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Software Product Lines (SPLs) are families of related software systems whichare distinguished by the set of features each system provides. Feature Modelsare the de facto standard for modelling the variability of SPLs because theydescribe the features, their relations, and all the combinations of featuresthat constitute a SPL. Because of their key role, feature models are at thecore of many tasks in SPL engineering. Our work presents an empirical study onthe comprehension of feature models for the task of checking the validity ofconfigurations. Our study explored the relation between the number of featuresand the number of cross-tree constraints with the accuracy of participants'answers to validity checking questions, and used eye fixations for analyzingthe difficulty in interpreting fixated information and the amount of cognitiveprocessing of the different parts of the feature model stimuli. We found thatanswer accuracy does not relate individually to the number of features or tothe number of cross-tree constrains of a feature model, but both factors doshow an interaction on accuracy. Additionally, our study identified differencesin feature models with cross-tree constraints in both number of fixations andfixation time, but no differences in those models without cross-treeconstraints.

An Empirical Eye-Tracking Study of Feature Model Comprehension