OVERVIEW

The course introduces the students to problems related to modeling and verification of systems which intertwine physical processes, computing and network resources.

AIMS AND CONTENT

LEARNING OUTCOMES

Students should acquire the capability to model and reason about systems involving mixed continuous-discrete-probabilistic dynamics.

AIMS AND LEARNING OUTCOMES

The goal of the course is to consolidate elements of Computer and Systems Engineering acquired by the students along their careers, and to provide a uniform approach to Cyber-Physical Systems (CPS), i.e., engineered systems that are built from and depend upon the synergy of computational and physical components. In particular, the course is meant to introduce the students to the theory of Hybrid and Probabilistic Automata, and to lead them through hands-on-experience with state-of-the-art simulation, synthesis and verification tools for CPS. At the end of the course students should be able to model, simulate and verify distributed computational units controlling physical processes

PREREQUISITES

Some basics in System/Control Theory as well as Computer Science foundations are necessary to understand the course contents. In particular the student should be familiar with continuous models such as ordinary (linear) differential equations, and discrete models such as finite automata, and Markov chains. Some knowledge about programming is preferred, but not mandatory.

TEACHING METHODS

Lectures and computer labs.

SYLLABUS/CONTENT

Introduction to system verification. Modeling and verification of discrete state systems. Modeling and verification of real-time and hybrid systems. Modeling and verification of probabilistic systems. Heterogeneous and hierarchical modeling.

RECOMMENDED READING/BIBLIOGRAPHY

Cristel Baier, Joost-Pieter Katoen - Principles of Model Checking – MIT Press - 2008

AA. VV. - System Design, Modeling and Simulation using Ptolemy II - Ptolemy.org - 2014

TEACHERS AND EXAM BOARD

Exam Board

ARMANDO TACCHELLA (President)

ENRICO GIUNCHIGLIA

MASSIMO NARIZZANO

LESSONS

LESSONS START

September 2019

Class schedule

The timetable for this course is available here: Portale EasyAcademy

EXAMS

EXAM DESCRIPTION

Homeworks (10%), final project (50%) and presentation (40%)

ASSESSMENT METHODS

At the end of the course students should be able to model, simulate and verify distributed computational units controlling physical processes.

Exam schedule