For background information on the topic as a whole, scroll to the end of this page.
Available Project Proposals
If you are interested in the general topic of Quantitative Verification, or if you have your own project idea related to the topic, please contact us directly. Alternatively, you can also work on one of the following concrete project proposals in various subfields of quantitative analysis:
Modelling Language Technology
Modelling languages are similar to programming languages, yet different. We offer topics related to various aspects of our modelling language compilers.
Probabilistic Verification
Probabilistic model checking and statistical model checking compute optimal probabilities, expected values, and strategies for Markov models. You can implement new algorithms, combinations of methods, or improve performance.
(Probabilistic) Timed Automata
Timed automata are an established way to model hard real-time systems. Probabilistic timed automata capture the combination of randomisation and real-time behaviour.
Other Topics
Background
Probability is everywhere in our daily lives and IT systems: as games of chance, as random events like device failures, or in randomised algorithms. Other systems show time-dependent behaviour or need to satisfy real-time requirements. Sometimes, timing and probabilities are intertwined, like in communication protocols, or we even need to consider quantities evolving according to physical laws such as a room's temperature or the water level in a buffer tank.
In FMT, we work with (extensions of) Markov chains, Markov decision processes, stochastic games, and timed automata to model such systems. We model real-life systems with UPPAAL, use fault trees as a graphical tool to think about failure probabilities, and develop the Modest Toolset to create, simulate, and verify formal models that include probabilities and timing.
We offer B.Sc. research projects related to probabilistic, timed, and hybrid verification topics: on case studies, modelling language and compiler improvements, algorithms for model checking and simulation, and connections with other languages or tools.
Prerequisites
- Basic probability theory and statistics (for probabilistic topics)
- Object-oriented programming experience
Related Modules
- Discrete Structures and Algorithms (automata and graph algorithms)
- Cyber-Physical Systems (modelling and verification with UPPAAL)
- Programming Paradigms (compiler construction)












