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ORCIDMartin Tappler
Person information
- affiliation: TU Wien, Vienna, Austria
- affiliation: Graz University of Technology, Austria
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2020 – today
- 2024
[j10]Bernhard K. Aichernig
, Martin Tappler, Felix Wallner:
Benchmarking Combinations of Learning and Testing Algorithms for Automata Learning. Formal Aspects Comput. 36(1): 3:1-3:37 (2024)- [j9]Edi Muskardin, Martin Tappler, Bernhard K. Aichernig, Ingo Pill:
Active model learning of stochastic reactive systems (extended version). Softw. Syst. Model. 23(2): 503-524 (2024) - [j8]Bernhard K. Aichernig, Sandra König, Cristinel Mateis, Andrea Pferscher, Martin Tappler:
Learning minimal automata with recurrent neural networks. Softw. Syst. Model. 23(3): 625-655 (2024) - [c33]Edi Muskardin, Martin Tappler, Ingo Pill, Bernhard K. Aichernig, Thomas Pock:
On the Relationship Between RNN Hidden-State Vectors and Semantic Structures. ACL (Findings) 2024: 5641-5658 - [c32]Martin Tappler, Andrea Pferscher, Bernhard K. Aichernig, Bettina Könighofer:
Learning and Repair of Deep Reinforcement Learning Policies from Fuzz-Testing Data. ICSE 2024: 6:1-6:13 - [c31]Martin Tappler, Florian Lorber:
Bridging the Gap Between Models in RL: Test Models vs. Neural Networks. ICSTW 2024: 68-77 - [c30]Edi Muskardin, Tamim Burgstaller, Martin Tappler, Bernhard K. Aichernig:
Active Model Learning of Git Version Control System. ICSTW 2024: 78-82 - [c29]Martin Tappler, Edi Muskardin, Bernhard K. Aichernig, Bettina Könighofer:
Learning Environment Models with Continuous Stochastic Dynamics - with an Application to Deep RL Testing. ICST 2024: 197-208 - [c28]Stefan Pranger, Hana Chockler, Martin Tappler, Bettina Könighofer:
Test Where Decisions Matter: Importance-driven Testing for Deep Reinforcement Learning. NeurIPS 2024 - [c27]Benjamin von Berg, Bernhard K. Aichernig, Maximilian Rindler, Darko Stern, Martin Tappler:
Hierarchical Learning of Generative Automaton Models from Sequential Data. SEFM 2024: 215-233 - [i13]Stefan Pranger, Hana Chockler, Martin Tappler, Bettina Könighofer:
Test Where Decisions Matter: Importance-driven Testing for Deep Reinforcement Learning. CoRR abs/2411.07700 (2024) - 2023
- [j7]Bettina Könighofer, Julian Rudolf, Alexander Palmisano, Martin Tappler, Roderick Bloem:
Online shielding for reinforcement learning. Innov. Syst. Softw. Eng. 19(4): 379-394 (2023) - [c26]Edi Muskardin, Martin Tappler, Bernhard K. Aichernig:
Testing-based Black-box Extraction of Simple Models from RNNs and Transformers. ICGI 2023: 291-294 - [c25]Edi Muskardin, Martin Tappler, Bernhard K. Aichernig, Ingo Pill:
Reinforcement Learning Under Partial Observability Guided by Learned Environment Models. iFM 2023: 257-276 - [c24]Martin Tappler, Bernhard K. Aichernig:
Differential Safety Testing of Deep RL Agents Enabled by Automata Learning. AISoLA 2023: 138-159 - [i12]Edi Muskardin, Martin Tappler, Ingo Pill, Bernhard K. Aichernig, Thomas Pock:
On the Relationship Between RNN Hidden State Vectors and Semantic Ground Truth. CoRR abs/2306.16854 (2023) - [i11]Martin Tappler, Edi Muskardin, Bernhard K. Aichernig, Bettina Könighofer:
Learning Environment Models with Continuous Stochastic Dynamics. CoRR abs/2306.17204 (2023) - 2022
- [j6]Edi Muskardin, Bernhard K. Aichernig, Ingo Pill, Andrea Pferscher, Martin Tappler:
