Abstract

Goal models allow software engineers to model software system requirements and stake holder objectives at a high level of abstraction. We extend the use of goal models by presenting a probability model for them. The probability model can be used to compute the probability of satisfaction and denial of goals, and may have other applications as well. In our probability model, goal satisfaction and denial is expressed as a function of leaf level tasks being satisfied and denied given that all contribution links are satisfied. We also translate goal models to Bayesian networks that satisfy our probability model. Using Bayesian networks allows for the probability to be calculated efficiently, which we demonstrate in our experimental evaluation. Furthermore, using Bayesian networks allows the research on Bayesian networks to be applied on goal models. 1

Citations