Reflection on Evolutionary Decision Making with Goal Modeling via Empirical Studies
Alicia M. Grubb, “Reflection on Evolutionary Decision Making with Goal Modeling via Empirical Studies.” Proceedings of the IEEE 26th International Requirements Engineering Conference (RE), 2018.
Abstract: Goal models have long been used in academia without wide spread adoption in industry. If the fundamental purpose of goal models is to allow stakeholders to generate scenarios and ask what if questions, then which parts of the process of model construction, analysis, and evolution benefit from and which are hindered by manual activities? The recent expansion of goal modelling to ask time-based questions further amplifies this issue because significant additional information is required from stakeholders. Through a series of empirical studies, we aim to isolate the processes of model construction, analysis, and evolution for the purpose of studying the utility of goal-oriented requirements engineering approaches and exploring which tasks are essential practices that stakeholders must complete themselves to gain modeling benefit, and which tasks can be simplified through automation. In this process, we will also measure the benefits of completing relevant goal modelling activities with and without timing analysis. In this short communication, we describe our objectives for understanding the benefits of and barriers to goal-oriented requirements engineering.