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Theory of Computation (ΠΛ2)

Theory of Computation (ΠΛ2)

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General

School School of Science
Academic Unit Department of Mathematics
Level of Studies Graduate
Course Code ΠΛ2
Semester 1
Course Title Theory of Computation
Independent Teaching Activities Lectures (Weekly Teaching Hours: 3, Credits: 7.5)
Course Type Specialization
Prerequisite Courses

Undergraduate courses in Automata Theory and Formal Languages, Data Structures and Algorithms

Language of Instruction and Examinations

Greek

Is the Course Offered to Erasmus Students Yes (in English)
Course Website (URL) See eCourse, the Learning Management System maintained by the University of Ioannina.

Learning Outcomes

Learning outcomes

The goal of this course is the deeper understanding of Automata Theory and Language, Computability Theory and Complexity Theory as well as the introduction of students to critical thinking and research process. During the course a detailed examination of the following topics are done:

  • Finite Automata (Deterministic FA, Nondeterministic FA, FA with Epsilon-Transitions) and their applications, Regular Expressions and Languages, Properties of Regular Languages
  • Context-Free Grammars and languages, Pushdown Automata (Deterministic PDA, Acceptance by Fina lState, Acceptance by Empty Stack) , Properties of Context-Free Languages
  • Turing Machines (Standard TM, Multitrack TM, Two-Way Tape TM, Multitape TM, Nondeterministic TM)
  • Decidability and Computability
  • Computational Complexity

After completing the course the student can handle:

  • theoretical documentation of problems
  • solving exercises
  • tracking applications

which related to Finite Automata, Pushdown Automata, and Turing Machines as well as to Decidability and Computability and to Computational Complexity.

General Competences
  • Independent work
  • Bibliographic search
  • Effective selection and Design of the required machine and language.

Syllabus

  • Properties of the Computation Theory Mathematical Models
  • Problems classification to solvable and unsolvable
  • Solvable Problems Classification

Teaching and Learning Methods - Evaluation

Delivery

Face to face

Use of Information and Communications Technology Yes
Teaching Methods
Activity Semester Workload
Lectures 39
Self study 78
Exercises 70.5
Course total 187.5
Student Performance Evaluation
  • Final essays (40%).
  • Exercises - questions requiring critical thinking (30%).
  • Presentations of related issues (30%).

Attached Bibliography

  • Sudkamp, Thomas A. Languages and machines : an introduction to the theory of computer science / Thomas A. Sudkamp. - 2nd ed. ISBN 0-201-82136-2
  • Hopcroft, John E., Rajeev Motwani, Jeffrey . Ullman Introduction to automata theory, languages and computation -2nd ed. ISBN 0321210298
  • Michael Sipser. Introduction to the Theory of Computation (3rd ed.). Cengage Learning. ISBN 978-1-133-18779-0.
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