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An Empirical Comparison of Mutant Selection Assessment Metrics.

, , , , and . ICST Workshops, page 90-101. IEEE, (2019)

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Model validation using mutated training labels: An exploratory study., , , , and . Neurocomputing, (June 2023)ConDefects: A New Dataset to Address the Data Leakage Concern for LLM-based Fault Localization and Program Repair., , , and . CoRR, (2023)Fairea: a model behaviour mutation approach to benchmarking bias mitigation methods., , , and . ESEC/SIGSOFT FSE, page 994-1006. ACM, (2021)Who Judges the Judge: An Empirical Study on Online Judge Tests., , , , , , , and . ISSTA, page 334-346. ACM, (2023)Do Pseudo Test Suites Lead to Inflated Correlation in Measuring Test Effectiveness?, , , , and . ICST, page 252-263. IEEE, (2019)Large Language Models for Software Engineering: Survey and Open Problems., , , , , , and . ICSE-FoSE, page 31-53. IEEE, (2023)Fairness Improvement with Multiple Protected Attributes: How Far Are We?, , , and . ICSE, page 160:1-160:13. ACM, (2024)ConDefects: A Complementary Dataset to Address the Data Leakage Concern for LLM-Based Fault Localization and Program Repair., , , and . SIGSOFT FSE Companion, page 642-646. ACM, (2024)Improving Machine Translation Systems via Isotopic Replacement., , , , , and . ICSE, page 1181-1192. ACM, (2022)MAAT: a novel ensemble approach to addressing fairness and performance bugs for machine learning software., , , and . ESEC/SIGSOFT FSE, page 1122-1134. ACM, (2022)