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.
Online links:   Plain Text
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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