CMU-ISR-17-110
Institute for Software Research
School of Computer Science, Carnegie Mellon University



CMU-ISR-17-110

Uncertainty in Self-Adaptive Systems
Categories, Management, and Perspectives

Javier Cámara, David Garlan, Won Gu Kang,
Wenxin Peng, and Bradley Schmerl

July 2017

CMU-ISR-17-110.pdf

Keywords: Uncertainty, self-adaptation, decision-making, formal reasoning

Self-Adaptive systems are expected to adapt to unanticipated run-time events using imperfect information about their environment. This entails handling the effects of uncertainties in decision-making, which are not always considered as a first-class concern. This technical report summarizes a set of existing techniques and insights into addressing uncertainty in self-adaptive systems and outlines a future research agenda on uncertainty management in self-adaptive systems. The material in this report is strongly informed by our own research in the area, and is therefore not necessarily representative of other works.

45 pages


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