DFOME Formal Methods in Theory and Practice

Faculty of Informatics
Spring 2017
Extent and Intensity
3/0. 3 credit(s). Type of Completion: z (credit).
Teacher(s)
doc. RNDr. Tomáš Brázdil, Ph.D. (lecturer)
prof. RNDr. Luboš Brim, CSc. (lecturer)
prof. RNDr. Ivana Černá, CSc. (lecturer)
prof. RNDr. Petr Hliněný, Ph.D. (lecturer)
prof. RNDr. Mojmír Křetínský, CSc. (lecturer)
prof. RNDr. Antonín Kučera, Ph.D. (lecturer)
doc. Ing. Matej Lexa, Ph.D. (lecturer)
prof. RNDr. Jan Strejček, Ph.D. (lecturer)
Guaranteed by
prof. RNDr. Petr Hliněný, Ph.D.
Faculty of Informatics
Supplier department: Faculty of Informatics
Prerequisites (in Czech)
!NOWANY( DEMBSY Embedded systems , DMKZI Quantum Information Processing , DPGZO Graphics & Image Processing , DMPOS Computer Networks Methods , DMZDD Digital Data Processing , DPITS EIT Systems and Services , DZPJUI NLP and AI Methods , DPOSO Advances in Concurrency , DRPSEC Research in comp.security )
Course Enrolment Limitations
The course is only offered to the students of the study fields the course is directly associated with.
fields of study / plans the course is directly associated with
there are 8 fields of study the course is directly associated with, display
Course objectives
The course consists of several and relatively independent parts devoted to selected topics in formal methods. Each part starts with an introduction presented by a lecturer followed by students' reports about the results in selected research papers recommended by the lecturer. The list of topics includes the following: stochastic processes, stochastic games, automatic verification of software, formal models and specification languages, model-checking, infinite-state systems, etc.
Syllabus
  • probability theory: stochastic processes, Markov chains, continuous-time Markov chains, discrete stochastic programming.
  • temporal logic: linear-time and branching-time logics, probabilistic extensions, model-checking
  • static analysis: basic concepts, control-flow and data-flow analysis, applications and tools
  • game theory: basic game theory, min-max theorem, Nash theorem, games in formal verification, Martin's theorem, stochastic games.
Literature
  • KLEINBERG, Jon and Éva TARDOS. Algorithm design. Boston: Pearson/Addison-Wesley, 2006, xxiii, 838. ISBN 0321295358. info
  • PUTERMAN, Martin L. Markov decision processes : discrete stochastic dynamic programming. Hoboken, N.J.: Wiley-Interscience, 2005, xvii, 649. ISBN 0471727822. info
  • DAHLQUIST, Germund, Ned ANDERSON and Åke BJÖRCK. Numerical methods. Mineola, N.Y.: Dover Publications, 2003, xviii, 573. ISBN 0486428079. info
  • GRUMBERG, Orna, Doron A. PELED and E. M. CLARKE. Model checking. Cambridge: MIT Press, 1999, xiv, 314. ISBN 0262032708. info
  • FILAR, Jerzy A. and Koos VRIEZE. Competitive Markov decision processes : with 57 illustrations. New York: Springer, 1997, xii, 393. ISBN 0387948058. info
  • NORRIS, J. R. Markov chains. 1st pub. Cambridge: Cambridge University Press, 1997, xvi, 237. ISBN 9780521481816. info
  • OWEN, Guillermo. Game theory. 3rd ed. San Diego: Academic Press, 1995, xii, 447. ISBN 0125311516. info
  • FELLER, William. An introduction to probability theory and its applications. 3rd ed. [New York]: John Wiley & Sons, 1968, xviii, 509. ISBN 9780471257080. info
Teaching methods
Lectures, class discussion, reading.
Assessment methods
Oral exam.
Language of instruction
Czech
The course is also listed under the following terms Autumn 2007, Spring 2008, Autumn 2008, Spring 2009, Autumn 2009, Spring 2010, Autumn 2010, Spring 2011, Autumn 2011, Spring 2012, Autumn 2012, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020.
  • Enrolment Statistics (Spring 2017, recent)
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