Automated Derivation of Application-specific Error Detectors Using Dynamic Analysis

Karthik Pattabiraman, Giacinto Paulo Saggese, Daniel Chen, Zbigniew Kalbarczyk and Ravishankar Iyer, IEEE Transactions on Dependable and Secure Computing (TDSC) Vol 8., Issue 5, Sept/Oct 2011 . [ PDF File ]

Abstract: This paper proposes a novel technique for preventing a wide range of data errors from corrupting the execution of applications. The proposed technique enables automated derivation of fine-grained, application-specific error detectors based on dynamic traces of application execution. The technique derives a set of error detectors using rule-based templates to maximize the error detection coverage for the application. A probability model is developed to guide the choice of the templates and their parameters for error-detection. The paper also presents an automatic framework for synthesizing the set of detectors in hardware to enable low-overhead, run-time checking of the application. The coverage of the derived detectors is evaluated using fault injection experiments, while the performance and area overhead of the detectors is evaluated by synthesizing them on reconfigurable hardware.

This paper supercedes the following conference paper.

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