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Using software product lines to create blockchain products: application to supply chain traceability.

, , , and . SPLC (A), page 97-107. ACM, (2022)

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Towards a cognitive model of feature model comprehension: an exploratory study using eye-tracking., , , and . SPLC (A), page 21-31. ACM, (2022)A first systematic mapping study on combinatorial interaction testing for software product lines., , , and . ICST Workshops, page 1-10. IEEE Computer Society, (2015)A variability aware configuration management and revision control platform., , and . ICSE (Companion Volume), page 803-806. ACM, (2016)Towards a fault-detection benchmark for evaluating software product line testing approaches., , and . SAC, page 2034-2041. ACM, (2018)On Extracting Feature Models from Sets of Valid Feature Combinations., , and . FASE, volume 7793 of Lecture Notes in Computer Science, page 53-67. Springer, (2013)Detecting Inconsistencies in Multi-View Models with Variability., and . ECMFA, volume 6138 of Lecture Notes in Computer Science, page 217-232. Springer, (2010)Coping with Variability in Model-Based Systems Engineering: An Experience in Green Energy., , , , , , , and . ECMFA, volume 6138 of Lecture Notes in Computer Science, page 293-304. Springer, (2010)Variability extraction and modeling for product variants., , and . SPLC, page 250. ACM, (2018)Comparative analysis of classical multi-objective evolutionary algorithms and seeding strategies for pairwise testing of Software Product Lines., , , , and . IEEE Congress on Evolutionary Computation, page 387-396. IEEE, (2014)Constraint-driven modeling through transformation., , and . Softw. Syst. Model., 14 (2): 573-596 (2015)