Abstract
Different 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 difficulty. 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 specification 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 different techniques that support decisionmaking for self-adaptation and identify limitations with respect to the identification of preferences and weights (i.e. the research gap), (2) identify existing solutions that deal with current limitations.
Divisions: | Engineering & Applied Sciences > Computer Science Engineering & Applied Sciences > Systems analytics research institute (SARI) Engineering & Applied Sciences |
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Event Title: | 20th Ibero-American Conference on Software Engineering, CIbSE 2017 |
Event Type: | Other |
Event Dates: | 2017-05-22 - 2017-05-23 |
Uncontrolled Keywords: | Decision making,Preference trade-off,Quality attributes,Self-adaptation,Human-Computer Interaction,Software,Signal Processing,Artificial Intelligence |
Full Text Link: | |
Related URLs: |
http://www.scop ... tnerID=8YFLogxK
(Scopus URL) |
Published Date: | 2017 |
Published Online Date: | 2017-05-23 |
Authors: |
Paucar, Luis H.Garcia
Bencomo, Nelly ( ![]() |