Mutating Skeletons: Learning Timed Automata via Domain Knowledge

Created by W.Langdon from gp-bibliography.bib Revision:1.8344

@InProceedings{Wallner:2025:ICSTW,

• author = "Felix Wallner and Bernhard K. Aichernig and Florian Lorber and Martin Tappler",
• title = "Mutating Skeletons: Learning Timed Automata via Domain Knowledge",
• booktitle = "2025 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW)",
• year = "2025",
• pages = "67--77",
• month = mar,
• keywords = "genetic algorithms, genetic programming, Software testing, Runtime, Learning automata, Model checking, Skeleton, Reflection, Real-time systems, Timing, Formal verification, model-learning, timed automata, domain knowledge",
• ISSN = "2159-4848",
• DOI = "doi:10.1109/ICSTW64639.2025.10962513",
• abstract = "Formal verification techniques, such as model checking, can provide valuable insights and guarantees for (safety-critical) devices and their possible behaviour. However, these guarantees only hold true as long as the model correctly reflects the system. Automata learning provides a huge advantage there as it enables not only the automatic creation of the needed models but also ensures their correct reflection of the system behaviour. However, and this holds especially true for real-time systems, model learning techniques can become very time consuming. To combat this, we show how to integrate given domain knowledge into an existing approach based on genetic programming to speed up the learning process. In particular, we show how the genetic programming approach can take a (possibly abstracted, incomplete or incorrect) untimed skeleton of an automaton, which can often be obtained very cheaply, and augment it with timing behaviour to form timed automata in a fast and efficient manner. We demonstrate the approach on several examples of varying sizes.",
• notes = "Also known as \cite{10962513}",

}

Genetic Programming entries for Felix Wallner Bernhard K Aichernig Florian Lorber Martin Tappler

Citations