Course details

Model-Based Analysis

MBA Acad. year 2024/2025 Summer semester 5 credits

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.

Guarantor

Course coordinator

Language of instruction

Czech

Completion

Examination (written+oral)

Time span

  • 26 hrs lectures
  • 10 hrs pc labs
  • 16 hrs projects

Assessment points

  • 70 pts final exam
  • 30 pts projects

Department

Lecturer

Instructor

Learning objectives

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.

Recommended prerequisites

Prerequisite knowledge and skills

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

Study literature

  • Češka, M.: Petriho sítě, Akad.nakl. CERM, Brno, 1994. ISBN: 8-085-86735-4
  • 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 Dostupné online.

Fundamental literature

  • 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
  • Boucherie, R. J.(editor), van Dijk, N. M. (editor): Markov Decision Processes in Practice, Springer, 2017. ISBN-13: 978-3319477640 Dostupné online ze sítě VUT.

Syllabus of lectures

  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. Markov chains as a model of probabilistic systems, Markov chains in discrete and continuous time. Temporal logic for specification of behaviour of Markov chains.
  7. Analysis of Markov chains (model checking), the tool PRISM.
  8. Extension of Markov chains by nondeterminism - Markov decision processes. Use of Markov chains in theory of operation. Synthesis of operation for Markov decision processes.
  9. Timed automata and their use in modelling of systems with real-time.
  10. Timed automata analysis, region abstraction, decidable problems. Tool UPPAAL.
  11. Timed temporal logic TCTL and its relation to timed automata.
  12. UML/SysML diagrams and their use in model-based design and analysis.
  13. Model checking of systems described by UML (state) diagrams.

Syllabus of computer exercises

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.

Syllabus - others, projects and individual work of students

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

Progress assessment

Three projects (10 points each), final exam (70 points).


3 projects, 10 points each.

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

Schedule

DayTypeWeeksRoomStartEndCapacityLect.grpGroupsInfo
Mon comp.lab lectures N203 16:0017:5020 1MIT 2MIT xx
Tue lecture 1., 2., 4., 5., 6., 7. of lectures D0207 10:0011:5090 1MIT 2MIT NSEN NVER xx Rogalewicz
Tue lecture 8., 9., 10. of lectures D0207 10:0011:5090 1MIT 2MIT NSEN NVER xx Češka
Tue lecture 11., 12., 13. of lectures D0207 10:0011:5090 1MIT 2MIT NSEN NVER xx Fiedor
Tue lecture 2025-02-25 D0207 10:0011:5090 1MIT 2MIT NSEN NVER xx Holík
Fri comp.lab lectures N105 13:0014:5020 1MIT 2MIT xx

Course inclusion in study plans

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