Functional Complexity Measurement

The specific analysis of FPA, from a complexity viewpoint, leads us to propose an initial model of functional complexity in which software complexity is a function of component complexity and system complexity. In this paper, we will use the next generation of functional size methods proposed by the COSMIC team [1][24], and we will look at it from the complexity perspective to identify some factors that affect complexity. Based on the analysis of such factors, we will propose a model for measuring a specific perspective of software complexity, which we will refer to as functional complexity. This model of functional complexity has two parts: component complexity, that is, the complexity of a functional process (COSMIC terminology) that comes from both the data movements and data manipulation; system complexity, that is, the complexity coming from relationships between the functional processes like communication, concurrence and multi-instances. Measuring these factors independently gives us a set of indicators or baselines for assessing software complexity from a functional perspective. Such a measure of functional complexity will then be used in the future in empirical studies to investigate its contribution to the improvements of estimation models which sometimes fare poorly when based only on functional size.