• DocumentCode
    2519221
  • Title

    Size and Complexity Attributes for Multimodel Improvement Framework Taxonomy

  • Author

    Ferreira, Andre L. ; Machado, Ricardo J. ; Paulk, Mark C.

  • Author_Institution
    Dept. de Sist. de Informacao, Univ. do Minho, Guimarães, Portugal
  • fYear
    2010
  • fDate
    1-3 Sept. 2010
  • Firstpage
    306
  • Lastpage
    309
  • Abstract
    Selection of best practice models is a daunting task. The number of models is considerable and the ability to compare objectively their content is not straightforward due to scope and structural variety in descriptions. The purpose of this paper is to provide a base for quantitative analysis of best practice models at the light of proposed attributes of size and complexity. We propose a characterization of size as a measure of scope coverage and detail of descriptions between models and complexity in terms of structural connectedness. We analyzed a set o best practice models popular in the Software Engineering domain and derived relative size and complexity measures of these models.
  • Keywords
    software metrics; software process improvement; complexity attributes; multimodel improvement framework taxonomy; size attributes; software engineering domain; Analytical models; Best practices; Complexity theory; Size measurement; Software; Standards organizations; Taxonomy; Multimodel improvement taxonomies; Software Engineering Management; Software Process Improvement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Engineering and Advanced Applications (SEAA), 2010 36th EUROMICRO Conference on
  • Conference_Location
    Lille
  • ISSN
    1089-6503
  • Print_ISBN
    978-1-4244-7901-6
  • Type

    conf

  • DOI
    10.1109/SEAA.2010.54
  • Filename
    5598112