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Automatic Fault Diagnosis --SE Workshop--

Automatic Fault Diagnosis --SE Workshop--. Rui Abreu. TRADER Project. T elevision R elated A rchitecture to D esign and E nhance R eliability Improve user perceived reliability of high-volume consumer electronics Test case: television platform from NXP Three main LoA Error Detection

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Automatic Fault Diagnosis --SE Workshop--

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  1. Automatic Fault Diagnosis--SE Workshop-- Rui Abreu

  2. TRADER Project • Television Related Architecture to Design and Enhance Reliability • Improve user perceived reliability of high-volume consumer electronics • Test case: television platform from NXP • Three main LoA • Error Detection • Fault Diagnosis • Recovery

  3. Spectrum-based Fault Localization • Spectra for m runs • Error detection per run • Compare every column vector with the error vector similarity sj

  4. Error Detection • DIED: Dynamic Invariants for (automatic) Error Detection • Research question • How good are generic invariants as error detectors for SFL? • Two phases • Training: train the program to accept certain values • Execution: if value was not seen, run is set as failed

  5. Conclusions • SFL • Black-box approach: no models! • Low overhead, thus attractive for embedded systems • Quality of diagnosis is roughly 80% on average for the Siemens set (when using the reference program as error detector) • DIED • Simple and generic • Low overhead • Quality of diagnosis is identical to the one obtained with the reference program

  6. Future Work • Diagnose multiple software faults • Paper due to DX’08 and ASE’08 • Together with Johan de Kleer (PARC, USA) • Compare SFL with MBDs • Paper due to DX’08 (?) • Together with Markus Stumptner and Wolfgang Mayer (University of South Australia) • Improve the performance overhead of the automatic error detection

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