Course detail

Model-Based Analysis

FIT-MBAAcad. year: 2020/2021

Introduction of model-base design, testing, analysis and model checking. Petri nets as a model of parallel systems. Techniques for analysis of Petri nets. Markov chains as a model of probabilistic systems. Techniques for analysis of Markov chains. Timed automata as a model of systems working with real-time. Techniques for analysis of timed automata. UML and SysML diagrams within model-based design and techniques for their analysis. Introduction to the tools for analysis of the presented models.

Learning outcomes of the course unit

Not applicable.

Prerequisites

Basic knowledge of graph theory, formal languages concepts and automata theory. Basic knowledge of statistics and probability. Basic knowledge of software engineering.

Co-requisites

Not applicable.

Recommended optional programme components

Not applicable.

Recommended or required reading

Jensen, K.: Coloured Petri Nets, Basic Concepts, Analysis Methods and Practical Use, Springer Verlag, 1993. ISBN: 3-540-60943-1
Kaynar, D.,  Lynch, N., Segala, R., Vaandrager, F. :The Theory of Timed I/O Automata, Morgan & Claypool, 2010.  ISBN-13: 978-1608450022 Available online.
Boucherie, R. J.(editor), van Dijk, N. M. (editor): Markov Decision Processes in Practice, Springer,  2017.  ISBN-13: 978-3319477640 Available online (https://link.springer.com/book/10.1007%2F978-3-319-47766-4) from VUT network.
Christel Baier and Joost-Pieter Katoen: Principles of Model Checking, MIT Press, 2008. ISBN: 978-0-262-02649-9
Reisig, W.: Petri Nets, An Introduction, Springer Verlag, 1985. ISBN: 0-387-13723-8
Češka, M.: Petriho sítě, Akad.nakl. CERM, Brno, 1994. ISBN: 8-085-86735-4
Kaynar, D.,  Lynch, N., Segala, R., Vaandrager, F. :The Theory of Timed I/O Automata, Morgan & Claypool, 2010.  ISBN-13: 978-1608450022
Boucherie, R. J.(editor), van Dijk, N. M. (editor): Markov Decision Processes in Practice, Springer,  2017.  ISBN-13: 978-3319477640

Planned learning activities and teaching methods

Not applicable.

Assesment methods and criteria linked to learning outcomes

Not applicable.

Language of instruction

Czech

Work placements

Not applicable.

Aims

Introduce students to the possibility of software (resp. hardware) quality assurance by creating its model, check correctness on the level of the model, and subsequently translate (sometimes automatelly) the model into the target programming language. These principles are introduced on four models, in particular: Petri nets, Markov chains, timed automata and UML/SysML diagrams.

Specification of controlled education, way of implementation and compensation for absences

3 projects, 10 points each.

Students have to achieve at least 30 points, otherwise the exam is assessed by 0 points.

Classification of course in study plans

  • Programme IT-MGR-2 Master's

    branch MBI , any year of study, summer semester, 5 credits, elective
    branch MPV , any year of study, summer semester, 5 credits, elective
    branch MSK , any year of study, summer semester, 5 credits, elective
    branch MBS , any year of study, summer semester, 5 credits, elective
    branch MMM , any year of study, summer semester, 5 credits, compulsory

  • Programme MITAI Master's

    specialization NADE , any year of study, summer semester, 5 credits, elective
    specialization NBIO , any year of study, summer semester, 5 credits, elective
    specialization NGRI , any year of study, summer semester, 5 credits, elective
    specialization NNET , any year of study, summer semester, 5 credits, elective
    specialization NVIZ , any year of study, summer semester, 5 credits, elective
    specialization NCPS , any year of study, summer semester, 5 credits, elective
    specialization NSEC , any year of study, summer semester, 5 credits, elective
    specialization NEMB , any year of study, summer semester, 5 credits, elective
    specialization NHPC , any year of study, summer semester, 5 credits, elective
    specialization NISD , any year of study, summer semester, 5 credits, elective
    specialization NIDE , any year of study, summer semester, 5 credits, elective
    specialization NISY , any year of study, summer semester, 5 credits, elective
    specialization NMAL , any year of study, summer semester, 5 credits, elective
    specialization NMAT , any year of study, summer semester, 5 credits, elective
    specialization NSEN , any year of study, summer semester, 5 credits, compulsory
    specialization NVER , any year of study, summer semester, 5 credits, compulsory
    specialization NSPE , any year of study, summer semester, 5 credits, elective

  • Programme IT-MGR-2 Master's

    branch MGM , 2. year of study, summer semester, 5 credits, elective
    branch MIS , 2. year of study, summer semester, 5 credits, compulsory-optional
    branch MIN , 2. year of study, summer semester, 5 credits, compulsory

Type of course unit

 

Lecture

39 hours, optionally

Teacher / Lecturer

Syllabus

  1. Introduction to the topic of model-based design, testing and analysis. The term model-checking.
  2. Petri nets. Basic terms, history and applications.
  3. P/T Petri nets, definition, evolution rules, state space, bacis problems of analysis.
  4. Analysis of P/T Petri nets, coveribility tree, P- and T- invariants.
  5. Extensions of P/T Petri nets and Coloured Petri nets. Decidability and relation to Turing machines. Tools NetLab a PIPE.
  6. Timed automata and their use in modelling of systems with real-time.
  7. Timed automata analysis, region abstraction, decidable problems. Tool UPPAAL.
  8. Timed temporal logic TCTL and its relation to timed automata.
  9. Temporal logic PCTL for Markov chain specification. Advanced analysis of Markov chains and Markov Decision Processes.
  10. Using counter-examples in the verification of Markov Chains. Synthesis of Markov chains.
  11. Continuous-time Markov chains and their analysis using uniformization.
  12. UML/SysML diagrams and their use in model-based design and analysis.
  13. Model checking of systems described by UML (state) diagrams.

Exercise in computer lab

6 hours, compulsory

Teacher / Lecturer

Syllabus

If applicable:

  1. Analysis of P/T Petri nets, tools NetLab a PIPE.
  2. Analysis of Markov chains, tool PRISM
  3. Analysis of timed automata, tool UPPAAL.

Project

7 hours, compulsory

Teacher / Lecturer

Syllabus

  1. Application of Petri nets.
  2. Application of timed automata.
  3. Application of Markov chains.

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