Graphical Modeling VS. Textual Modeling: An Experimental Comparison Based on iStar Models

Abstract

[Context] Establishing requirements models is an effective way to analyze them, which is typically dealt with in a graphical manner (i.e., the drag-and-draw fashion). However, as the size of models increases, the scalability issue has become an unignorable challenge, hindering the practical adoption of requirements modeling approach. Some researchers have recently proposed and promoted textual modeling approaches, mitigating these issues of requirements modeling. [Objective] In this paper, we aim at evaluating the two modeling methods, i.e., a graphical modeling method VS. a textual modeling method. In particular, we apply these two methods to iStar modeling language, which has been widely recognized as an effective means to model and analyze requirements. [Methods] We have systematically designed and conducted a controlled experiment with 38 participants to compare two iStar modeling methods (graphical and textual) using two corresponding modeling tools (piStar and T-Star). The experimental results reveal that the numbers of iStar model nodes and relationships built by the participants had no significant difference, regardless of the modeling method adopted. [Conclusions] First, the results show that the textual modeling method is as usable as the graphical modeling method when creating iStar models. Second, we have identified a number of issues that contribute to improving the utility and practicality of the iStar modeling method.