Automated derivation of application-Specific error detectors using dynamic analysis

Karthik Pattabiraman, Giancinto Paolo Saggese, Daniel Chen, Zbigniew Kalbarczyk, Ravishankar Iyer

Research output: Contribution to journalArticlepeer-review

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, runtime checking of the application. The coverage of the derived detectors is evaluated using fault-injection experiments, while the performance and area overheads of the detectors are evaluated by synthesizing them on reconfigurable hardware.

Original languageEnglish (US)
Article number5467091
Pages (from-to)640-655
Number of pages16
JournalIEEE Transactions on Dependable and Secure Computing
Volume8
Issue number5
DOIs
StatePublished - 2011

Keywords

  • Data errors
  • FPGA hardware
  • critical variables
  • dynamic execution
  • likely invariants

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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