An automated procedure for identifying poorly documented object oriented software components

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, I present a procedure for automating the identification of object oriented software components that may be poorly documented. The proposed procedure uses artificial neural network to learn and estimate the software size and the source code documentation size. The differences in the estimates for software size and actual size, and the estimates for source code documentation size and actual documentation size are used to identify software components that may be poorly documented.

Original languageEnglish (US)
Title of host publicationProceedings of the 2009 C3S2E Conference, C3S2E '09
Pages217-222
Number of pages6
DOIs
StatePublished - Nov 9 2009
Event2009 Canadian Conference on Computer Science and Software Engineering, C3S2E '09 - Montreal, QC, Canada
Duration: May 19 2009May 21 2009

Publication series

NameACM International Conference Proceeding Series

Other

Other2009 Canadian Conference on Computer Science and Software Engineering, C3S2E '09
CountryCanada
CityMontreal, QC
Period5/19/095/21/09

All Science Journal Classification (ASJC) codes

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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