The Automated Reasoning: Symbolic Model Checking course delves into the automatic verification of system and program properties. Through the study of transition systems, students learn to describe properties such as reachability in CTL. Symbolic model checking is explored as a solution for managing large state spaces, with a focus on representing sets of states with binary decision diagrams (BDDs).
The course is structured into four modules, each delivering crucial knowledge and practical examples. In Module 1, the fundamentals of CTL model checking are covered, while Module 2 and Module 3 delve into the intricacies of BDDs. Finally, Module 4 focuses on BDD-based symbolic model checking, providing real-world examples and problem-solving scenarios.
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Uncover the intricacies of automated reasoning and symbolic model checking through four comprehensive modules, each focusing on crucial concepts and practical examples.
The first module provides a comprehensive introduction to CTL model checking, covering topics such as the size of state space and CTL equivalence. Students will gain a deep understanding of the computation tree logic and its application in system verification.
Module 2 delves into the representation of Boolean functions and decision trees, paving the way for an in-depth exploration of binary decision diagrams (BDDs). Students will learn about reduced ordered decision trees and their significance in symbolic model checking.
In Module 3, students will explore BDD examples and algorithms, along with engaging in quizzes to test their knowledge. This module offers a comprehensive understanding of BDDs and their application in symbolic model checking.
The final module focuses on BDD-based symbolic model checking, providing real-world examples of its application. Students will engage in problem-solving scenarios related to network deadlock checking, packet switching networks, and more.
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