Diagnosing architectural run-time failures
Paulo Casanova,
David Garlan,
Bradley Schmerl and Rui Abreu.
In Proceedings of the 8th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, 20-21 May 2013. Received SEAMS 2013 Best Paper Award.
Online links:   Plain Text
Abstract
| Self-diagnosis is a fundamental capability of self-adaptive
systems. In order to recover from faults, systems need
to know which part is responsible for the incorrect behavior. In
previous work we showed how to apply a design-time diagnosis
technique at run time to identify faults at the architectural level
of a system. Our contributions address three major shortcomings
of our previous work: 1) we present an expressive, hierarchical
language to describe system behavior that can be used to
diagnose when a system is behaving different to expectation; the
hierarchical language facilitates mapping low level system events
to architecture level events; 2) we provide an automatic way to
determine how much data to collect before an accurate diagnosis
can be produced; and 3) we develop a technique that allows the
detection of correlated faults between components. Our results
are validated experimentally by injecting several failures into a
system and accurately diagnosing them using our algorithm. |
Keywords: Diagnosis, Self-adaptation.
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