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2020 – today
- 2024
[j94]Matteo Biagiola
, Andrea Stocco, Vincenzo Riccio, Paolo Tonella:
Two is better than one: digital siblings to improve autonomous driving testing. Empir. Softw. Eng. 29(4): 72 (2024)- [j93]Michael Weiss, Paolo Tonella:
Adopting Two Supervisors for Efficient Use of Large-Scale Remote Deep Neural Networks. ACM Trans. Softw. Eng. Methodol. 33(1): 28:1-28:29 (2024) - [j92]Michael Weiss, Paolo Tonella:
Adopting Two Supervisors for Efficient Use of Large-Scale Remote Deep Neural Networks - RCR Report. ACM Trans. Softw. Eng. Methodol. 33(1): 29:1-29:4 (2024) - [j91]Matteo Biagiola, Paolo Tonella:
Testing of Deep Reinforcement Learning Agents with Surrogate Models. ACM Trans. Softw. Eng. Methodol. 33(3): 73:1-73:33 (2024) - [j90]Tahereh Zohdinasab, Vincenzo Riccio, Paolo Tonella:
Focused Test Generation for Autonomous Driving Systems. ACM Trans. Softw. Eng. Methodol. 33(6): 152 (2024) - [j89]Jon Ayerdi, Valerio Terragni, Gunel Jahangirova, Aitor Arrieta, Paolo Tonella:
GenMorph: Automatically Generating Metamorphic Relations via Genetic Programming. IEEE Trans. Software Eng. 50(7): 1888-1900 (2024) - [j88]Matteo Biagiola, Paolo Tonella:
Boundary State Generation for Testing and Improvement of Autonomous Driving Systems. IEEE Trans. Software Eng. 50(8): 2040-2053 (2024) - [c197]Michele Pasqua, Mariano Ceccato, Paolo Tonella:
Hypertesting of Programs: Theoretical Foundation and Automated Test Generation. ICSE 2024: 115:1-115:12 - [c196]Sajad Khatiri, Sebastiano Panichella, Paolo Tonella:
Simulation-based Testing of Unmanned Aerial Vehicles with Aerialist. ICSE Companion 2024: 134-138 - [c195]Ruben Grewal, Paolo Tonella, Andrea Stocco:
Predicting Safety Misbehaviours in Autonomous Driving Systems Using Uncertainty Quantification. ICST 2024: 70-81 - [c194]Nargiz Humbatova, Gunel Jahangirova, Paolo Tonella:
Spectral Analysis of the Relation between Deep Learning Faults and Neural Activation Values. ICST 2024: 245-256 - [c193]Andréa Doreste, Matteo Biagiola, Paolo Tonella:
Adversarial Testing with Reinforcement Learning: A Case Study on Autonomous Driving. ICST 2024: 293-304 - [d42]Nargiz Humbatova, Gunel Jahangirova, Paolo Tonella:
Spectral Analysis of the Relation between Deep Learning Faults and Neural Activation Values: Replication Package. Zenodo, 2024
- [i32]Luca Giamattei, Matteo Biagiola, Roberto Pietrantuono, Stefano Russo, Paolo Tonella:
Reinforcement Learning for Online Testing of Autonomous Driving Systems: a Replication and Extension Study. CoRR abs/2403.13729 (2024) - [i31]Ruben Grewal, Paolo Tonella, Andrea Stocco:
Predicting Safety Misbehaviours in Autonomous Driving Systems using Uncertainty Quantification. CoRR abs/2404.18573 (2024) - [i30]Deepak-George Thomas, Matteo Biagiola, Nargiz Humbatova, Mohammad Wardat, Gunel Jahangirova, Hridesh Rajan, Paolo Tonella:
muPRL: A Mutation Testing Pipeline for Deep Reinforcement Learning based on Real Faults. CoRR abs/2408.15150 (2024) - [i29]Luciano Baresi, Davide Yi Xian Hu, Andrea Stocco, Paolo Tonella:
Efficient Domain Augmentation for Autonomous Driving Testing Using Diffusion Models. CoRR abs/2409.13661 (2024) - 2023
- [j87]Andrea Romdhana, Alessio Merlo, Mariano Ceccato, Paolo Tonella:
Assessing the security of inter-app communications in android through reinforcement learning. Comput. Secur. 131: 103311 (2023) - [j86]Andrea Stocco, Brian Pulfer, Paolo Tonella:
Model vs system level testing of autonomous driving systems: a replication and extension study. Empir. Softw. Eng. 28(3): 73 (2023) - [j85]Michael Weiss, André García Gómez, Paolo Tonella:
Generating and detecting true ambiguity: a forgotten danger in DNN supervision testing. Empir. Softw. Eng. 28(6): 146 (2023) - [j84]Michael Weiss, Paolo Tonella:
Uncertainty quantification for deep neural networks: An empirical comparison and usage guidelines. Softw. Test. Verification Reliab. 33(6) (2023) - [j83]Antonia Bertolino, Guglielmo De Angelis, Breno Miranda, Paolo Tonella:
In vivo test and rollback of Java applications as they are. Softw. Test. Verification Reliab. 33(7) (2023) - [j82]Tahereh Zohdinasab, Vincenzo Riccio, Alessio Gambi, Paolo Tonella:
Efficient and Effective Feature Space Exploration for Testing Deep Learning Systems. ACM Trans. Softw. Eng. Methodol. 32(2): 49:1-49:38 (2023) - [j81]Andrea Stocco, Brian Pulfer, Paolo Tonella:
Mind the Gap! A Study on the Transferability of Virtual Versus Physical-World Testing of Autonomous Driving Systems. IEEE Trans. Software Eng. 49(4): 1928-1940 (2023) - [c192]Tahereh Zohdinasab, Vincenzo Riccio, Paolo Tonella:
An Empirical Study on Low- and High-Level Explanations of Deep Learning Misbehaviours. ESEM 2023: 1-11 - [c191]Paolo Tonella:
The Road Toward Dependable AI Based Systems. ICSE 2023: 2 - [c190]Nargiz Humbatova, Gunel Jahangirova, Paolo Tonella:
DeepCrime: from Real Faults to Mutation Testing Tool for Deep Learning. ICSE Companion 2023: 68-72 - [c189]Vincenzo Riccio, Paolo Tonella:
When and Why Test Generators for Deep Learning Produce Invalid Inputs: an Empirical Study. ICSE 2023: 1161-1173 - [c188]Jinhan Kim, Nargiz Humbatova, Gunel Jahangirova, Paolo Tonella, Shin Yoo:
Repairing DNN Architecture: Are We There Yet? ICST 2023: 234-245 - [c187]Sajad Khatiri, Sebastiano Panichella, Paolo Tonella:
Simulation-based Test Case Generation for Unmanned Aerial Vehicles in the Neighborhood of Real Flights. ICST 2023: 281-292 - [c186]Tahereh Zohdinasab, Vincenzo Riccio, Paolo Tonella:
DeepAtash: Focused Test Generation for Deep Learning Systems. ISSTA 2023: 954-966 - [c185]Tahereh Zohdinasab, Vincenzo Riccio, Alessio Gambi, Paolo Tonella:
DeepHyperion: Exploring the Feature Space of Deep Learning-based Systems through Illumination Search. Software Engineering 2023: 131-132 - [e2]Satish Chandra, Kelly Blincoe, Paolo Tonella:
Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, ESEC/FSE 2023, San Francisco, CA, USA, December 3-9, 2023. ACM 2023 [contents] - [d41]Jon Ayerdi, Valerio Terragni, Gunel Jahangirova, Arrieta Arrieta, Paolo Tonella:
Replication package for "GenMorph: Automatically Generating Metamorphic Relations via Genetic Programming". Zenodo, 2023 - [d40]Michael Weiss, André García Gómez, Paolo Tonella:
Replication package for the EMSE paper "Generating and Detecting True Ambiguity: A Forgotten Danger in DNN Supervision Testing". Zenodo, 2023 - [d39]Michael Weiss, Paolo Tonella:
Simple Techniques Work Surprisingly Well for Neural Network Test Prioritization and Active Learning (Replication Paper). Version v0.1.1. Zenodo, 2023 [all versions] - [d38]Michael Weiss, Paolo Tonella:
Uncertainty-wizard: Fast and user-friendly neural network uncertainty quantification. Version v0.4.0. Zenodo, 2023 [all versions] - [d37]Tahereh Zohdinasab, Vincenzo Riccio, Paolo Tonella:
Replication Package: An Empirical Study on Low- and High-Level Explanations of Deep Learning Misbehaviours. Version v0.1.0. Zenodo, 2023 [all versions] - [d36]Tahereh Zohdinasab, Vincenzo Riccio, Paolo Tonella:
