| Reinforcement learning for automatic test case prioritization and selection in continuous integration H Spieker, A Gotlieb, D Marijan, M Mossige Proceedings of the 26th ACM SIGSOFT International Symposium on Software …, 2017 | 296 | 2017 |
| A fine-grained data set and analysis of tangling in bug fixing commits S Herbold, A Trautsch, B Ledel, A Aghamohammadi, TA Ghaleb, ... Empirical Software Engineering 27 (6), 125, 2022 | 51* | 2022 |
| Adaptive metamorphic testing with contextual bandits H Spieker, A Gotlieb Journal of Systems and Software 165, 110574, 2020 | 28 | 2020 |
| Geqca: Generic qualitative constraint acquisition MB Belaid, N Belmecheri, A Gotlieb, N Lazaar, H Spieker Proceedings of the AAAI Conference on Artificial Intelligence 36 (4), 3690-3697, 2022 | 15 | 2022 |
| Multi-stage evolution of single-and multi-objective MCLP: Successive placement of charging stations H Spieker, A Hagg, A Gaier, S Meilinger, A Asteroth Soft Computing 21, 4859-4872, 2017 | 15 | 2017 |
| Time-aware test case execution scheduling for cyber-physical systems M Mossige, A Gotlieb, H Spieker, H Meling, M Carlsson Principles and Practice of Constraint Programming: 23rd International …, 2017 | 12 | 2017 |
| Towards testing of deep learning systems with training set reduction H Spieker, A Gotlieb arXiv preprint arXiv:1901.04169, 2019 | 10 | 2019 |
| Testing deep learning models: a first comparative study of multiple testing techniques MK Ahuja, A Gotlieb, H Spieker 2022 IEEE International Conference on Software Testing, Verification and …, 2022 | 8 | 2022 |
| Opening the software engineering toolbox for the assessment of trustworthy AI MK Ahuja, MB Belaid, P Bernabé, M Collet, A Gotlieb, C Lal, D Marijan, ... arXiv preprint arXiv:2007.07768, 2020 | 8 | 2020 |
| Constraint-guided reinforcement learning: Augmenting the agent-environment-interaction H Spieker 2021 International Joint Conference on Neural Networks (IJCNN), 1-8, 2021 | 6 | 2021 |
| Testing Industrial Robotic Systems: A New Battlefield! A Gotlieb, D Marijan, H Spieker Software Engineering for Robotics, 109-137, 2021 | 6 | 2021 |
| Detecting Intentional AIS Shutdown in Open Sea Maritime Surveillance Using Self-Supervised Deep Learning P Bernabé, A Gotlieb, B Legeard, D Marijan, FO Sem-Jacobsen, ... IEEE Transactions on Intelligent Transportation Systems, 2023 | 4 | 2023 |
| Learning objective boundaries for constraint optimization problems H Spieker, A Gotlieb Machine Learning, Optimization, and Data Science: 6th International …, 2020 | 4 | 2020 |
| Rotational diversity in multi-cycle assignment problems H Spieker, A Gotlieb, M Mossige Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 7724-7731, 2019 | 3 | 2019 |
| Methodische Grundlegung für eine Strategie zum sukzessiven Ausbau der Ladeinfrastruktur für Elektromobilität in Bonn und dem Rhein-Sieg-Kreis: Studie zur Strategie für den … A Hagg, H Spieker, A Oslislo, V Jacobs, A Asteroth, S Meilinger | 3 | 2015 |
| Probabilistic model checking of stochastic reinforcement learning policies D Gross, H Spieker arXiv preprint arXiv:2403.18725, 2024 | 2 | 2024 |
| A Review of Validation and Verification of Neural Network-based Policies for Sequential Decision Making Q Mazouni, H Spieker, A Gotlieb, M Acher arXiv preprint arXiv:2312.09680, 2023 | 2 | 2023 |
| Successive evolution of charging station placement H Spieker, A Hagg, A Asteroth, S Meilinger, V Jacobs, A Oslislo 2015 International Symposium on Innovations in Intelligent SysTems and …, 2015 | 2 | 2015 |
| Safety-Oriented Pruning and Interpretation of Reinforcement Learning Policies D Gross, H Spieker arXiv preprint arXiv:2409.10218, 2024 | 1 | 2024 |
| Enhancing Manufacturing Quality Prediction Models through the Integration of Explainability Methods D Gross, H Spieker, A Gotlieb, R Knoblauch arXiv preprint arXiv:2403.18731, 2024 | 1 | 2024 |
Arnaud GotliebSimula Research LaboratoryVerified email at simula.no
