Scalable enumeration of trap spaces in boolean networks via answer set programming
G. Trinh, B. Benhamou, S. Pastva, S. Soliman, in:, Proceedings of the 38th AAAI Conference on Artificial Intelligence, Association for the Advancement of Artificial Intelligence, 2024, pp. 10714–10722.

Bubaak: Runtime monitoring of program verifiers
M. Chalupa, T.A. Henzinger, in:, Tools and Algorithms for the Construction and Analysis of Systems, Springer Nature, 2023, pp. 535–540.

Vamos: Middleware for best-effort third-party monitoring
M. Chalupa, F. Mühlböck, S. Muroya Lei, T.A. Henzinger, in:, Fundamental Approaches to Software Engineering, Springer Nature, 2023, pp. 260–281.

VAMOS: Middleware for Best-Effort Third-Party Monitoring
M. Chalupa, F. Mühlböck, S. Muroya Lei, T.A. Henzinger, VAMOS: Middleware for Best-Effort Third-Party Monitoring, Institute of Science and Technology Austria, 2023.

A learner-verifier framework for neural network controllers and certificates of stochastic systems
K. Chatterjee, T.A. Henzinger, M. Lechner, D. Zikelic, in:, Tools and Algorithms for the Construction and Analysis of Systems , Springer Nature, 2023, pp. 3–25.

Computing adequately permissive assumptions for synthesis
A. Anand, K. Mallik, S.P. Nayak, A.K. Schmuck, in:, TACAS 2023: Tools and Algorithms for the Construction and Analysis of Systems, Springer Nature, 2023, pp. 211–228.

Quantitative safety and liveness
T.A. Henzinger, N.A. Mazzocchi, N.E. Sarac, in:, 26th International Conference Foundations of Software Science and Computation Structures, Springer Nature, 2023, pp. 349–370.

Regular methods for operator precedence languages
T.A. Henzinger, P. Kebis, N.A. Mazzocchi, N.E. Sarac, in:, 50th International Colloquium on Automata, Languages, and Programming, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2023, p. 129:1--129:20.

Revisiting the adversarial robustness-accuracy tradeoff in robot learning
M. Lechner, A. Amini, D. Rus, T.A. Henzinger, IEEE Robotics and Automation Letters 8 (2023) 1595–1602.

Boolean network sketches: A unifying framework for logical model inference
N. Benes, L. Brim, O. Huvar, S. Pastva, D. Safránek, Bioinformatics 39 (2023).