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Irish Conference on Artificial Intelligence and Cognitive Science

AICS 2002: Artificial Intelligence and Cognitive Science pp 61–69Cite as

Recovering High-Level Structure of Software Systems Using a Minimum Description Length Principle

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2464))

Abstract

In [12] a system was described for finding good hierarchical decompositions of complex systems represented as collections of nodes and links, using a genetic algorithm, with an information theoretic fitness function (representing complexity) derived from a minimum description length principle. This paper describes the application of this approach to the problem of reverse engineering the high-level structure of software systems.

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Author information

Authors and Affiliations

  1. School of Cognitive and Computing Sciences, University of Sussex, Sussex

    Rudi Lutz

Authors
  1. Rudi Lutz
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Information Systems, University of Limerick, Ireland

    Michael O’Neill , Richard F. E. Sutcliffe , Conor Ryan , Malachy Eaton  & Niall J. L. Griffith , , ,  & 

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© 2002 Springer-Verlag Berlin Heidelberg

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Lutz, R. (2002). Recovering High-Level Structure of Software Systems Using a Minimum Description Length Principle. In: O’Neill, M., Sutcliffe, R.F.E., Ryan, C., Eaton, M., Griffith, N.J.L. (eds) Artificial Intelligence and Cognitive Science. AICS 2002. Lecture Notes in Computer Science(), vol 2464. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45750-X_8

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  • DOI: https://doi.org/10.1007/3-540-45750-X_8

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44184-7

  • Online ISBN: 978-3-540-45750-3

  • eBook Packages: Springer Book Archive

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