Replication Package: An Empirical Study on Low- and High-Level Explanations of Deep Learning Misbehaviours. Version v0.1.0. Zenodo, 2023 [all versions] - [d35]Tahereh Zohdinasab, Vincenzo Riccio, Paolo Tonella:
Replication Package: DeepAtash: Focused Test Generation for Deep Learning Systems. Version 1. Zenodo, 2023 [all versions] - [d34]Tahereh Zohdinasab, Vincenzo Riccio, Paolo Tonella:
Replication Package: DeepAtash: Focused Test Generation for Deep Learning Systems. Version 2. Zenodo, 2023 [all versions] - [d33]Tahereh Zohdinasab, Vincenzo Riccio, Paolo Tonella:
Replication Package: DeepAtash: Focused Test Generation for Deep Learning Systems. Version v0.1.0. Zenodo, 2023 [all versions] - [d32]Tahereh Zohdinasab, Vincenzo Riccio, Paolo Tonella:
Replication Package: DeepAtash: Focused Test Generation for Deep Learning Systems. Version v0.1.0. Zenodo, 2023 [all versions] - [d31]Tahereh Zohdinasab, Vincenzo Riccio, Paolo Tonella:
Replication Package: DeepAtash: Focused Test Generation for Deep Learning Systems. Version v0.1.0. Zenodo, 2023 [all versions] - [d30]Tahereh Zohdinasab, Vincenzo Riccio, Paolo Tonella:
Replication Package: DeepAtash: Focused Test Generation for Deep Learning Systems. Version v0.1.0. Zenodo, 2023 [all versions] - [d29]Tahereh Zohdinasab, Vincenzo Riccio, Paolo Tonella:
Replication Package: DeepAtash: Focused Test Generation for Deep Learning Systems. Version v0.1.0. Zenodo, 2023 [all versions] - [d28]Tahereh Zohdinasab, Vincenzo Riccio, Paolo Tonella:
Replication Package: DeepAtash: Focused Test Generation for Deep Learning Systems. Version v0.1.0. Zenodo, 2023 [all versions] - [d27]Tahereh Zohdinasab, Vincenzo Riccio, Paolo Tonella:
Replication Package: DeepAtash-LR: Focused Test Generation for Autonomous Driving Systems. Zenodo, 2023 - [i28]Jinhan Kim, Nargiz Humbatova, Gunel Jahangirova, Paolo Tonella, Shin Yoo:
Repairing DNN Architecture: Are We There Yet? CoRR abs/2301.11568 (2023) - [i27]Michael Weiss, Paolo Tonella:
Adopting Two Supervisors for Efficient Use of Large-Scale Remote Deep Neural Networks. CoRR abs/2304.02654 (2023) - [i26]Matteo Biagiola, Andrea Stocco, Vincenzo Riccio, Paolo Tonella:
Two is Better Than One: Digital Siblings to Improve Autonomous Driving Testing. CoRR abs/2305.08060 (2023) - [i25]Matteo Biagiola, Paolo Tonella:
Testing of Deep Reinforcement Learning Agents with Surrogate Models. CoRR abs/2305.12751 (2023) - [i24]Andrea Stocco, Alexandra Willi, Luigi Libero Lucio Starace, Matteo Biagiola, Paolo Tonella:
Neural Embeddings for Web Testing. CoRR abs/2306.07400 (2023) - [i23]Matteo Biagiola, Paolo Tonella:
Boundary State Generation for Testing and Improvement of Autonomous Driving Systems. CoRR abs/2307.10590 (2023) - [i22]Jon Ayerdi, Valerio Terragni, Gunel Jahangirova, Aitor Arrieta, Paolo Tonella:
Automatically Generating Metamorphic Relations via Genetic Programming. CoRR abs/2312.15302 (2023) - 2022
- [j80]Antonia Bertolino, Pietro Braione, Guglielmo De Angelis, Luca Gazzola, Fitsum Meshesha Kifetew, Leonardo Mariani, Matteo Orrù, Mauro Pezzè, Roberto Pietrantuono, Stefano Russo, Paolo Tonella:
A Survey of Field-based Testing Techniques. ACM Comput. Surv. 54(5): 92:1-92:39 (2022) - [j79]Andrea Stocco, Paolo Tonella:
Confidence-driven weighted retraining for predicting safety-critical failures in autonomous driving systems. J. Softw. Evol. Process. 34(10) (2022) - [j78]Andrea Romdhana, Alessio Merlo, Mariano Ceccato, Paolo Tonella:
