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Learning Software Configuration Spaces: A Systematic Literature Review., , , , , and . CoRR, (2019)Heuristic and exact algorithms for product configuration in software product lines., , , and . Int. Trans. Oper. Res., 24 (6): 1285-1306 (2017)Learning software configuration spaces: A systematic literature review., , , , , and . J. Syst. Softw., (2021)Identification and relationship between notation and tool for feature models with graphic representation., , , , , and . SCCC, page 1-12. IEEE, (2016)Predicting Design Impactful Changes in Modern Code Review: A Large-Scale Empirical Study., , , , , , , , and . MSR, page 471-482. IEEE, (2021)Feature subset selection for learning huge configuration spaces: the case of linux kernel size., , , , , , , and . SPLC (A), page 85-96. ACM, (2022)A comparison of performance specialization learning for configurable systems., , , and . SPLC (A), page 46-57. ACM, (2021)Sampling Effect on Performance Prediction of Configurable Systems: A Case Study., , , and . ICPE, page 277-288. ACM, (2020)Analysis of a many-objective optimization approach for identifying microservices from legacy systems., , , , , , and . Empir. Softw. Eng., 27 (2): 51 (2022)Analyzing a Semantics-Aware Bug Seeding Tool's Efficacy: A qualitative study with the SemSeed tool., , , , , , , and . SBES, page 246-256. ACM, (2023)