TY - GEN
T1 - Exploring feature interactions without specifications
T2 - 17th ACM SIGPLAN International Conference on Generative Programming: Concepts and Experiences, GPCE 2018, co-located with SPLASH 2018
AU - Soares, Larissa Rocha
AU - Meinicke, Jens
AU - Nadi, Sarah
AU - Kästner, Christian
AU - Santana de Almeida, Eduardo
N1 - Publisher Copyright:
© 2018 Association for Computing Machinery.
PY - 2018/11/5
Y1 - 2018/11/5
N2 - 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.
AB - 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.
KW - Controlled Experiment
KW - Feature Interaction
KW - Highly Configurable Systems
UR - http://www.scopus.com/inward/record.url?scp=85059024552&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85059024552&partnerID=8YFLogxK
U2 - 10.1145/3278122.3278127
DO - 10.1145/3278122.3278127
M3 - Conference contribution
AN - SCOPUS:85059024552
T3 - GPCE 2018 - Proceedings of the 17th ACM SIGPLAN International Conference on Generative Programming: Concepts and Experiences, co-located with SPLASH 2018
SP - 40
EP - 52
BT - GPCE 2018 - Proceedings of the 17th ACM SIGPLAN International Conference on Generative Programming
A2 - Van Wyk, Eric
A2 - Rompf, Tiark
PB - Association for Computing Machinery, Inc
Y2 - 5 November 2018 through 6 November 2018
ER -