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SAPIENTML: Synthesizing Machine Learning Pipelines by Learning from Human-Written Solutions.

, , , , , , , , and . ICSE, page 1932-1944. ACM, (2022)

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Genealogical insights into the facts and fictions of clone removal, , , and . ACM SIGAPP Applied Computing Review, 13 (4): 30?42 (2013)Visualizing the evolution of code clones, , and . Proceedings of the 5th International Workshop on Software Clones, page 71?72. (2011)Bugs.jar: a large-scale, diverse dataset of real-world Java bugs., , , , and . MSR, page 10-13. ACM, (2018)Harnessing evolution for multi-hunk program repair., , and . ICSE, page 13-24. IEEE / ACM, (2019)Evaluating the conventional wisdom in clone removal: A genealogy-based empirical study, , , and . Proceedings of the 28th Annual ACM Symposium on Applied Computing, page 1123?1130. (2013)Toward understanding the causes of unanswered questions in software information sites: a case study of stack overflow., , and . ESEC/SIGSOFT FSE, page 663-666. ACM, (2013)Restoring the Executability of Jupyter Notebooks by Automatic Upgrade of Deprecated APIs., , , and . ASE, page 240-252. IEEE, (2021)Fuzz testing based data augmentation to improve robustness of deep neural networks., , , and . ICSE, page 1147-1158. ACM, (2020)Evaluating Code Clone Genealogies at Release Level: An Empirical Study., , , , and . SCAM, page 87-96. IEEE Computer Society, (2010)A discriminative model approach for suggesting tags automatically for stack overflow questions., , and . MSR, page 73-76. IEEE Computer Society, (2013)