BibTeX
@INBOOK{
         Hascoet2009RSf,
       title = "Reversal Strategies for Adjoint Algorithms",
       author = "Laurent Hasco{\"e}t",
       editor = "Bertot, Y. and Huet, G. and Levy, J.-J. and Plotkin, G.",
       publisher = "Cambridge University Press",
       year = "2009",
       booktitle = "From Semantics to Computer Science. Essays in memory of Gilles Kahn",
       pages = "487--503",
       abstract = "Adjoint Algorithms are a powerful way to obtain the gradients that are needed in
         Scientific Computing. Automatic Differentiation can build Adjoint Algorithms automatically by source
         transformation of the direct algorithm. The specific structure of Adjoint Algorithms strongly relies
         on reversal of the sequence of computations made by the direct algorithm. This reversal problem is
         at the same time difficult and interesting. This paper makes a survey of the reversal strategies
         employed in recent tools and describes some of the more abstract formalizations used to justify
         these strategies.",
       ad_tools = "Tapenade",
       ad_theotech = "reverse mode, adjoint, checkpointing, data-flow reversal, control-flow
         reversal"
}