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IEEE Transactions on Software Engineering - Special issue on software measurement principles, techniques, and environments
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Automated support for classifying software failure reports
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SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems principles
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Failure Diagnosis Using Decision Trees
ICAC '04 Proceedings of the First International Conference on Autonomic Computing
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IEEE Transactions on Software Engineering
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Online Diagnosis and Recovery: On the Choice and Impact of Tuning Parameters
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SP'96 Proceedings of the 1996 IEEE conference on Security and privacy
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This paper proposes an approach to software faults diagnosis in complex fault tolerant systems, encompassing the phases of error detection, fault location, and system recovery. Errors are detected in the first phase, exploiting the operating system support. Faults are identified during the location phase, through a machine learning based approach. Then, the best recovery action is triggered once the fault is located. Feedback actions are also used during the location phase to improve detection quality over time. A real world application from the Air Traffic Control field has been used as case study for evaluating the proposed approach. Experimental results, achieved by means of fault injection, show that the diagnosis engine is able to diagnose faults with high accuracy and at a low overhead.