Diferent techniques have been used to specify preferences for quality attributes and decision-making strategies of self-adaptive systems (SAS). These preferences are defined during requirement specification and design time. Further, it is well known that correctly identifying the preferences associated with the quality attributes is a major dificulty. This is exacerbated in the case of SAS, as the preferences defined at design time may not apply to contexts found at runtime. This paper aims at making an exploration of the research landscape that have addressed decision-making and quality attribute preferences speciication for selfadaptation, in order to identify new techniques that can improve the current state-of-the-art of decision-making to support self-adaptation. In this paper we (1) review difierent techniques that support decisionmaking for self-adaptation and identify limitations with respect to the identi cation of preferences and weights (i.e. the research gap), (2) identify existing solutions that deal with current limitations
Self-adaptation; decision making; preference trade-o; quality attributes
@inproceedings{wer201701,
author = {Paucar, L. H. G. and Bencomo, N.},
title = {A Survey on Preferences of Quality Attributes in the Decision-making for Self-Adaptive Systems: the Bad, the Good and the Ugly},
booktitle = {Proceedings of the WER2017-20th Workshop on Requirements Engineering, Buenos Aires - Argentina},
year = {2017},
issn = {2675-0066},
isbn = {978-987-3806-98-8},
doi = {}
}