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Computation Theory

Module ID

Ε801

Semester

8

Hours/Week - ECTS

4 – 5

George Makris

Adjunct Lecturer

Learning Outcomes

The learning objectives of the course are:

  • To introduce students to the mathematical infrastructure of computation and specifically to automata theory, the theory of formal languages and grammars, the concepts of algorithm, diagnosability, complexity and computability.
  • To develop students’ ability to understand and construct mathematical proofs for calculations and algorithms.

Upon completion of the course the student should be able to:

  • categorize abstract machines and construct abstract machines suitable for specific problems
  • demonstrate an understanding of the advantages and limitations of analytical techniques in software development
  • recognize the importance of complexity classes and calculate the complexity of specific types of algorithms
  • demonstrate a deeper and broader understanding of classes of complexity
  • prove the basic results of the Theory of Computation

Indicative Module Content

  • INTRODUCTION: Automata, Computability, and Complexity, mathematical concepts and terminology
  • REGULAR LANGUAGES: Finite Automata, Arbitrary, Regular Expressions, Non-Regular Languages
  • UNCONSUMABLE LANGUAGES: Uncontextualized Grammars, Stack Automata, Non-Uncontextualized Languages,
  • THE CHURCH-TURING DOCTRINE: Turing Machines, Variations of Turing Machines, The Definition of Algorithm,
  • DIAGNOSTICABILITY: Diagnosable Languages, The Termination Problem
  • TIME COMPLEXITY: Measuring Complexity, The P Class, The NP Class
  • SPATIAL COMPLEXITY: Savitch’s theorem, The PSPACE class