Neural Processing Letters

, Volume 5, Issue 3, pp 219–226 | Cite as

Promoting Software Reuse Using Self Organizing Maps

  • Sushil Acharya
  • R. Sadananda


Reusability of software, regardless of its utilizing technique, is widely believed to be a promising means for improving software productivity and reliability. However it is not practiced adequately due to the lack of techniques that facilitate the locating of reusable components that are functionally close. In this paper we apply Kohonen's Self-Organizing Maps to develop an approach for promoting Software Reuse. We look at the details of how Self-Organization can arrange and regularize data from the original pattern space into a topology preserving map. We describe a practical implementation of the SOM methodology for Software Reuse using a database of UNIX commands. And finally we briefly present our proposed Software Reuse Methodology.

data clustering self-organizing maps software reuse unix 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    S. Pandey, “Self-Organizing Map to promote Software Reuse”, Thesis Report, Asian Institute of Technology, Bangkok, 1994.Google Scholar
  2. 2.
    B. Maarek and Kaiser, “An information retrieval approach for automatically constructing software library”, IEEE Transaction on Software Engineering, Vol. 17, No. 8, 1991.Google Scholar
  3. 3.
    Burton et. al., “The reusable software library”, IEEE Software, pp. 25–33, July 1987.Google Scholar
  4. 4.
    B. Devanbu and B. Selfridge, “LASSIE: A knowledge based software information system”, CACM, Vol. 4, No. 5, pp. 34–49, May 1991.Google Scholar
  5. 5.
    T. Kohonen, “The Self Organizing Map”, IEEE Proceedings, Vol. 78, No. 9, pp. 1464–1480, 1990.Google Scholar
  6. 6.
    T. Kohonen and H. Ritter, “Self-Organizing Semantic Maps”, Biological Cybernetics, 1989.Google Scholar
  7. 7.
    T. Kohonen, “Self-Organization and Associative Memory”, Spinger Verlag, Heidelberg, Germany, 1989.Google Scholar
  8. 8.
    J.M. Zurada, “Introduction to Artificial Neural Systems”, Info Access Distribution Limited, Singapore, 1992.Google Scholar
  9. 9.
    S. Acharya and R. Sadananda, “A knowledge discovery methodology using Self Organizing Maps”, Proc. of the International Conference on Information Systems Analysis and Synthesis (ISAS'96)”, Orlando, USA, 1996.Google Scholar
  10. 10.
    R. Sadananda, A. Shrestha and N. Khosla, “The choice of neighborhood in Self-Organization Scheme for VLSI”, IEEE Conference in Expert Systems, AIT, 1994.Google Scholar

Copyright information

© Kluwer Academic Publishers 1997

Authors and Affiliations

  • Sushil Acharya
    • 1
  • R. Sadananda
    • 1
  1. 1.Computer Science and Information Management ProgramSchool of Advanced Technologies, Asian Institute of TechnologyPathumthaniThailand

Personalised recommendations