Deep Reinforcement Learning for Black-box Testing of Android Apps. ACM Trans. Softw. Eng. Methodol. 31(4): 65:1-65:29 (2022) - [j77]Matteo Biagiola, Paolo Tonella:
Testing the Plasticity of Reinforcement Learning-based Systems. ACM Trans. Softw. Eng. Methodol. 31(4): 80:1-80:46 (2022) - [c184]Jon Ayerdi, Valerio Terragni, Aitor Arrieta, Paolo Tonella, Goiuria Sagardui, Maite Arratibel:
Evolutionary generation of metamorphic relations for cyber-physical systems. GECCO Companion 2022: 15-16 - [c183]Andrea Romdhana, Mariano Ceccato, Alessio Merlo, Paolo Tonella:
IFRIT: Focused Testing through Deep Reinforcement Learning. ICST 2022: 24-34 - [c182]Michael Weiss, Paolo Tonella:
Simple techniques work surprisingly well for neural network test prioritization and active learning (replicability study). ISSTA 2022: 139-150 - [c181]Andrea Stocco, Paulo J. Nunes, Marcelo d'Amorim, Paolo Tonella:
ThirdEye: Attention Maps for Safe Autonomous Driving Systems. ASE 2022: 102:1-102:12 - [p2]Chiara Di Francescomarino, Paolo Tonella:
The BPMN Visual Query Language and Process Querying Framework. Process Querying Methods 2022: 181-218 - [d26]Sajad Khatiri, Sebastiano Panichella, Paolo Tonella:
Replication Package: "Simulation-based Test Case Generation for Unmanned Aerial Vehicles in the Neighborhood of Real Flights". Zenodo, 2022 - [d25]Michael Weiss, Paolo Tonella:
Simple Techniques Work Surprisingly Well for Neural Network Test Prioritization and Active Learning (Replication Paper). Zenodo, 2022 - [d24]Michael Weiss, Paolo Tonella:
Simple Techniques Work Surprisingly Well for Neural Network Test Prioritization and Active Learning (Replication Paper). Version v0.1.0. Zenodo, 2022 [all versions] - [d23]Michael Weiss, Paolo Tonella:
Replication Package: Simple Techniques Work Surprisingly Well for Neural Network Test Prioritization and Active Learning. Version v0.1.0. Zenodo, 2022 [all versions] - [d22]Michael Weiss, Paolo Tonella:
Replication Package: Simple Techniques Work Surprisingly Well for Neural Network Test Prioritization and Active Learning. Version v0.1.0. Zenodo, 2022 [all versions] - [d21]Michael Weiss, Paolo Tonella:
Replication Package: Simple Techniques Work Surprisingly Well for Neural Network Test Prioritization and Active Learning. Version v0.1.0. Zenodo, 2022 [all versions] - [d20]Michael Weiss, Paolo Tonella:
Replication Package: Simple Techniques Work Surprisingly Well for Neural Network Test Prioritization and Active Learning. Version v0.1.0. Zenodo, 2022 [all versions] - [d19]Michael Weiss, Paolo Tonella:
Replication Package: Simple Techniques Work Surprisingly Well for Neural Network Test Prioritization and Active Learning. Version v0.1.0. Zenodo, 2022 [all versions] - [i21]Michael Weiss, Paolo Tonella:
Simple Techniques Work Surprisingly Well for Neural Network Test Prioritization and Active Learning (Replicability Study). CoRR abs/2205.00664 (2022) - [i20]Michael Weiss, André García Gómez, Paolo Tonella:
A Forgotten Danger in DNN Supervision Testing: Generating and Detecting True Ambiguity. CoRR abs/2207.10495 (2022) - [i19]Michael Weiss, Paolo Tonella:
Uncertainty Quantification for Deep Neural Networks: An Empirical Comparison and Usage Guidelines. CoRR abs/2212.07118 (2022) - [i18]Vincenzo Riccio, Paolo Tonella:
When and Why Test Generators for Deep Learning Produce Invalid Inputs: an Empirical Study. CoRR abs/2212.11368 (2022) - 2021
