Model-based Simplified Functional Size Measurement - an Experimental Evaluation with COSMIC Function Points

Functional Size Measurement methods –like the COSMIC method– are widely used but have two major shortcomings: they require a complete and detailed knowledge of user requirements and they are carried out via relatively expensive and lengthy processes. To tackle these issues, simplified measurement processes have been proposed that can be applied to requirements specifications even if they are incomplete or not very detailed. Since software requirements can be effectively modeled using languages like UML and the models increase their level of detail and completeness through the development lifecycle, our goal is to define the characteristics of progressively refined requirements models that support progressively more sophisticated and accurate measurement processes for functional software size. We consider the COSMIC method and three simplified measurement processes, and we show how they can be carried out, based on UML diagrams. Then, the accuracy of the measurement supported by each type of UML model is empirically tested, by analyzing the results obtained on a set of projects. Our analysis shows that it is possible to write progressively more detailed and complete user requirements UML models that provide the data required by simplified methods, which provide progressively more accurate values for functional size measures of the modeled software. Conclusions. Developers that use UML for requirements model can obtain an estimation of the application’s functional size early on in the development process, when only a very simple UML model has been built for the application, and can get increasingly more accurate size estimates while the knowledge of the product increases and UML models are refined accordingly.