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ML Dependency Analysis for Assessors

  • Philippe Ayrault
  • Vincent Benayoun
  • Catherine Dubois
  • François Pessaux
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7504)

Abstract

Critical software needs to obtain an assessment before commissioning. This assessment is given after a long task of software analysis performed by assessors. They may be helped by tools, used interactively, to build models using information-flow analysis. Tools like SPARK-Ada exist for Ada subsets used for critical software. But some emergent languages such as those of the ML family lack such adapted tools. Providing similar tools for ML languages requires special attention on specific features such as higher-order functions and pattern-matching. This paper presents an information-flow analysis for such a language specifically designed according to the needs of assessors. This analysis can be parametrized to allow assessors getting a view of dependencies at several levels of abstraction and gives the basis for an efficient fault tolerance analysis.

Keywords

Operational Semantic Dependency Analysis Recursive Call Dependency Term Fault Injection 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Philippe Ayrault
    • 1
    • 2
  • Vincent Benayoun
    • 3
  • Catherine Dubois
    • 3
    • 4
    • 5
  • François Pessaux
    • 6
  1. 1.EtersafePalaiseauFrance
  2. 2.LIP6Université Paris 6ParisFrance
  3. 3.Laboratoire CEDRICCNAMParisFrance
  4. 4.ENSIIEEvryFrance
  5. 5.INRIAParisFrance
  6. 6.ENSTA ParisTechUEIPalaiseauFrance

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