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2021 IEEE/ACM 43rd International Conference on Software Engineering: New Ideas and Emerging Results (ICSE-NIER)
Mutation testing is a well-established technique for assessing a test suite's quality by injecting artificial faults into production code. In recent years, mutation testing has been extended to machine learning (ML) systems, and deep learning (DL) in particular; researchers have proposed approaches, tools, and statistically sound heuristics to determine whether mutants in DL systems are killed or not. However, as we will argue in this work, questions can be raised to what extent currently useddoi:10.1109/icse-nier52604.2021.00022 fatcat:qt6524eg7jbxfapbmgv3wy4kyq