1 code implementation • 13 Mar 2024 • Florian Tambon, Arghavan Moradi Dakhel, Amin Nikanjam, Foutse khomh, Michel C. Desmarais, Giuliano Antoniol
The bug patterns are presented in the form of a taxonomy.
1 code implementation • 24 Jan 2024 • Mina Taraghi, Gianolli Dorcelus, Armstrong Foundjem, Florian Tambon, Foutse khomh
Based on our qualitative analysis, we present a taxonomy of the challenges and benefits associated with PTM reuse within this community.
1 code implementation • 1 Nov 2023 • Florian Tambon, Foutse khomh, Giuliano Antoniol
Given a property selected by a user (e. g., neurons covered, faults), GIST enables the selection of good test sets from the point of view of this property among available test sets.
1 code implementation • 26 Jul 2023 • Mohammad Mehdi Morovati, Amin Nikanjam, Florian Tambon, Foutse khomh, Zhen Ming, Jiang
Based on our results, fixing ML bugs are more costly and ML components are more error-prone, compared to non-ML bugs and non-ML components respectively.
1 code implementation • 13 Jan 2023 • Florian Tambon, Vahid Majdinasab, Amin Nikanjam, Foutse khomh, Giuliano Antonio
This allows us to compare different mutation killing definitions based on existing approaches, as well as to analyze the behavior of the obtained mutation operators and their potential combinations called Higher Order Mutation(s) (HOM).
1 code implementation • 11 Aug 2022 • Florian Tambon, Foutse khomh, Giuliano Antoniol
Methods: In this work, we propose a Probabilistic Mutation Testing (PMT) approach that alleviates the inconsistency problem and allows for a more consistent decision on whether a mutant is killed or not.
1 code implementation • 26 Dec 2021 • Florian Tambon, Amin Nikanjam, Le An, Foutse khomh, Giuliano Antoniol
This paper presents the first empirical study of Keras and TensorFlow silent bugs, and their impact on users' programs.
1 code implementation • 26 Jul 2021 • Florian Tambon, Gabriel Laberge, Le An, Amin Nikanjam, Paulina Stevia Nouwou Mindom, Yann Pequignot, Foutse khomh, Giulio Antoniol, Ettore Merlo, François Laviolette
Method: We conduct a Systematic Literature Review (SLR) of research papers published between 2015 to 2020, covering topics related to the certification of ML systems.
1 code implementation • 10 Jul 2021 • Florian Tambon, Giulio Antoniol, Foutse khomh
Deep Neural Networks (DNN) applications are increasingly becoming a part of our everyday life, from medical applications to autonomous cars.