Can Patterns Improve i* Modeling? Two Exploratory Studies

  • Authors:

  • Markus Strohmaier;Jennifer Horkoff;Eric Yu;Jorge Aranda;Steve Easterbrook

  • Affiliations:

  • Knowledge Management Institute, Graz University of Technology and Know-Center, Graz, Austria;Department of Computer Science, University of Toronto, Toronto, Canada;Faculty of Information Studies, University of Toronto, Toronto, Canada;Department of Computer Science, University of Toronto, Toronto, Canada;Department of Computer Science, University of Toronto, Toronto, Canada

  • Venue:
  • REFSQ '08 Proceedings of the 14th international conference on Requirements Engineering: Foundation for Software Quality
  • Year:
  • 2008

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Abstract

A considerable amount of effort has been placed into the investigation of i* modeling as a tool for early stage requirements engineering. However, widespread adoption of i* models in the requirements process has been hindered by issues such as the effort required to create the models, coverage of the problem context, and model complexity. In this work, we explore the feasibility of pattern application to address these issues. To this end, we perform both an exploratory case study and initial experiment to investigate whether the application of patterns improves aspects of i* modeling. Furthermore, we develop a methodology which guides the adoption of patterns for i* modeling. Our findings suggest that applying model patterns can increase model coverage, but increases complexity, and may increase modeling effort depending on the experience of the modeler. Our conclusions indicate situations where pattern application to i* models may be beneficial.