AALpy: an active automata learning library. Innov. Syst. Softw. Eng. 18(3): 417-426 (2022) - [c23]Luca Gazzola, Leonardo Mariani, Matteo Orrù, Mauro Pezzè, Martin Tappler:
Testing Software in Production Environments with Data from the Field. ICST 2022: 58-69 - [c22]Edi Muskardin, Bernhard K. Aichernig, Ingo Pill, Martin Tappler:
Learning Finite State Models fromRecurrent Neural Networks. IFM 2022: 229-248 - [c21]Martin Tappler, Filip Cano Córdoba, Bernhard K. Aichernig, Bettina Könighofer:
Search-Based Testing of Reinforcement Learning. IJCAI 2022: 503-510 - [c20]Martin Tappler, Stefan Pranger, Bettina Könighofer, Edi Muskardin, Roderick Bloem, Kim G. Larsen:
Automata Learning Meets Shielding. ISoLA (1) 2022: 335-359 - [c19]Martin Tappler, Bernhard K. Aichernig, Florian Lorber:
Timed Automata Learning via SMT Solving. NFM 2022: 489-507 - [c18]Bernhard K. Aichernig, Sandra König, Cristinel Mateis, Andrea Pferscher, Dominik Schmidt, Martin Tappler:
Constrained Training of Recurrent Neural Networks for Automata Learning. SEFM 2022: 155-172 - [i10]Martin Tappler, Filip Cano Córdoba, Bernhard K. Aichernig, Bettina Könighofer:
Search-Based Testing of Reinforcement Learning. CoRR abs/2205.04887 (2022) - [i9]Edi Muskardin, Martin Tappler, Bernhard K. Aichernig, Ingo Pill:
Reinforcement Learning under Partial Observability Guided by Learned Environment Models. CoRR abs/2206.11708 (2022) - [i8]Martin Tappler, Stefan Pranger, Bettina Könighofer, Edi Muskardin, Roderick Bloem, Kim G. Larsen:
Automata Learning meets Shielding. CoRR abs/2212.01838 (2022) - [i7]Bettina Könighofer, Julian Rudolf, Alexander Palmisano, Martin Tappler, Roderick Bloem:
Online Shielding for Reinforcement Learning. CoRR abs/2212.01861 (2022) - 2021
- [j5]Martin Tappler, Bernhard K. Aichernig, Giovanni Bacci, Maria Eichlseder, Kim G. Larsen:
L*-based learning of Markov decision processes (extended version). Formal Aspects Comput. 33(4-5): 575-615 (2021) - [c17]Stefan Pranger, Bettina Könighofer, Martin Tappler, Martin Deixelberger, Nils Jansen, Roderick Bloem:
Adaptive Shielding under Uncertainty. ACC 2021: 3467-3474 - [c16]Edi Muskardin, Bernhard K. Aichernig, Ingo Pill, Andrea Pferscher, Martin Tappler:
AALpy: An Active Automata Learning Library. ATVA 2021: 67-73 - [c15]Bettina Könighofer, Julian Rudolf, Alexander Palmisano, Martin Tappler, Roderick Bloem:
Online Shielding for Stochastic Systems. NFM 2021: 231-248 - [c14]Martin Tappler, Edi Muskardin, Bernhard K. Aichernig, Ingo Pill:
Active Model Learning of Stochastic Reactive Systems. SEFM 2021: 481-500 - [c13]Noura El Moussa, Davide Molinelli, Mauro Pezzè, Martin Tappler:
Health of smart ecosystems. ESEC/SIGSOFT FSE 2021: 1491-1494 - 2020
- [c12]Bernhard K. Aichernig, Andrea Pferscher, Martin Tappler:
From Passive to Active: Learning Timed Automata Efficiently. NFM 2020: 1-19 - [c11]Bernhard K. Aichernig, Martin Tappler, Felix Wallner:
Benchmarking Combinations of Learning and Testing Algorithms for Active Automata Learning. TAP@STAF 2020: 3-22 - [i6]Stefan Pranger, Bettina Könighofer, Martin Tappler, Martin Deixelberger, Nils Jansen, Roderick Bloem:
Adaptive Shielding under Uncertainty. CoRR abs/2010.03842 (2020) - [i5]Bettina Könighofer, Julian Rudolf, Alexander Palmisano, Martin Tappler, Roderick Bloem:
Online Shielding for Stochastic Systems. CoRR abs/2012.09539 (2020)
2010 – 2019
- 2019
- [j4]Bernhard K. Aichernig, Martin Tappler:
