Quality Attributes Assessment in Self-Adaptive Systems: An Empirical Evaluation

Self-adaptive  systems  are  capable  to  monitor  themselves and  the  context  surrounding  them,  detect  changes,  and  decide  how to  react  to  unexpected  conditions  with  minimal  human  supervision  at runtime. One of the challenges behind the development of self-adaptive systems is to handle the decision-making process during the analysis of trade off points between multiple quality attributes (QA). In Software Engineering, a widely-accepted method for evaluating software architectures QA goals is the Architecture Tradeoff Analysis Method (ATAM). However, few studies report on tradeoff analysis of QA in self-adaptive systems, despite its importance. Therefore, in this article, we proposed an  adapted  version  of  the  ATAM  to  handle  the  particularities  of  self-adaptive  systems.  We  employed  the  UPPAAL  SMC  to  assist  in  the analysis of a set of QA. To assess whether the proposed adaptation is feasible in practice, we carried out an empirical evaluation by running the  adapted  ATAM  in  a  self-adaptive  system  developed  following  the MAPE-K  model.  The  yielded  results  indicate  that  the  adapted  ATAM could support the design decision process in self-adaptive systems thatuse the MAPE-K model.