PSY-TaLiRo: A Python Toolbox for Search-Based Test Generation for Cyber-Physical Systems
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Abstract (arXiv)
In this paper, we present the Python package PSY-TaLiRo which is a toolbox for temporal logic robustness guided falsification of Cyber-Physical Systems (CPS). PSY-TaLiRo is a completely modular toolbox supporting multiple temporal logic offline monitors as well as optimization engines for test case generation. Among the benefits of PSY-TaLiRo is that it supports search-based test generation for many different types of systems under test. All PSY-TaLiRo modules can be fully modified by the users to support new optimization and robustness computation engines as well as any System under Test (SUT).
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 Jun 2021.
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Citing papers per year: 2021: 1; 2022: 0; 2023: 1; 2024: 2; 2025: 1.
5 papers.
- 2021Part-X: A Family of Stochastic Algorithms for Search-Based Test Generation with Probabilistic Guaranteescited by 6
- 2023Requirement falsification for cyber-physical systems using generative modelscited by 3
- 2024Tolerance of Reinforcement Learning Controllers against Deviations in Cyber Physical Systemscited by 1
- 2024Learning test generators for cyber-physical systemscited by 0
- 2025Data-Driven Falsification of Cyber-Physical Systemscited by 0
- 2025Data-Driven Falsification of Cyber-Physical Systems6 May 2025
- 2024Learning test generators for cyber-physical systems4 Oct 2024
- 2024Tolerance of Reinforcement Learning Controllers against Deviations in Cyber Physical Systems24 Jun 2024
- 2023Requirement falsification for cyber-physical systems using generative models31 Oct 2023
- 2021Part-X: A Family of Stochastic Algorithms for Search-Based Test Generation with Probabilistic Guarantees20 Oct 2021