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This paper presents GOOFI-2, a comprehensive fault in jection tool for experimental dependability assessment of embedded systems. The tool includes a large number of ex tensions and improvements over its predecessor, GOOF!. These include support for three widely used fault injection techniques, two target processors, and a variety of new features for storing, disseminating and analyzing experi mental data. We report on our experiences and lessons learned from the use and development ofGOOFI-2. In par ticular, we compare and discuss properties of three fault injection techniques: Nexus-based, exception-based and instrumentation-based injection. The comparison relies on several sets of experiments with two target processors, Freescale's MPC565 and MPC5554.

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This paper investigates sources of uncertainty in measurement results obtained using three different fault injection techniques. Two software-implemented and one test port-based technique are characterized and compared. The three techniques can be used to inject the same faults, which are defined in a shared database. Due to the uncertainties associated with the techniques, which we identify and discuss, the results of injecting a given fault may differ to some extent. The paper analyzes the results of using the three techniques to inject faults into two experimental targets: a brake-by-wire controller and a partitioning operating system. The objective of the experiments is to determine whether the results of the different techniques are metrologically compatible and, consequently, meaningful when disseminated and compared. Our observations indicate that, even though the outcome of many individual experiments is affected by uncertainties, the three techniques produce similar average results over a large number of experiments.

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