- [j76]Maurizio Leotta, Filippo Ricca, Paolo Tonella:
Sidereal: Statistical adaptive generation of robust locators for web testing. Softw. Test. Verification Reliab. 31(3) (2021) - [j75]Héctor D. Menéndez, Gunel Jahangirova, Federica Sarro, Paolo Tonella, David Clark:
Diversifying Focused Testing for Unit Testing. ACM Trans. Softw. Eng. Methodol. 30(4): 44:1-44:24 (2021) - [j74]Gunel Jahangirova, David Clark, Mark Harman, Paolo Tonella:
An Empirical Validation of Oracle Improvement. IEEE Trans. Software Eng. 47(8): 1708-1728 (2021) - [c180]Paolo Tonella:
Keynote Speaker. AITest 2021: xv - [c179]Valerio Terragni, Gunel Jahangirova, Mauro Pezzè, Paolo Tonella:
Improving assertion oracles with evolutionary computation. GECCO Companion 2021: 45-46 - [c178]Valerio Terragni, Gunel Jahangirova, Paolo Tonella, Mauro Pezzè:
GAssert: A Fully Automated Tool to Improve Assertion Oracles. ICSE (Companion Volume) 2021: 85-88 - [c177]Michael Weiss, Rwiddhi Chakraborty, Paolo Tonella:
A Review and Refinement of Surprise Adequacy. DeepTest@ICSE 2021: 17-24 - [c176]Michael Weiss, Paolo Tonella:
Fail-Safe Execution of Deep Learning based Systems through Uncertainty Monitoring. ICST 2021: 24-35 - [c175]Gunel Jahangirova, Andrea Stocco, Paolo Tonella:
Quality Metrics and Oracles for Autonomous Vehicles Testing. ICST 2021: 194-204 - [c174]Emanuele Viglianisi, Mariano Ceccato, Paolo Tonella:
Summary of: A Federated Society of Bots for Smart Contract Testing. ICST 2021: 282-283 - [c173]Andrea Romdhana, Mariano Ceccato, Gabriel Claudiu Georgiu, Alessio Merlo, Paolo Tonella:
COSMO: Code Coverage Made Easier for Android. ICST 2021: 417-423 - [c172]Michael Weiss, Paolo Tonella:
Uncertainty-Wizard: Fast and User-Friendly Neural Network Uncertainty Quantification. ICST 2021: 436-441 - [c171]Dario Olianas, Maurizio Leotta, Filippo Ricca, Matteo Biagiola, Paolo Tonella:
STILE: a Tool for Parallel Execution of E2E Web Test Scripts. ICST 2021: 460-465 - [c170]Nargiz Humbatova, Gunel Jahangirova, Paolo Tonella:
DeepCrime: mutation testing of deep learning systems based on real faults. ISSTA 2021: 67-78 - [c169]Tahereh Zohdinasab, Vincenzo Riccio, Alessio Gambi, Paolo Tonella:
DeepHyperion: exploring the feature space of deep learning-based systems through illumination search. ISSTA 2021: 79-90 - [c168]Vincenzo Riccio, Nargiz Humbatova, Gunel Jahangirova, Paolo Tonella:
DeepMetis: Augmenting a Deep Learning Test Set to Increase its Mutation Score. ASE 2021: 355-367 - [c167]Jon Ayerdi, Valerio Terragni, Aitor Arrieta, Paolo Tonella, Goiuria Sagardui, Maite Arratibel:
Generating metamorphic relations for cyber-physical systems with genetic programming: an industrial case study. ESEC/SIGSOFT FSE 2021: 1264-1274 - [d18]Nargiz Humbatova, Gunel Jahangirova, Paolo Tonella:
DeepCrime and DeepMutation++ mutations for UnityEyes and Movie Recommender Systems. Zenodo, 2021 - [d17]Nargiz Humbatova, Gunel Jahangirova, Paolo Tonella:
DeepCrime mutations for MNIST. Zenodo, 2021 - [d16]Nargiz Humbatova, Gunel Jahangirova, Paolo Tonella:
DeepCrime and DeepMutation++ mutations for MNIST. Zenodo, 2021 - [d15]Nargiz Humbatova, Gunel Jahangirova, Paolo Tonella:
DeepCrime mutations for Udacity self-driving car system. Zenodo, 2021 - [d14]Nargiz Humbatova, Gunel Jahangirova, Paolo Tonella:
DeepCrime and DeepMutation++ mutations for Udacity self-driving car system. Zenodo, 2021 - [d13]Nargiz Humbatova, Gunel Jahangirova, Paolo Tonella:
