Welcome to the cutting-edge course on Quantitative Model Checking for Markov Chains! In today's technology-driven world, the demand for dependable software is unprecedented. This comprehensive course introduces you to the intricate dynamics of real-world systems through the creation of State Transition Systems, the fundamental model capturing system behavior.
Through an exploration of Discrete-time and Continuous-time Markov Chains, you will delve into powerful mathematical formalisms that elegantly model complex systems. Learn how to specify dependability properties and track the temporal evolution of Markov chains while utilizing advanced computational algorithms for verification.
Are you ready to become an expert in ensuring the reliability of tomorrow's technologies? Enroll today and join us in mastering the art and science of model checking.
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Quantitative Model Checking for Markov Chains comprises modules covering Computational Tree Logic, Discrete Time Markov Chains, Probabilistic Computational Tree Logic, Continuous Time Markov Chains, and Continuous Stochastic Logic. Dive into each module to master the art and science of model checking.
Welcome to the module on Computational Tree Logic (CTL). Gain insights into the semantics and model checking of CTL, including operators such as 'Until' and 'Always.' Test your understanding of CTL semantics and learn to formulate properties for yourself.
Delve into the world of Discrete Time Markov Chains (DTMCs) by understanding their evolution in time, transient probabilities, state classification, and steady-state computation. Test your understanding of DTMCs and their classification.
Explore Probabilistic Computational Tree Logic (PCTL) with a focus on syntax, model checking with operators such as 'Next' and 'Until,' and backwards computation. Test your understanding of PCTL and its syntax.
Discover Continuous Time Markov Chains (CTMCs) and their definition, generator matrix, steady-state probabilities, and the concept of uniformisation. Test your understanding of CTMCs, steady-state probability, and uniformisation.
Engage with Continuous Stochastic Logic (CSL) to master model checking with time-bounded next, steady-state operator, and time-bounded Until. Test your understanding of CSL and its applications in real-world scenarios.
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