Miguel Goulao



Miguel Goulão is Assistant Professor at FCT/UNL, in Portugal, where he obtained his PhD in 2008, and a member of the CITI research center. His current research interests include experimental software engineering, software evolution and reengineering, software quality, software languages engineering and evaluation, and requirements engineering. He has co-authored over 45 peer-reviewed papers, one of which received the Janos Szentes award in the 6th European Conference on Software Quality.


Goal-Oriented Requirements Engineering (GORE) approaches have been developed to facilitate the requirements engineers work by, for example, providing abstraction mechanisms to help eliciting and modeling requirements. One of the well-established GORE approaches is KAOS. Nevertheless, in large-scale systems building KAOS models may result in incomplete and/or complex goal models, which are difficult to understand and change. This may lead to an increase in costs of product development and evolution. Thus, for large-scale systems, the effective management of complexity and completeness of goal models is vital. In this paper, we propose a metrics framework for supporting the quantitative assessment of complexity and completeness of KAOS goal models. Those metrics are formally specified, implemented and incorporated in a KAOS modeling tool. We validate the metrics with a set of real-world case studies and discuss the identified recurring modeling practices.