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Quantitative Model Checking
Ernst Moritz Hahn (instructor)
Vahid Hashemi (assistant)
This advanced course addresses Bachelor and Master students in Computer Science, Bioinformatics, CuK or Computerlinguistics. Background in probability theory and the module Verification are of advantage but not mandatory.
Quantitative model checking is concerned with quantities (mostly probabilities) within systems exhibiting random behaviour. Such systems include networked, embedded, or biological systems. Their underlying semantics are usually discrete-time and/or continuous-time Markov chains, possibly extended with nondeterminism. On the respective models, quantitative properties of interest can be verified. The properties can be specified, e.g., by PCTL or LTL for discrete-time models, and CSL for continuous-time models. This course aims to cover both the model construction and the verification techniques for these systems.
Credits: 6 ECTS points (2 hours of lecture, 2 hours of tutorials, and some exercises every week)
When and where?
Lectures: first lecture on Wednesday 14 - 16, April 19, 2017 in the seminar room U12 in E1 1,
afterwards every Monday 8 - 10 in the seminar room 016 in E1 3, starting on April 24, 2017.
Tutorials: every Wednesday 14 - 16 in the seminar room U12 in E1 1 (subject to change), starting on April 26, 2017
The dates for the exams will be announced.
Having at least 50% points for both theoretical and practical exercises is required for admission to the final exam. Your current point status will be made available in dCMS.
- Model Checking
- Probability Theory
- Stochastic Processes
- Discrete-Time Markov Chains (DTMC)
- Probabilistic Computation Tree Logic (PCTL)
- Model Checking DTMC
- Probabilistic Bisimulation (DTMC)
- Continuous-time Markov Chains (CTMC)
- Continuous Stochastic Logic (CSL)
- Model Checking CTMC
- Probabilistic Bisimulation (CTMC)
- Logical Characterization
- Non-Determinism and Markov Decision Processes (MDP)
- Model Checking MDP
- Bisimulation and Logical Characterization (MDP)