Automatic Generation of Goal Models from Regulations

Abstract

Organizations in many domains such as healthcare, finances, telecommunications, educa-tion, and software development, must comply with an ever-increasing number of regula-tions, including laws and policies. In order to measure compliance to regulation, several recent approaches propose modelling regulations using goals and indicators. However, creating goal models for regulations is time consuming and prone to errors, especially as this is usually done manually. This thesis tackles this issue by automating some of the steps for creating goal models, and by offering better ways to create graphical views of goal models than what is currently available nowadays in goal modelling tools. The notation used in this thesis is the Goal-oriented Requirement Language (GRL), which is part of the User Requirements Notation standard and is supported by the jUCMNav tool. The concepts of regulations and their indicators are captured using a tab-ular presentation in Comma-Separated Value (CSV) files. An import mechanism is added to jUCMNav to automatically create regulation goal models from such files. The imported GRL model can then by visualized using novel features that enable the addition of multiple views/diagrams in an efficient and usable way.