  State machine formalisms equipped with hierarchy and parallelism allow to
compactly model complex system behaviours. Such models can then be transformed
into executable code or inputs for model-based testing and verification
techniques. Generated artifacts are mostly flat descriptions of system
behaviour. \emph{Flattening} is thus an essential step of these
transformations. To assess the importance of flattening, we have defined and
applied a systematic mapping process and 30 publications were finally selected.
However, it appeared that flattening is rarely the sole focus of the
publications and that care devoted to the description and validation of
flattening techniques varies greatly. Preliminary assessment of associated tool
support indicated limited tool availability and scalability on challenging
models. We see this initial investigation as a first step towards generic
flattening techniques and scalable tool support, cornerstones of reliable
model-based behavioural development.
