System Validation (2): Model process behaviour (Coursera)

Offered by EIT Digital,
System Validation (2): Model process behaviour (Coursera)

System Validation is the field that studies the fundamentals of system communication and information processing. It is the next logical step in computer science and improving software development in general. It allows automated analysis based on behavioural models of a system to see if a system works correctly. We want to guarantee that the systems does exactly what it is supposed to do.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

The techniques put forward in system validaton allow to prove the absence of errors. It allows to design embedded system behaviour that is structurally sound and as a side effect enforces you to make the behaviour simple and insightful. This means that the systems are not only behaving correctly, but are also much easier to maintain and adapt. ’Model process behaviour' is the follow up MOOC to 'Automata and behavioural equivalences'. This MOOC shows you how to model process behaviour, in particular protocols and distributed algorithms, dive deeper in the properties of system behaviour, and keep things simple to avoid a state space explosion.
Suggested Readings: J.F. Groote and M.R. Mousavi. Modeling and analysis of communicating systems. The MIT Press, 2014.
This course is part 2 of the set of courses for System Validation. System Validation, as a set of courses, is part of a larger EIT Digital online programme called 'Internet of Things through Embedded Systems'.

Syllabus

WEEK 1: Sequential behaviour
WEEK 2: Data types
WEEK 3: Parallel behaviour

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Python Data Representations (Coursera) Coursera
Rice University

Python Data Representations (Coursera)

This course will continue the introduction to Python programming that started with Python Programming Essentials. We'll learn about different data representations, including strings, lists, and tuples, that form the core of all Python programs. We will also teach you how to access files, which will allow you to store and retrieve data within your programs. These concepts and skills will help you to manipulate data and write more complex Python programs.

Jun 1st 2026
4 Weeks
Mastering the Software Engineering Interview (Coursera) Coursera
University of California, San Diego

Mastering the Software Engineering Interview (Coursera)

You’ve hit a major milestone as a computer scientist and are becoming a capable programmer. You now know how to solve problems, write algorithms, and analyze solutions; and you have a wealth of tools (like data structures) at your disposal. You may now be ready for an internship or (possibly) an entry-level software engineering job. But can you land the internship/job? It depends in part on how well you can solve new technical problems and communicate during interviews. How can you get better at this? Practice!

Jun 1st 2026
4 Weeks
The R Programming Environment (Coursera) Coursera
Johns Hopkins University

The R Programming Environment (Coursera)

This course provides a rigorous introduction to the R programming language, with a particular focus on using R for software development in a data science setting. Whether you are part of a data science team or working individually within a community of developers, this course will give you the knowledge of R needed to make useful contributions in those settings.

Jun 1st 2026
4 Weeks
Introduction to Graph Theory (Coursera) Coursera
University of California, San Diego,Higher School of Economics - HSE University

Introduction to Graph Theory (Coursera)

We invite you to a fascinating journey into Graph Theory — an area which connects the elegance of painting and the rigor of mathematics; is simple, but not unsophisticated. Graph Theory gives us, both an easy way to pictorially represent many major mathematical results, and insights into the deep theories behind them. In this course, among other intriguing applications, we will see how GPS systems find shortest routes, how engineers design integrated circuits, how biologists assemble genomes, why a political map can always be colored using a few colors. We will study Ramsey Theory which proves that in a large system, complete disorder is impossible!

Jun 1st 2026
5-12 Weeks
Problem Solving, Python Programming, and Video Games (Coursera) Coursera
University of Alberta

Problem Solving, Python Programming, and Video Games (Coursera)

This course is an introduction to computer science and programming in Python. Important computer science concepts such as problem solving (computational thinking), problem decomposition, algorithms, abstraction, and software quality are emphasized throughout. The Python programming language and video games are used to demonstrate computer science concepts in a concrete and fun manner. However, a learner can take the knowledge and skills from this course and apply them to non-game problems, other programming languages, and other computer science courses.

Jun 1st 2026
5-12 Weeks
Continuous Integration (Coursera) Coursera
University of California, Davis

Continuous Integration (Coursera)

In today's world, software development is highly complex and often has large teams of developers working on small pieces of a larger software project. This course will go over the basic principles of using a continuous integration system effectively to constantly improve software. We're going to describe the different stations of continuous test, build, integration and deploy processes required for DevOps practices and apply best practices for quality software management, and tooling to accomplish iterative software build & test processes.

Jun 1st 2026
4 Weeks
Integrating Test-Driven Development into Your Workflow (Coursera) Coursera
LearnQuest

Integrating Test-Driven Development into Your Workflow (Coursera)

In this course we will discuss how to integrate best practices of test-driven development into your programming workflow. We will start out by discussing how to refactor legacy codebases with the help of agile methodologies. Then, we will explore continuous integration and how to write automated tests in Python. Finally, we will work everything we've learned together to write code that contains error handlers, automated tests, and refactored functions.

Jun 1st 2026
4 Weeks
Advanced Deployment Scenarios with TensorFlow (Coursera) Coursera
DeepLearning.AI

Advanced Deployment Scenarios with TensorFlow (Coursera)

Bringing a machine learning model into the real world involves a lot more than just modeling. This Specialization will teach you how to navigate various deployment scenarios and use data more effectively to train your model. In this final course, you’ll explore four different scenarios you’ll encounter when deploying models.

Jun 1st 2026
4 Weeks
Test-Driven Development Overview (Coursera) Coursera
LearnQuest

Test-Driven Development Overview (Coursera)

In this introductory course you will get both a full overview of what TDD is, when it can and can't be applied, and what its benefits are for practitioners and organizations. You will also have the opportunity to get hands on with a few fun introductory projects where you can apply what you have learned and experience the benefits of this approach to problem solving yourself.

Jun 1st 2026
4 Weeks
Capstone Project: Teaching Impacts of Technology (Coursera) Coursera
University of California, San Diego

Capstone Project: Teaching Impacts of Technology (Coursera)

In this project-based course you’ll review the Advanced Placement Computer Science Principles course and exam description guide to prepare for the “Explore Task”, where students must research a recent computing innovation and and analyze its impacts on the world. You’ll also review the description of this task from the student perspective and complete the task yourself. Then you’ll assess sample secondary student work by following the APCSP scoring guidelines as well as provide feedback to a fellow learner on their submitted task and receive the same from fellow learners.

Jun 3rd 2026
5-12 Weeks
SRS Documents: Requirements and Diagrammatic Notations (Coursera) Coursera
University of Colorado System

SRS Documents: Requirements and Diagrammatic Notations (Coursera)

As requirements are being gathered and prioritized, they also need to be documented. In Diagrammatic Notations and Software Requirements Specification Writing, we discuss and practice the process of turning requirements into something readable to the customers at a high level, and the developers. When a designer or developer reads your document, they should be able to understand the overall idea, the scope, the domain, the resources, the expectations, and why alternative choices are not selected. To create a document in this way, you use a balance between storytelling (with pictures!) and complex diagrams.

Jun 1st 2026
5-12 Weeks