Fault Injection Campaign for a Fault Tolerant Duplex Framework

2007 ◽  
Author(s):  
Gian Franco Sacco ◽  
Robert D. Ferraro ◽  
Paul von Allmen ◽  
Dave A. Rennels
Keyword(s):  
Fault Tolerant ◽  
Fault Injection

A Recovery-Oriented Approach for Software Fault Diagnosis in Complex Critical Systems

2012 ◽  
pp. 29-56
Author(s):  
Gabriella Carrozza ◽  
Roberto Natella
Keyword(s):  
Error Detection ◽  
Traffic Control ◽  
Fault Location ◽  
Fault Tolerant ◽  
Fault Injection ◽  
Critical Systems ◽  
Software Faults ◽  
Real World Application ◽  
Complex Fault ◽  
Detection Quality

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.

A Recovery-Oriented Approach for Software Fault Diagnosis in Complex Critical Systems

2011 ◽  
Vol 2 (1) ◽  
pp. 77-104 ◽  
Author(s):  
Gabriella Carrozza ◽  
Roberto Natella
Keyword(s):  
Error Detection ◽  
Traffic Control ◽  
Fault Location ◽  
Fault Tolerant ◽  
Fault Injection ◽  
Critical Systems ◽  
Software Faults ◽  
Real World Application ◽  
Complex Fault ◽  
Detection Quality

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.

scholarly journals Test

2021 ◽  
pp. 381-391
Author(s):  
Peter Marwedel
Keyword(s):  
Physical System ◽  
Fault Tolerant ◽  
Fault Injection ◽  
Fault Simulation ◽  
Fault Coverage ◽  
Fault Model ◽  
Pattern Generation ◽  
Signature Analysis ◽  
Fault Tolerant Systems ◽  
Random Patterns

AbstractUnfortunately, we cannot rely on designed and possibly already manufactured systems to operate as expected. These systems may have become defective during their use, or their function may have been compromised during the fabrication or their design. The purpose of testing is to verify whether or not an existing embedded/cyber-physical system can be operated as expected. In this chapter, we will present fundamental terms and techniques for testing. There will be a brief introduction to the aims of test pattern generation and their application. We will be introducing terms such as fault model, fault coverage, fault simulation, and fault injection. Also, we will be presenting techniques which improve testability, including the generation of pseudo-random patterns, and signature analysis. It would be beneficial to consider testability issues already during design. In case of fault-tolerant systems, resilience must be verified.

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