DeepCrime mutations for Speaker Recognition system. Zenodo, 2021 - [d12]Nargiz Humbatova, Gunel Jahangirova, Paolo Tonella:
DeepCrime and DeepMutation++ mutations for Speaker Recognition system. Zenodo, 2021 - [d11]Nargiz Humbatova, Gunel Jahangirova, Paolo Tonella:
Replication package for the "DeepCrime: Mutation Testing of Deep Learning Systems based on Real Faults" paper. Version 1. Zenodo, 2021 [all versions] - [d10]Nargiz Humbatova, Gunel Jahangirova, Paolo Tonella:
Replication package for the "DeepCrime: Mutation Testing of Deep Learning Systems based on Real Faults" paper. Version 2. Zenodo, 2021 [all versions] - [d9]Nargiz Humbatova, Gunel Jahangirova, Paolo Tonella:
DeepCrime: Mutation Testing of Deep Learning Systems Based on Real Faults (Tool). Zenodo, 2021 - [d8]Vincenzo Riccio, Nargiz Humbatova, Gunel Jahangirova, Paolo Tonella:
Experimental data for "DeepMetis: Augmenting a Deep Learning Test Set to Increase its Mutation Score" paper. Zenodo, 2021 - [d7]Tahereh Zohdinasab, Vincenzo Riccio, Alessio Gambi, Paolo Tonella:
Replication Package: DeepHyperion: Exploring the Feature Space of Deep Learning-Based Systems through Illumination Search. Version v0.1.0. Zenodo, 2021 [all versions] - [d6]Tahereh Zohdinasab, Vincenzo Riccio, Alessio Gambi, Paolo Tonella:
Replication Package: DeepHyperion: Exploring the Feature Space of Deep Learning-Based Systems through Illumination Search. Version v0.1.0. Zenodo, 2021 [all versions] - [i17]Michael Weiss, Paolo Tonella:
Uncertainty-Wizard: Fast and User-Friendly Neural Network Uncertainty Quantification. CoRR abs/2101.00982 (2021) - [i16]Andrea Romdhana, Alessio Merlo, Mariano Ceccato, Paolo Tonella:
Deep Reinforcement Learning for Black-Box Testing of Android Apps. CoRR abs/2101.02636 (2021) - [i15]Michael Weiss, Paolo Tonella:
Fail-Safe Execution of Deep Learning based Systems through Uncertainty Monitoring. CoRR abs/2102.00902 (2021) - [i14]Valerio Terragni, Gunel Jahangirova, Paolo Tonella, Mauro Pezzè:
GAssert: A Fully Automated Tool to Improve Assertion Oracles. CoRR abs/2103.02901 (2021) - [i13]Michael Weiss, Rwiddhi Chakraborty, Paolo Tonella:
A Review and Refinement of Surprise Adequacy. CoRR abs/2103.05939 (2021) - [i12]Tahereh Zohdinasab, Vincenzo Riccio, Alessio Gambi, Paolo Tonella:
DeepHyperion: Exploring the Feature Space of Deep Learning-Based Systems through Illumination Search. CoRR abs/2107.06997 (2021) - [i11]Vincenzo Riccio, Nargiz Humbatova, Gunel Jahangirova, Paolo Tonella:
DeepMetis: Augmenting a Deep Learning Test Set to Increase its Mutation Score. CoRR abs/2109.07514 (2021) - [i10]Andrea Stocco, Brian Pulfer, Paolo Tonella:
Mind the Gap! A Study on the Transferability of Virtual vs Physical-world Testing of Autonomous Driving Systems. CoRR abs/2112.11255 (2021) - 2020
- [j73]Alessio Viticchié, Leonardo Regano, Cataldo Basile, Marco Torchiano, Mariano Ceccato, Paolo Tonella:
Empirical assessment of the effort needed to attack programs protected with client/server code splitting. Empir. Softw. Eng. 25(1): 1-48 (2020) - [j72]Vincenzo Riccio, Gunel Jahangirova, Andrea Stocco, Nargiz Humbatova, Michael Weiss, Paolo Tonella:
Testing machine learning based systems: a systematic mapping. Empir. Softw. Eng. 25(6): 5193-5254 (2020) - [j71]Emanuele Viglianisi, Mariano Ceccato, Paolo Tonella:
A federated society of bots for smart contract testing. J. Syst. Softw. 168: 110647 (2020) - [c166]Andrea Stocco, Michael Weiss, Marco Calzana, Paolo Tonella:
Misbehaviour prediction for autonomous driving systems.