  Software Product Lines (SPLs) are families of related software systems which
are distinguished by the set of features each system provides. Feature Models
are the de facto standard for modelling the variability of SPLs because they
describe the features, their relations, and all the combinations of features
that constitute a SPL. Because of their key role, feature models are at the
core of many tasks in SPL engineering. Our work presents an empirical study on
the comprehension of feature models for the task of checking the validity of
configurations. Our study explored the relation between the number of features
and the number of cross-tree constraints with the accuracy of participants'
answers to validity checking questions, and used eye fixations for analyzing
the difficulty in interpreting fixated information and the amount of cognitive
processing of the different parts of the feature model stimuli. We found that
answer accuracy does not relate individually to the number of features or to
the number of cross-tree constrains of a feature model, but both factors do
show an interaction on accuracy. Additionally, our study identified differences
in feature models with cross-tree constraints in both number of fixations and
fixation time, but no differences in those models without cross-tree
constraints.
