An approach to modelling long-term growth trends in software systems

Abstract

Three related models of growth, consistent with the view that complexity constrains system growth, were fitted to empirical data relating to four software systems. Predictive accuracy of the models, measured in mean magnitude of relative error, ranges from approximately 2 to 17 percent of the quantitative data. The modelling approach emphasises simple models that, nevertheless, provide a basis for evolution planning and management tools. These and previous results suggest that it is meaningful to search for models of this kind, though the presence of discontinuities in the trends and the extent to which the latter are restricted to individual processes or specific domains need to be further investigated. The work presented has been pursued as part of the FEAST/2 (Feedback, Evolution And Software Technology) project.