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
Link To Document :
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