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A course is the basic teaching unit, it's design as a medium for a student to acquire comprehensive knowledge and skills indispensable in the given field. A course guarantor is responsible for the factual content of the course.
For each course, there is a department responsible for the course organisation. A person responsible for timetabling for a given department sets a time schedule of teaching and for each class, s/he assigns an instructor and/or an examiner.
Expected time consumption of the course is expressed by a course attribute extent of teaching. For example, extent = 2 +2 indicates two teaching hours of lectures and two teaching hours of seminar (lab) per week.
At the end of each semester, the course instructor has to evaluate the extent to which a student has acquired the expected knowledge and skills. The type of this evaluation is indicated by the attribute completion. So, a course can be completed by just an assessment ('pouze zápočet'), by a graded assessment ('klasifikovaný zápočet'), or by just an examination ('pouze zkouška') or by an assessment and examination ('zápočet a zkouška') .
The difficulty of a given course is evaluated by the amount of ECTS credits.
The course is in session (cf. teaching is going on) during a semester. Each course is offered either in the winter ('zimní') or summer ('letní') semester of an academic year. Exceptionally, a course might be offered in both semesters.
The subject matter of a course is described in various texts.

MI-AVY Automata in Text Pattern Matching Extent of teaching: 2P+1C
Instructor: Žďárek J., Guth O., Pecka T., Plachý Š., Trávníček J. Completion: Z,ZK
Department: 18101 Credits: 4 Semester: L

Annotation:
Searching in a text (pattern matching) and generally in data is an area of problems and exciting solutions from theoretical and practical perspectives. We may interpret and search the data as one-dimensional (text) or multi-dimensional (tree, picture). We may search for something known (a pattern: a string or a set specified by regular expression) or unknown (for example, a regularity). Matching can be either exact or approximate. This course presents a taxonomy of searching problems. It focuses on algorithms based on some automaton (finite, pushdown, linear-bounded, or tree).

Lecture syllabus:
1. Finite automata, basic operations with finite automata. Taxonomy of pattern matching problems for exact and approximate matching. Forward pattern matching, models of searching algorithms. Nondeterministic search automata.
2. Deterministic search finite automata and their state complexity.
3. Construction of prefix and suffix automata. Construction of factor automata. Computation of borders and periods of text. Searching exact and approximate repetitions in text.
4. Searching other string regularities and other indexing automata applications.
5. Regular expressions with backreferences.
6. Synchronizing finite automata.
7. Locally testable languages.
8. Classes of deterministic and nondeterministic pushdown automata. Determinisation of pushdown automata.
9. Tree automata.
10. Tree pattern matching & indexing, non-linear tree patterns.
11. Combinatorial pattern matching and indexing of multidimensional text.
12. Tree regular expressions.

Seminar syllabus:
1. Finite automata, basic operations with finite automata. Taxonomy of pattern matching problems for exact and approximate matching. Forward pattern matching, models of searching algorithms. Nondeterministic search automata.
2. Deterministic search finite automata and their state complexity.
3. Construction of prefix and suffix automata. Construction of factor automata. Computation of borders and periods of text. Searching exact and approximate repetitions in text.
4. Searching other string regularities and other indexing automata applications.
5. Regular expressions with backreferences.
6. Synchronizing finite automata.
7. Locally testable languages.
8. Classes of deterministic and nondeterministic pushdown automata. Determinisation of pushdown automata.
9. Tree automata.
10. Tree pattern matching & indexing, non-linear tree patterns.
11. Combinatorial pattern matching and indexing of multidimensional text.
12. Tree regular expressions.

Literature:
1. Melichar, B.; Holub, J.; Polcar, T. Text Searching Algorithms. Volume I: Forward String Matching. Dostupné z: https://psc.fit.cvut.cz/athens/TextSearchingAlgorithms/
2. Aho, A. V. Algorithms for Finding Patterns in Strings. In Handbook of Theoretical Computer Science, Algorithms and Complexity, 255-300. Elsevier, 1990. ISBN 9780444880710. DOI: 10.1016/B978-0-444-88071-0.50010-2.
3. Alur, R.; Madhusudan P. Visibly pushdown languages. In Proc. 36th Int. ACM Symposium on Theory of Computing (STOC), 2004.
4. Van Tang, N. A tighter bound for the determinization of visibly pushdown automata. In 11th International Workshop on Verification of Infinite-State Systems, INFINITY 2009, 2009.
5. Nowotka, D.; Srba J. Height-Deterministic Pushdown Automata. In 32nd International Symposium on Mathematical Foundations of Computer Science, MFCS'07, 2007.
6. Černý, J. Poznámka k homogénnym experimentom s konečnými automatmi. Matematicko-fyzikálny časopis Slovenskej Akadémie Vied, 14: 208-216. Dostupné z: https://dml.cz/handle/10338.dmlcz/126647
7. Pin, JE. On two combinatorial problems arising from automata theory. Combinatorial mathematics (Marseille-Luminy, 1981), 1983, Marseille-Luminy, pp.535-548. Dostupné z: https://hal.archives-ouvertes.fr/hal-00143937
8. Holub, J.; Štekr, S. Implementation of deterministic finite automata on parallel computers. Colloquium and Festschrift at the occasion of the 60th birthday of Derrick Kourie (Computer Science), Windy Brow, South Africa, 28 June 2008. Dostupné z: http://hdl.handle.net/2263/9145
9. Yechezkel, Z. Locally testable languages. Journal of Computer and System Sciences 6, 151-167 (1972). Dostupné z: https://doi.org/10.1016/S0022-0000(72)80020-5
10. James, R.; Dakotah, L. Extracting Forbidden Factors from Regular Stringsets. Proceedings of the 15th Meeting on the Mathematics of Language, 2017, London, pp.36-46. Dostupné z: https://www.aclweb.org/anthology/W17-3404/

Requirements:
Students are supposed to know the formal language theory and algorithms on finite automata (BIE-AAG course). In particular, students should be familiar with Chomsky hierarchy of languages, subset construction and epsilon-transitions removal.

The course is also part of the following Study plans:
Study Plan Study Branch/Specialization Role Recommended semester
MI-NPVS.2016 Design and Programming of Embedded Systems V 2
MI-SP-SP.2016 System Programming V 2
MI-WSI-ISM.2016 Web and Software Engineering V 2
MI-PSS.2016 Computer Systems and Networks V 2
MI-WSI-SI.2016 Web and Software Engineering V 2
MI-SP-TI.2016 System Programming PZ 2
MI-SPOL.2016 Unspecified Branch/Specialisation of Study VO 2
MI-ZI.2016 Knowledge Engineering V 2
MI-ZI.2018 Knowledge Engineering V 2
MI-WSI-WI.2016 Web and Software Engineering V 2
MI-WSI-ISM.2016 Web and Software Engineering V 2


Page updated 29. 3. 2024, semester: L/2021-2, Z,L/2023-4, Z/2021-2, Z/2020-1, Z/2019-20, L/2020-1, Z,L/2022-3, L/2019-20, Send comments to the content presented here to Administrator of study plans Design and implementation: J. Novák, I. Halaška