Exploring Feature Interactions Without Specifications: A Controlled Experiment

kaestner@cs.cmu.edu (L. Soares, J. Meinicke, S. Nadi, C. Kästner, E. de Almeida)
Thu, 08 Nov 2018 12:04:37 -0500

Larissa Rocha Soares, Jens Meinicke, Sarah Nadi, Christian Kästner, and Eduardo Santana de Almeida. Exploring Feature Interactions Without Specifications: A Controlled Experiment. In Proceedings of the 17th ACM International Conference on Generative Programming and Component Engineering (GPCE), pages 41--52, New York, NY: ACM Press, 2018.

In highly configurable systems, features may interact unexpectedly and produce faulty behavior. Those faults are not easily identified from the analysis of each feature separately, especially when feature specifications are missing. We propose VarXplorer, a dynamic and iterative approach to detect suspicious interactions. It provides information on how features impact the control and data flow of the program. VarXplorer supports developers with a graph that visualizes this information, mainly showing suppress and require relations between features. To evaluate whether VarXplorer helps improve the performance of identifying suspicious interactions, we perform a controlled study with 24 subjects. We find that with our proposed feature-interaction graphs, participants are able to identify suspicious interactions more than 3 times faster compared to the state-of-the-art tool.