172 citations · 254 across the 21 of their papers we have counts for
3 papers · 1 filter
GIST: Generated Inputs Sets Transferability in Deep Learning
Florian Tambon, Foutse Khomh, Giuliano Antoniol
To foster the verifiability and testability of Deep Neural Networks (DNN), an increasing number of methods for test case generation techniques are being developed. When confronted…
Mutation Testing of Deep Reinforcement Learning Based on Real Faults
Florian Tambon, Vahid Majdinasab, Amin Nikanjam +2
Testing Deep Learning (DL) systems is a complex task as they do not behave like traditional systems would, notably because of their stochastic nature. Nonetheless, being able to ad…
Models of Computational Profiles to Study the Likelihood of DNN Metamorphic Test Cases
Ettore Merlo, Mira Marhaba, Foutse Khomh +2
Neural network test cases are meant to exercise different reasoning paths in an architecture and used to validate the prediction outcomes. In this paper, we introduce "computationa…