This work 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.
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This work 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. 168 pp. Englisch. Seller Inventory # 9783659672323
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This work 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.Books on Demand GmbH, Überseering 33, 22297 Hamburg 168 pp. Englisch. Seller Inventory # 9783659672323
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