Title:

Theoretical Computer Science

Code:TIN
Ac.Year:2012/2013
Term:Winter
Study plans:
ProgramBranchYearDuty
IT-MSC-2MBI1stCompulsory
IT-MSC-2MBS1stCompulsory
IT-MSC-2MGM1stCompulsory
IT-MSC-2MIN1stCompulsory
IT-MSC-2MIS1stCompulsory
IT-MSC-2MMI1stCompulsory
IT-MSC-2MMM1stCompulsory
IT-MSC-2MPV1stCompulsory
IT-MSC-2MSK1stCompulsory
IT-MSC-2EITE1stCompulsory
Language:Czech
Public info:http://www.fit.vutbr.cz/study/courses/TIN/public/
Private info:http://www.fit.vutbr.cz/study/courses/TIN/private/
Credits:5
Completion:accreditation+exam (written&verbal)
Type of
instruction:
Hour/semLecturesSem. ExercisesLab. exercisesComp. exercisesOther
Hours:3900013
 ExaminationTestsExercisesLaboratoriesOther
Points:60200020
Guarantee:Češka Milan, prof. RNDr., CSc., DITS
Lecturer:Češka Milan, prof. RNDr., CSc., DITS
Instructor:Holík Lukáš, Mgr., Ph.D., DITS
Rogalewicz Adam, Mgr., Ph.D., DITS
Faculty:Faculty of Information Technology BUT
Department:Department of Intelligent Systems FIT BUT
Follow-ups:
Complexity (SLO), DITS
Functional and Logic Programming (FLP), DIFS
Parallel and Distributed Algorithms (PRL), DITS
Petri Nets (PES), DITS
Substitute for:
Theoretical Computer Science 1 (TI1), DITS
 
Learning objectives:
To acquaint students with more advanced parts of the formal language theory, with basics of the theory of computability, and with basic terms of the complexity theory.
Description:
An overview of the applications of the formal language theory in modern computer science and engineering (compilers, system modelling and analysis, linguistics, etc.), the modelling and decision power of formalisms, regular languages and their properties, minimalization of finite-state automata, context-free languages and their properties, Turing machines, properties of recursively enumerable and recursive languages, computable functions, undecidability, undecidable problems of the formal language theory.
Knowledge and skills required for the course:
Basic knowledge of discrete mathematics concepts including graph theory and formal languages concepts, and basic concepts of algorithmic complexity.
Subject specific learning outcomes and competences:
The students are acquainted with basic as well as more advanced terms, approaches, and results of the theory of automata and formal languages and with basics of the theory of computability and complexity allowing them to better understand the nature of the various ways of describing and implementing computer-aided systems. The students are capable of applying the acquainted knowledge when solving complex theoretical as well as practical problems in the areas of system modelling, programming, formal specification and verification, and artificial intelligence.
Generic learning outcomes and competences:
The students acquire basic capabilities for theoretical research activities.
Syllabus of lectures:
  1. An overview of the applications of the formal language theory, the modelling and decision power of formalisms, operations over languages.
  2. Regular languages and their properties, Kleene's theorem, Nerod's theorem, Pumping lemma.
  3. Minimalization of finite-state automata, the relation of indistinguishability of automata states, construction of a reduced finite-state automaton.
  4. Closure properties of regular languages, regular languages as a Boolean algebra, decidable problems of regular languages.
  5. Context-free languages and their properties, normal forms of context-free grammars, unambiguous and deterministic context-free languages, Pumping lemma for context-free languages.
  6. Closure properties of context-free languages, closedness wrt. substitution and its consequences, decidable problems of context-free languages.
  7. Turing machines (TMs), the language accepted by a TM, recursively enumerable and recursive languages and problems, TMs and functions, methods of  constructing TMs.
  8. Modifications of TMs, TMs with a tape infinite on both sides, with more tapes, nondeterministic TMs, automata with two push-down stacks, automata with counters.
  9. TMs and type-0 languages, diagonalisation, properties of recursively enumerable and recursive languages, linearly bounded automata and type-1 languages.
  10. Computable functions, initial functions, primitive recursive functions, mu-recursive functions, the relation of TMs and computable functions.
  11. The Church-Turing thesis, universal TMs, undecidability, the halting problem, reductions, the Post's correspondence problem.
  12. Undecidable problems of the formal language theory.
  13. An introduction to the computational complexity, Turing complexity, the P and NP classes and beyond.
Syllabus - others, projects and individual work of students:
  1. A homework on regular languages and finite-state automata.
  2. A homework on context-free languages.
  3. A homework on Turing machines.
  4. A homework on computable functions.
Fundamental literature:
  1. Kozen, D.C.: Automata and Computability, Springer-Verlag, New York, Inc, 1997. ISBN 0-387-94907-0
  2. Hopcroft, J.E., Motwani, R., Ullman, J.D.: Introduction to Automata Theory, Languages, and Computation, Addison Wesley, 2nd ed., 2000. ISBN 0-201-44124-1
  3. Martin, J.C.: Introduction to Languages and the Theory of Computation, McGraw-Hill, Inc., 3rd ed., 2002. ISBN 0-072-32200-4
  4. Brookshear, J.G. : Theory of Computation: Formal Languages, Automata, and Complexity, The Benjamin/Cummings Publishing Company, Inc, Redwood City, California, 1989. ISBN 0-805-30143-7
  5. Aho, A.V., Ullmann, J.D.: The Theory of Parsing,Translation and Compiling, Prentice-Hall, 1972. ISBN 0-139-14564-8
Study literature:
  1. Kozen, D.C.: Automata and Computability, Springer-Verlag, New Yourk, Inc, 1997. ISBN 0-387-94907-0
  2. Hopcroft, J.E., Motwani, R., Ullman, J.D.: Introduction to Automata Theory, Languages, and Computation, Addison Wesley, 2nd ed., 2000. ISBN 0-201-44124-1
Controlled instruction:
A written mid-term exam, a regular evaluation of homeworks, a final exam. The minimal number of points which can be obtained from the final exam is 25. Otherwise, no points will be assign to a student.

Progress assessment:
A mid-term exam evaluation (max. 20 points) and an evaluation of homeworks (max 20 points).
Exam prerequisites:
The minimal total score of 15 points gained out of the first three assignements and the mid-term exam (i.e. out of 35 points).