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Dimensions of software configuration: on the configuration context in modern software development.

, , and . ESEC/SIGSOFT FSE, page 338-349. ACM, (2020)

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Predicting Performance via Automated Feature-interaction Detection, , , , , , and . Proceedings of the 34th International Conference on Software Engineering (ICSE '12), (2012)Generating attributed variability models for transfer learning., , and . VaMoS, page 5:1-5:8. ACM, (2020)Specialized Embedded DBMS: Cell Based Approach, , , , and . EDACS '09: 20th International Workshop on Database and Expert Systems Application (DEXA 2009), page 9--13. ISBN: 978-0-7695-3763-4, IEEE Computer Society, (2009)Performance Prediction in the Presence of Feature Interactions., , , , , , and . Software Engineering, volume P-227 of LNI, page 33-34. GI, (2014)White-Box Analysis over Machine Learning: Modeling Performance of Configurable Systems., , , , and . ICSE, page 1072-1084. IEEE, (2021)Green Configuration: Can Artificial Intelligence Help Reduce Energy Consumption of Configurable Software Systems?, , , , and . Computer, 55 (3): 74-81 (2022)Modeling Dependent Software Product Lines, , , and . Proceedings of the GPCE Workshop on Modularization, Composition and Generative Techniques for Product Line Engineering (McGPLE), MIP-0802, page 13--18. Department of Informatics and Mathematics, University of Passau, (October 2008)Features as First-class Entities : Toward a Better Representation of Features, , , , , and . Workshop on Modularization, Composition, and Generative Techniques for Product Line Engineering, MIP-0802, page 27--34. Department of Informatics and Mathematics, University of Passau, (October 2008)Exploring feature interactions in the wild: the new feature-interaction challenge, , , , and . Proceedings of the 5th International Workshop on Feature-Oriented Software Development, page 1--8. ACM, (2013)Exploring Hyperparameter Usage and Tuning in Machine Learning Research., , , , , and . CAIN, page 68-79. IEEE, (2023)