the acquisition process to constrain the complexity of the resultant knowledge structures. This should support the efficient reuse of these structures by the programming model. The current prototype which is under development on a TI Explorer Lisp workstation is discussed.

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References

  • Barstow, David, 1979, Kinowledge Based Program Construction, Elsevier-Holland, New York, NY.

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  • Reynolds, Robert G., and Maletic, J., 1988, Refinement Metrics: Measures of Decision-Making Effort in the Stepwise Refinement Process, Department of Computer Science Research Report, Wayne State University, September, 1988.

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  • Simon, Herbert, 1986, Whether Software Engineering Needs to be Artificially Intelligent?, IEEE Transactions on Software Engineering, Vol. SE-12, No. 12, pp. 762–732, July, 1986.

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Author information

Authors and Affiliations

  1. Dept. of Computer Science, Wayne State University, Detroit, Michigan, 48202, USA

    Robert G. Reynolds

Authors
  1. Robert G. Reynolds
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Editor information

Editors and Affiliations

  1. School of Information and Computer Science, Georgia Institute of Technology, Atlanta, Georgia, USA

    Pranas Zunde

  2. U.S. Army Institute for Research in Management Information, Communications, and Computer Science, Atlanta, Georgia, USA

    Dan Hocking

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© 1990 Plenum Press, New York

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Reynolds, R.G. (1990). A Metrics-Driven Approach to the Automatic Acquisition of Software Engineering Knowledge. In: Zunde, P., Hocking, D. (eds) Empirical Foundations of Information and Software Science V. Springer, Boston, MA. https://doi.org/10.1007/978-1-4684-5862-6_32

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  • DOI: https://doi.org/10.1007/978-1-4684-5862-6_32

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4684-5864-0

  • Online ISBN: 978-1-4684-5862-6

  • eBook Packages: Springer Book Archive

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