TEASMA: A Practical Methodology for Test Adequacy Assessment of Deep Neural Networks
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| Title | TEASMA: A Practical Methodology for Test Adequacy Assessment of Deep Neural Networks |
| Publication Type | Journal Article |
| Year of Publication | 2024 |
| Authors | Abbasishahkoo A, Dadkhah M, Briand L, Lin D |
| Journal | IEEE Transactions on Software Engineering |
| Pagination | 1-23 |
| Keywords | Accuracy, Analytical models, artificial neural networks, Computational modeling, Correlation, Deep Neural Network, Fault detection, Measurement, Predictive models, Test Adequacy Metrics, Test Assessment, testing, Training |
| DOI | 10.1109/TSE.2024.3482984 |
