To adapt or not to adapt? Technical debt and learning driven self-adaptation for managing runtime performance

Self-adaptive system (SAS) can adapt itself to optimize various key performance indicators in response to the dynamics and uncertainty in environment. In this paper, we present Debt Learning Driven Adaptation (DLDA), an framework that dynamically determines when and whether to adapt the SAS at runti...

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Bibliographic Details
Main Authors: Tao Chen, Rami Bahsoon, Shuo Wang, Xin Yao
Format: Default Conference proceeding
Published: 2018
Subjects:
Self-adaptive systems
Performance
Technical debt
Learning
Online Access:https://hdl.handle.net/2134/9876323.v1
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