Pragmatic Requirements for Adaptive Systems: a Goal-Driven Modelling and Analysis Approach
This work addresses the challenge of modeling and analyzing adaptive systems for domain stakeholders, but it appears incremental as it builds on existing goal-model extensions.
The paper tackled the problem of context-dependent goal achievement in adaptive systems by introducing Pragmatic Goals with dynamic satisfaction criteria and an algorithm for deciding achievability. The result showed that specifying context-dependent goals makes it hard for stakeholders to cover all possibilities, highlighting the algorithm's importance in improving time and accuracy.
Goal-models (GM) have been used in adaptive systems engineering for their ability to capture the different ways to fulfill the requirements. Contextual GM (CGM) extend these models with the notion of context and context-dependent applicability of goals. In this paper, we observe that the interpretation of a goal achievement is itself context-dependent. Thus, we introduce the notion of Pragmatic Goals which have a dynamic satisfaction criteria. We also developed and evaluated an algorithm to decide the Pragmatic CGM's achievability. Finally, we performed several experiments to evaluate and to compare our algorithm against human judgment and concluded that the specification of context-dependent goals' applicability and interpretations make it hard for domain stakeholders to decide whether the model covers all possibilities, both in terms of time and accuracy, thus showing the importance and contribution of our algorithm.