Size and Complexity Attributes for Multimodel Improvement Framework Taxonomy

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.