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Comparing model coverage and code coverage in model driven testing: An exploratory study 1-gen-2016 Amalfitano, D.; De Simone, V.; Fasolino, A. R.; Riccio, V.
Towards a Thing-In-the-Loop approach for the Verification and Validation of IoT systems 1-gen-2017 Amalfitano, D.; Amatucci, N.; De Simone, V.; Riccio, V.; Rita, F. A.
Is this the lifecycle we really want?: An automated black-box testing approach for Android activities 1-gen-2018 Riccio, V.; Amalfitano, D.; Fasolino, A. R.
Why does the orientation change mess up my Android application? From GUI failures to code faults 1-gen-2018 Amalfitano, D.; Riccio, V.; Paiva, A. C. R.; Fasolino, A. R.
Combining Automated GUI Exploration of Android apps with Capture and Replay through Machine Learning 1-gen-2019 Amalfitano, D.; Riccio, V.; Amatucci, N.; Simone, V. D.; Fasolino, A. R.
Model-based exploration of the frontier of behaviours for deep learning system testing 1-gen-2020 Riccio, V.; Tonella, P.
Testing machine learning based systems: a systematic mapping 1-gen-2020 Riccio, Vincenzo; Jahangirova, Gunel; Stocco, Andrea; Humbatova, Nargiz; Weiss, Michael; Tonella, Paolo
Do Memories Haunt You? An Automated Black Box Testing Approach for Detecting Memory Leaks in Android Apps 1-gen-2020 Amalfitano, Domenico; Riccio, Vincenzo; Tramontana, Porfirio; Rita Fasolino, Anna
Taxonomy of real faults in deep learning systems 1-gen-2020 Humbatova, N.; Jahangirova, G.; Bavota, G.; Riccio, V.; Stocco, A.; Tonella, P.
DeepHyperion: Exploring the feature space of deep learning-based systems through illumination search 1-gen-2021 Zohdinasab, T.; Riccio, V.; Gambi, A.; Tonella, P.
DeepMetis: Augmenting a Deep Learning Test Set to Increase its Mutation Score 1-gen-2021 Riccio, V.; Humbatova, N.; Jahangirova, G.; Tonella, P.
SBST Tool Competition 2021 1-gen-2021 Panichella, S.; Gambi, A.; Zampetti, F.; Riccio, V.
Efficient and Effective Feature Space Exploration for Testing Deep Learning Systems 1-gen-2022 Zohdinasab, Tahereh; Riccio, Vincenzo; Gambi, Alessio; Tonella, Paolo
SBST Tool Competition 2022 1-gen-2022 Gambi, A.; Jahangirova, G.; Riccio, V.; Zampetti, F.
An Empirical Study on Low- and High-Level Explanations of Deep Learning Misbehaviours 1-gen-2023 Zohdinasab, Tahereh; Riccio, Vincenzo; Tonella, Paolo
Software testing in the machine learning era: Special issue of the empirical Software Engineering (EMSE) journal 1-gen-2023 Stocco, A.; Shehory, O.; Jahangirova, G.; Riccio, V.; Barash, G.; Farchi, E.; Saha, D.
SBFT Tool Competition 2023 - Cyber-Physical Systems Track 1-gen-2023 Biagiola, Matteo; Klikovits, Stefan; Peltomaki, Jarkko; Riccio, Vincenzo
When and Why Test Generators for Deep Learning Produce Invalid Inputs: an Empirical Study 1-gen-2023 Riccio, Vincenzo; Tonella, Paolo
DeepAtash: Focused Test Generation for Deep Learning Systems 1-gen-2023 Zohdinasab, Tahereh; Riccio, Vincenzo; Tonella, Paolo
Two is better than one: digital siblings to improve autonomous driving testing 1-gen-2024 Biagiola, Matteo; Stocco, Andrea; Riccio, Vincenzo; Tonella, Paolo
The 5thWorkshop on Testing for Deep Learning and Deep Learning for Testing (DeepTest 2024) 1-gen-2024 Biagiola, M.; Cardozo, N.; Khomh, F.; Riccio, V.; Shin, D.; Stocco, A.
Mostrati risultati da 1 a 21 di 21
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