Automated Reasoning: Symbolic Model Checking

EIT Digital via Coursera

Go to Course: https://www.coursera.org/learn/automated-reasoning-symbolic-model-checking

Introduction

# Course Review: Automated Reasoning: Symbolic Model Checking **Platform:** Coursera **Instructor:** [Instructor Name] **Duration:** 4 weeks **Level:** Intermediate If you are keen on understanding the complexities of automated reasoning and want to dive deep into the verification of systems and programs, the "Automated Reasoning: Symbolic Model Checking" course on Coursera is an excellent choice. This course stands out for its thorough approach to one of the more intricate topics in computer science. ## Overview The course centers around the notion of transition systems, which are pivotal in modelling the behavior of dynamic systems through states and transitions. It delves into Computation Tree Logic (CTL), which provides a framework for expressing properties regarding these systems. The heart of the course lies in symbolic model checking — a technique that helps manage large state spaces effectively by representing sets of states symbolically. This innovative approach is vital for verifying whether specific properties, such as reachability, hold in systems, making it a critical area of study for developers, researchers, and engineers alike. ## Syllabus Breakdown 1. **CTL Model Checking** - The course kicks off with a clear introduction to model checking, emphasizing the necessity of verifying system properties. The module discusses Computation Tree Logic (CTL) and its role in describing properties of transition systems. An abstract algorithm is explored to determine whether a given property is satisfied, introducing students to fundamental concepts without overwhelming details. 2. **BDDs Part 1** - The focus shifts to Binary Decision Diagrams (BDDs), which act as efficient representations of Boolean functions. This module explains decision trees and how BDDs optimize them through the concept of sharing. The uniqueness of BDD representations is explored, laying the groundwork needed for symbolic model checking. 3. **BDDs Part 2** - Following the foundational concepts, this module illustrates the practical computations involved in deriving Reduced Ordered Binary Decision Diagrams (ROBDDs) from propositional formulas. This part of the syllabus solidifies your understanding of BDDs and prepares you for their application in model checking. 4. **BDD Based Symbolic Model Checking** - The final module is where everything comes together. It demonstrates how to leverage BDDs for symbolic model checking, enhancing your ability to handle much larger state spaces compared to traditional explicit state-based techniques. Through various examples, the module effectively illustrates real-world applications of CTL and BDDs. ## Positives of the Course - **Comprehensive Content:** The course is well-structured, logically progressing from fundamental concepts to advanced techniques. The instructor’s clear explanations help demystify complex topics. - **Hands-On Learning:** The inclusion of numerous examples throughout ensures that theoretical understanding is paired with practical application, helping learners to visualize how symbolic model checking works in practice. - **Interactive Format:** Coursera’s platform provides an interactive learning environment, allowing you to engage with fellow students and discuss various problems. - **Self-Paced:** The course is flexible, allowing you to learn at your own pace, which is advantageous for busy professionals or students. ## Recommendations I highly recommend the "Automated Reasoning: Symbolic Model Checking" course to anyone interested in formal methods, programming verification, or automating reasoning systems. Whether you are a graduate student, a software engineer, or a researcher, this course equips you with invaluable tools and techniques that can significantly enhance your work in system verification. By the end of this course, you will not only understand the theoretical underpinnings of model checking and BDDs but also gain practical skills applicable in various domains, such as software development, automated testing, and systems engineering. In conclusion, if you are looking to bolster your understanding and capability in automated reasoning, look no further. Enroll in this Coursera course today to unlock the potential of symbolic model checking!

Syllabus

CTL model checking

After a general introduction to the MOOC, this module starts by a general description of model checking.Then Computation Tree Logic (CTL) is introduced: a language in which properties on transition systems can be described. The algorithm to check whether such a property holds is given in an abstract setting, leaving implicit how sets of states are represented.

BDDs part 1

In this module BDDs (binary decision diagrams) are introduced as decision trees with sharing. They represent boolean functions. Extra requirements on both decision trees and BDDs are presented from which uniqueness of the representation can be concluded.

BDDs part 2

After some examples of BDD, the algorithm is presented and discussed to compute the ROBDD of any propositional formula.

BDD based symbolic model checking

In this last module the topics of CTL model checking and BDDs are combined: it is shown how BDDs can be used to represent sets of states in a way that the abstract algorithm for CTL mode checking can be used, and much larger state spaces can be dealt with than by using explicit state based model checking. Sever examples are presented.