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Damage Reduction via White-Box Failure Shaping

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Search-Based Software Engineering (SSBSE 2018)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 11036))

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Abstract

Emerging hardware that trades reliability guarantees for resource savings presents a challenge to software engineered for deterministic execution. Research areas like approximate computing, however, embrace non-determinism by abandoning strict correctness in favor of maximizing the probability and degree of correctness. Existing work has used stochastic failure sampling to perform white-box searches along software execution paths, producing criticality assessments of which selected operations are likely most damaging if they fail. Here, we apply these assessments to a new domain and employ them using failure shaping, an automated method for reducing a computation’s expected output damage in a model where failures can be relocated but not eliminated. In two case studies, we demonstrate error reductions of 38% to 63% on Strassen’s matrix multiplication algorithm despite a virtually identical failure count. We discuss how our framework helps provide a smooth landscape for performing the search-based software engineering that will be required to apply this technology to larger problems.

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Authors and Affiliations

  1. Department of Computer Science, University of New Mexico, Albuquerque, NM, 87131, USA

    Thomas B. Jones & David H. Ackley

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  1. Thomas B. Jones
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  2. David H. Ackley
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Correspondence to Thomas B. Jones .

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Editors and Affiliations

  1. State University of Maringá, Maringá, Brazil

    Thelma Elita Colanzi

  2. University of Sheffield, Sheffield, United Kingdom

    Phil McMinn

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Jones, T.B., Ackley, D.H. (2018). Damage Reduction via White-Box Failure Shaping. In: Colanzi, T., McMinn, P. (eds) Search-Based Software Engineering. SSBSE 2018. Lecture Notes in Computer Science(), vol 11036. Springer, Cham. https://doi.org/10.1007/978-3-319-99241-9_11

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  • DOI: https://doi.org/10.1007/978-3-319-99241-9_11

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