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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.

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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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