Probabilistic black-box reachability checking (extended version). Formal Methods Syst. Des. 54(3): 416-448 (2019) - [j3]Bernhard K. Aichernig, Martin Tappler:
Efficient Active Automata Learning via Mutation Testing. J. Autom. Reason. 63(4): 1103-1134 (2019) - [c10]Martin Tappler, Bernhard K. Aichernig, Giovanni Bacci, Maria Eichlseder, Kim G. Larsen:
L*-Based Learning of Markov Decision Processes. FM 2019: 651-669 - [c9]Martin Tappler, Bernhard K. Aichernig, Kim Guldstrand Larsen, Florian Lorber:
Time to Learn - Learning Timed Automata from Tests. FORMATS 2019: 216-235 - [c8]Bernhard K. Aichernig, Roderick Bloem, Masoud Ebrahimi, Martin Horn, Franz Pernkopf, Wolfgang Roth, Astrid Rupp, Martin Tappler, Markus Tranninger:
Learning a Behavior Model of Hybrid Systems Through Combining Model-Based Testing and Machine Learning. ICTSS 2019: 3-21 - [i4]Martin Tappler, Bernhard K. Aichernig, Roderick Bloem:
Model-Based Testing IoT Communication via Active Automata Learning. CoRR abs/1904.07075 (2019) - [i3]Martin Tappler, Bernhard K. Aichernig, Giovanni Bacci, Maria Eichlseder, Kim G. Larsen:
L*-Based Learning of Markov Decision Processes (Extended Version). CoRR abs/1906.12239 (2019) - [i2]Bernhard K. Aichernig, Roderick Bloem, Masoud Ebrahimi, Martin Horn, Franz Pernkopf, Wolfgang Roth, Astrid Rupp, Martin Tappler, Markus Tranninger:
Learning a Behavior Model of Hybrid Systems Through Combining Model-Based Testing and Machine Learning (Full Version). CoRR abs/1907.04708 (2019) - 2018
- [c7]Bernhard K. Aichernig, Wojciech Mostowski, Mohammad Reza Mousavi, Martin Tappler, Masoumeh Taromirad:
Model Learning and Model-Based Testing. Machine Learning for Dynamic Software Analysis 2018: 74-100 - [c6]Bernhard K. Aichernig, Roderick Bloem, Masoud Ebrahimi, Martin Tappler, Johannes Winter:
Automata Learning for Symbolic Execution. FMCAD 2018: 1-9 - [i1]Martin Tappler, Bernhard K. Aichernig, Kim Guldstrand Larsen, Florian Lorber:
Learning Timed Automata via Genetic Programming. CoRR abs/1808.07744 (2018) - 2017
- [j2]Bernhard Großwindhager, Astrid Rupp, Martin Tappler, Markus Tranninger, Samuel Weiser, Bernhard K. Aichernig, Carlo Alberto Boano, Martin Horn, Gernot Kubin, Stefan Mangard, Martin Steinberger, Kay Römer:
Dependable Internet of Things for Networked Cars. Int. J. Comput. 16: 226-237 (2017) - [c5]Martin Tappler, Bernhard K. Aichernig, Roderick Bloem:
Model-Based Testing IoT Communication via Active Automata Learning. ICST 2017: 276-287 - [c4]Bernhard K. Aichernig, Martin Tappler:
Learning from Faults: Mutation Testing in Active Automata Learning. NFM 2017: 19-34 - [c3]Bernhard K. Aichernig, Martin Tappler:
Probabilistic Black-Box Reachability Checking. RV 2017: 50-67 - 2016
- [j1]Bernhard K. Aichernig, Elisabeth Jöbstl, Martin Tappler:
Does this fault lead to failure? Combining refinement and input-output conformance checking in fault-oriented test-case generation. J. Log. Algebraic Methods Program. 85(5): 806-823 (2016) - [c2]Bernhard K. Aichernig, Florian Lorber, Martin Tappler:
Conformance Checking of Real-Time Models - Symbolic Execution vs. Bounded Model Checking. Theory and Practice of Formal Methods 2016: 15-32 - 2015
- [c1]Bernhard K. Aichernig, Martin Tappler:
Symbolic Input-Output Conformance Checking for Model-Based Mutation Testing. USE@FM 2015: 3-19
Coauthor Index
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