"TEASMA: A Practical Approach for the Test Assessment of Deep Neural ..."

Amin Abbasishahkoo et al. (2023)

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DOI: 10.48550/ARXIV.2308.01311

access: open

type: Informal or Other Publication

metadata version: 2023-08-21

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  - journals/corr/abs-2308-01311
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  - https://dblp.org/rec/journals/corr/abs-2308-01311
Amin Abbasishahkoo, Mahboubeh Dadkhah, Lionel C. Briand, Dayi Lin:
TEASMA: A Practical Approach for the Test Assessment of Deep Neural Networks using Mutation Analysis. CoRR abs/2308.01311 (2023)

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