Affiliations: Sharif University of Technology, Tehran, Iran.
kamandi@ce.sharif.edu | Sharif University of Technology, Tehran, Iran.
jhabibi@sharif.edu
Note: [] Address for correspondence: Sharif University of Technology,
Tehran, Iran
Abstract: Modeling languages are needed to describe the conceptual construct
underlying software. Several modeling languages have been proposed during the
last decades. Cognitive complexity is one of the common problems in designing
modeling languages. Users have to split their attention and cognitive resources
between two different tasks when working with complex language: solving the
problem and understanding the elements composing the language. Several
researches have been accomplished to evaluate cognitive complexity of modeling
languages, among them, metric based and empirical approaches aremore important
and convenient than others. In this paper, we compared these two methods.
Results show that there is no significant relation between outputs generated by
these approaches.
Keywords: modeling language engineering, cognitive complexity, empirical study, metrics
