An Empirical Evaluation Roadmap for iStar 2.0

نویسندگان

  • Lidia López
  • Fatma Basak Aydemir
  • Fabiano Dalpiaz
  • Jennifer Horkoff
چکیده

The iStar 2.0 modeling language is the result of a two-year long community effort intended at providing a solid, unified basis for teaching and conducting research with i*. The language was released with important qualities in mind, such as keeping a core set of primitives, providing a clear meaning for those primitives, and flattening the learning curve for new users. In this paper, we propose a list of qualities against which we intend iStar 2.0 to be evaluated. Furthermore, we describe and empirical evaluation plan, which we devise in order to assess the extent to which the language meets identified qualities and to inform the development of further versions of the language. Besides explaining the objectives and steps of our planned empirical studies, we make a call for involving the research community in our endeavor.

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تاریخ انتشار 2016