172 citations · 254 across the 21 of their papers we have counts for
4 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…
Reinforcement Learning Informed Evolutionary Search for Autonomous Systems Testing
Dmytro Humeniuk, Foutse Khomh, Giuliano Antoniol
Evolutionary search-based techniques are commonly used for testing autonomous robotic systems. However, these approaches often rely on computationally expensive simulator-based mod…
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…
AmbieGen: A Search-based Framework for Autonomous Systems Testing
Dmytro Humeniuk, Foutse Khomh, Giuliano Antoniol
Thorough testing of safety-critical autonomous systems, such as self-driving cars, autonomous robots, and drones, is essential for detecting potential failures before deployment. O…