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Diagnosing Unobserved Components in Self-Adaptive Systems

Paulo Casanova, David Garlan, Bradley Schmerl and Rui Abreu.


In 9th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, Hyderabad, India, 2-3 June 2014.

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Abstract
Availability is an increasingly important quality for today's software-based systems and it has been successfully addressed by the use of closed-loop control systems in self-adaptive systems. Probes are inserted into a running system to obtain information and the information is fed to a controller that, through provided interfaces, acts on the system to alter its behavior. When a failure is detected, pinpointing the source of the failure is a critical step for a repair action. However, information obtained from a running system is commonly incomplete due to probing costs or unavailability of probes. In this paper we address the problem of fault localization in the presence of incomplete system monitoring. We may not be able to directly observe a component but we may be able to infer its health state. We provide formal criteria to determine when health states of unobservable components can be inferred and establish formal theoretical bounds for accuracy when using any spectrum-based fault localization algorithm.

Keywords: Diagnosis, Self-adaptation.  
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