Foundations of Quantitative Model Checking

In systems where failure is not an option, how can you be certain your design is correct? Move beyond traditional testing and learn to mathematically prove the reliability and performance of your systems. This course provides a practical introduction to quantitative model checking. You will learn to model complex systems as state transition systems and Markov chains, write formal specifications using temporal logic, and analyze probabilistic and real-time properties to identify potential design flaws before they become critical failures. What you'll learn: - Understand the core principles of model checking and formal verification. - Learn to represent system behavior using state transition systems and Markov chains. - Write precise system properties and requirements using probabilistic temporal logic (PCTL). - Apply model checking algorithms to analyze system properties like reachability and expected rewards. - Practice modeling common problems, such as communication protocols and resource allocation systems. - Interpret the results of quantitative analysis to make informed decisions about system safety and performance. The course begins with the fundamental concepts of system modeling and formal logic, then progresses to techniques for specifying and verifying quantitative properties of probabilistic systems. This course is designed for software engineers, systems designers, and computer science students. No prior experience in formal methods is required to get started. Start learning to build verifiably correct systems today.