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CSC 351 Theory of Computation

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In this introduction to theoretical computer science and ... Self-embeddedness, pumping lemma for context ... Automata, understanding of non-determinism ... – PowerPoint PPT presentation

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Title: CSC 351 Theory of Computation


1
CSC 351 Theory of Computation
  • Fall 2004

2
Course Description
  • In this introduction to theoretical computer
    science and analysis of discrete mathematical
    structures which find application in computer
    science, topics may include predicate calculus,
    groups, coding theory, graphs, trees, formal
    languages, grammars, finite state automata,
    Turing machines, complexity theory.
  • ACM Topics
  • AL5 - Basic computability (6)
  • AL6 - The complexity classes P and NP
  • AL7 - Automata theory

3
Course Goals
  • Examine the mathematical models of machines that
    act as acceptors for the principal classes of
    grammars and languages. 
  •  Study the closure and decidability properties
    that pertain to each class, write formal proofs
    using various pumping lemmas and theorems, and
    reach an understanding of language structure that
    cannot be encompassed in the class.
  • Learn about the historical background of the
    theory of computation, about the ideas of
    computability and NP-completeness.

4
Topics
  •  Regular expressions and languages, deterministic
    and non deterministic finite automata.
  • Closure and decidability properties of regular
    languages.
  • Pumping lemma for regular languages.
  • Context-free grammars, Chomsky normal form,
    pushdown automata.
  • Closure and decidability properties of
    context-free languages.
  • Self-embeddedness, pumping lemma for context-free
    languages.
  • Turing machines and variants, recursively
    enumerable languages.
  • Non recursive enumerable languages, the Chomsky
    hierarchy.
  • Computability, complexity, NP-completeness.

5
Course Administration
  • Textbook An Introduction to Formal Languages and
    Automata by Linz
  • Software JFLAP

6
Evaluation
  • Final Exam Average 77
  • Course Grade Average 80 100 passing
  • Most improved Automata, understanding of
    non-determinism
  • Still needs work remembering details of
    algorithms, proofs, especially proof by induction

7
Teaching Evaluation
  • Worked
  • JFLAP as visualization tool
  • Applications discussions and assignments
  • Theoretical discussions Turings thesis,
    computability
  • Changes for next year
  • Less emphasis on set functions
  • More applications homework
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