Assessing the understandability of UML statechart diagrams with composite states—A family of empirical studies

Abstract

The main goal of this work is to present a family of empirical studies that we have carried out to investigate whether the use of composite states may improve the understandability of UML statechart diagrams derived from class diagrams. Our hypotheses derive from conventional wisdom, which says that hierarchical modeling mechanisms are helpful in mastering the complexity of a software system. In our research, we have carried out three empirical studies, consisting of five experiments in total. The studies differed somewhat as regards the size of the UML statechart models, though their size and the complexity of the models were chosen so that they could be analyzed by the subjects within a limited time period. The studies also differed with respect to the type of subjects (students vs. professionals), the familiarity of the subjects with the domains of the diagrams, and other factors. To integrate the results obtained from each of the five experiments, we performed a meta-analysis study which allowed us to take into account the differences between studies and to obtain the overall effect that the use of composite states has on the understandability of UML statechart diagrams throughout all the experiments. The results Empir Software Eng (2009) obtained are not completely conclusive. They cast doubts on the usefulness of composite states for a better understanding and memorizing of UML statechart diagrams. Composite states seem only to be helpful for acquiring knowledge from the diagrams. At any rate, it should be noted that these results are affected by the previous experience of the subjects on modeling, as well as by the size and complexity of the UML statechart diagrams we used, so care should be taken when generalizing our results.

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