CatIO - A Framework for Model-Based Diagnosis of Cyber-Physical Systems. - Edi Muskardin; Ingo Pill; Franz Wotawa (ISMIS, 2020)

Learning-Based Fuzzing of IoT Message Brokers. - Bernhard K. Aichernig; Edi Muskardin; Andrea Pferscher (ICST, 2021)

Active Model Learning of Stochastic Reactive Systems. - Martin Tappler; Edi Muskardin; Bernhard K. Aichernig; Ingo Pill (SEFM, 2021)

Learning Finite State Models fromRecurrent Neural Networks. - Edi Muskardin; Bernhard K. Aichernig; Ingo Pill; Martin Tappler (IFM, 2022)

Automata Learning Meets Shielding. - Martin Tappler; Stefan Pranger; Bettina Könighofer; Edi Muskardin; Roderick Bloem; Kim G. Larsen (ISoLA (1), 2022)

Active vs. Passive: A Comparison of Automata Learning Paradigms for Network Protocols. - Bernhard K. Aichernig; Edi Muskardin; Andrea Pferscher (FMAS/ASYDE@SEFM, 2022)

AALpy: an active automata learning library. - Edi Muskardin; Bernhard K. Aichernig; Ingo Pill; Andrea Pferscher; Martin Tappler (Innov. Syst. Softw. Eng., 2022)

Mining Digital Twins of a VPN Server. - Andrea Pferscher; Benjamin Wunderling; Bernhard K. Aichernig; Edi Muskardin (FMDT@FM, 2023)

Testing-based Black-box Extraction of Simple Models from RNNs and Transformers. - Edi Muskardin; Martin Tappler; Bernhard K. Aichernig (ICGI, 2023)

Reinforcement Learning Under Partial Observability Guided by Learned Environment Models. - Edi Muskardin; Martin Tappler; Bernhard K. Aichernig; Ingo Pill (iFM, 2023)

On the Relationship Between RNN Hidden State Vectors and Semantic Ground Truth. - Edi Muskardin; Martin Tappler; Ingo Pill; Bernhard K. Aichernig; Thomas Pock (CoRR, 2023)

Learning Environment Models with Continuous Stochastic Dynamics. - Martin Tappler; Edi Muskardin; Bernhard K. Aichernig; Bettina Könighofer (CoRR, 2023)

On the Relationship Between RNN Hidden-State Vectors and Semantic Structures. - Edi Muskardin; Martin Tappler; Ingo Pill; Bernhard K. Aichernig; Thomas Pock (ACL (Findings), 2024)

Active Model Learning of Git Version Control System. - Edi Muskardin; Tamim Burgstaller; Martin Tappler; Bernhard K. Aichernig (ICSTW, 2024)

Learning Environment Models with Continuous Stochastic Dynamics - with an Application to Deep RL Testing. - Martin Tappler; Edi Muskardin; Bernhard K. Aichernig; Bettina Könighofer (ICST, 2024)

Active model learning of stochastic reactive systems (extended version). - Edi Muskardin; Martin Tappler; Bernhard K. Aichernig; Ingo Pill (Softw. Syst. Model., 2024)