Analyzing comprehension of models of variable software systems with eye-tracking technologies

Abstract

Software Product Lines (SPLs) are families of related software systems which are distinguished by the set of features each system provides. Feature Models are pivotal components of Software Product Lines and 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. Therefore, their correct comprehension is crucial for performing adequately all the tasks where they are involved. According to our knowledge, no research has been conducted on feature model comprehension. To address this lack, we contribute an empirical study of feature model comprehension in simple configuration validation tasks. We propose a first cognitive model for this type of tasks that we analyze by measuring eye gaze fixations on the different visual elements involved in the tasks. Our results identified three main components of the cognitive model and their distribution in terms of the cognitive effort for performing these tasks. We argue that further research on feature model comprehension can inform language design and tool development to provide more suitable language structures, user interfaces and support for this kind of models.

Date	9 Aug 2022
Original language	American English
Awarding Institution	École de technologie supérieure
Supervisor	Roberto Erick Lopez Herrejon (Supervisor)