İzmir Ekonomi Üniversitesi
  • TÜRKÇE

  • GRADUATE SCHOOL

    M.SC. in Computer Engineering (Without Thesis)

    CE 518 | Course Introduction and Application Information

    Course Name
    Advanced Computing Theory
    Code
    Semester
    Theory
    (hour/week)
    Application/Lab
    (hour/week)
    Local Credits
    ECTS
    CE 518
    Fall/Spring
    3
    0
    3
    7.5

    Prerequisites
    None
    Course Language
    English
    Course Type
    Elective
    Course Level
    Second Cycle
    Mode of Delivery -
    Teaching Methods and Techniques of the Course -
    National Occupation Classification -
    Course Coordinator -
    Course Lecturer(s) -
    Assistant(s) -
    Course Objectives The objective of this course is to provide an in-depth study of the theory of automata and formal languages. This course introduces the classical mathematical models used to analyse computation, including finite state automata, grammars, and Turing Machines. A computer scientist should be able to distinguish between what can be computed and what cannot. This distinction can only be made with a good scientific model of computers and computation. This course introduces the powerful idea of using a mathematical model to analyse computation. This course describes a number of different models of computation which were proposed and analysed over the past century. Many of these models were found to be equivalent, in the sense that they allow exactly the same computations to be carried out. Other models were shown to be less powerful, but simpler to implement, and so useful for some purposes.
    Learning Outcomes

    The students who succeeded in this course;

    • will be able to construct deteministic and non-deterministic automata recognising given languages using a variety of techniques.
    • will be able to convert a regular expression into a non-deterministic automaton recognising the same language.
    • will be able to prove that a language is not regular or is not context-free.
    • will be able to design a context-free grammar, prove if it is ambiguous by using the notion of parse trees, and be able to convert it into Chomsky’s normal form.
    • will be able to construct deterministic and non-deterministic pushdown automata recognising given languages using a variety of techniques.
    • will be able to convert a context-free grammar to an equivalent pushdown automata and vice versa.
    • will be able to construct Turing machines recognising given languages using a variety of techniques.
    • will be able to describe the diagonalization technique, Post’s correspondence, and some undecidable problems.
    Course Description The following topics will be included: finite automata, regular expressions and languages, properties of regular languages, context-free grammars and languages, pushdown automata, properties of context-free languages, Turing machines, and undecidability.

     



    Course Category

    Core Courses
    Major Area Courses
    Supportive Courses
    Media and Management Skills Courses
    Transferable Skill Courses

     

    WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

    Week Subjects Related Preparation Learning Outcome
    1 Finite Automata Chapter 2. Introduction to Automata Theory, Languages, and Computation. J.E. Hopcroft, R. Motawa, and J.D. Ullman. Second Edition, ISBN 0-321-21029-8.
    2 Regular expressions and its applications Chapter 3. Introduction to Automata Theory, Languages, and Computation. J.E. Hopcroft, R. Motawa, and J.D. Ullman. Second Edition, ISBN 0-321-21029-8.
    3 Algebraic laws for regular expressions Chapter 3. Introduction to Automata Theory, Languages, and Computation. J.E. Hopcroft, R. Motawa, and J.D. Ullman. Second Edition, ISBN 0-321-21029-8.
    4 Pumping lemma for regular languages; closure properties of regular languages Chapter 4. Introduction to Automata Theory, Languages, and Computation. J.E. Hopcroft, R. Motawa, and J.D. Ullman. Second Edition, ISBN 0-321-21029-8.
    5 Decision properties of regular languages; equivalence and minimization of automata Chapter 4. Introduction to Automata Theory, Languages, and Computation. J.E. Hopcroft, R. Motawa, and J.D. Ullman. Second Edition, ISBN 0-321-21029-8.
    6 Context-free grammars; parse tress Chapter 5. Introduction to Automata Theory, Languages, and Computation. J.E. Hopcroft, R. Motawa, and J.D. Ullman. Second Edition, ISBN 0-321-21029-8.
    7 Ambiguity in grammars and languages Chapter 5. Introduction to Automata Theory, Languages, and Computation. J.E. Hopcroft, R. Motawa, and J.D. Ullman. Second Edition, ISBN 0-321-21029-8
    8 Pushdown automata Chapter 6. Introduction to Automata Theory, Languages, and Computation. J.E. Hopcroft, R. Motawa, and J.D. Ullman. Second Edition, ISBN 0-321-21029-8.
    9 Normal forms for context-free; pumping lemma for context-free languages Chapter 7. Introduction to Automata Theory, Languages, and Computation. J.E. Hopcroft, R. Motawa, and J.D. Ullman. Second Edition, ISBN 0-321-21029-8.
    10 Closure properties of context-free languages; decision properties of context-free languages Chapter 7. Introduction to Automata Theory, Languages, and Computation. J.E. Hopcroft, R. Motawa, and J.D. Ullman. Second Edition, ISBN 0-321-21029-8.
    11 Turing machines Chapter 8. Introduction to Automata Theory, Languages, and Computation. J.E. Hopcroft, R. Motawa, and J.D. Ullman. Second Edition, ISBN 0-321-21029-8.
    12 A language that is not recursively enumerable Chapter 9. Introduction to Automata Theory, Languages, and Computation. J.E. Hopcroft, R. Motawa, and J.D. Ullman. Second Edition, ISBN 0-321-21029-8.
    13 An undecidable problem that is recursively enumerable Chapter 9. Introduction to Automata Theory, Languages, and Computation. J.E. Hopcroft, R. Motawa, and J.D. Ullman. Second Edition, ISBN 0-321-21029-8.
    14 Post’s correspondence problem Chapter 9. Introduction to Automata Theory, Languages, and Computation. J.E. Hopcroft, R. Motawa, and J.D. Ullman. Second Edition, ISBN 0-321-21029-8.
    15 Examples of undecidable problems Chapter 9. Introduction to Automata Theory, Languages, and Computation. J.E. Hopcroft, R. Motawa, and J.D. Ullman. Second Edition, ISBN 0-321-21029-8.
    16 -

     

    Course Notes/Textbooks The textbook referenced above and course slides
    Suggested Readings/Materials Related Research Papers

     

    EVALUATION SYSTEM

    Semester Activities Number Weigthing
    Participation
    Laboratory / Application
    Field Work
    Quizzes / Studio Critiques
    Portfolio
    Homework / Assignments
    Presentation / Jury
    1
    30
    Project
    Seminar / Workshop
    Oral Exams
    Midterm
    1
    30
    Final Exam
    1
    40
    Total

    Weighting of Semester Activities on the Final Grade
    1
    60
    Weighting of End-of-Semester Activities on the Final Grade
    1
    40
    Total

    ECTS / WORKLOAD TABLE

    Semester Activities Number Duration (Hours) Workload
    Theoretical Course Hours
    (Including exam week: 16 x total hours)
    16
    3
    48
    Laboratory / Application Hours
    (Including exam week: '.16.' x total hours)
    16
    0
    Study Hours Out of Class
    15
    9
    135
    Field Work
    0
    Quizzes / Studio Critiques
    0
    Portfolio
    0
    Homework / Assignments
    0
    Presentation / Jury
    1
    5
    5
    Project
    0
    Seminar / Workshop
    0
    Oral Exam
    0
    Midterms
    1
    15
    15
    Final Exam
    1
    22
    22
        Total
    225

     

    COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

    #
    PC Sub Program Competencies/Outcomes
    * Contribution Level
    1
    2
    3
    4
    5
    1 Accesses information in breadth and depth by conducting scientific research in Computer Engineering, evaluates, interprets and applies information.
    X
    -
    -
    -
    -
    2 Is well-informed about contemporary techniques and methods used in Computer Engineering and their limitations.
    -
    -
    -
    X
    -
    3 Uses scientific methods to complete and apply information from uncertain, limited or incomplete data, can combine and use information from different disciplines.
    -
    -
    -
    X
    -
    4 Is informed about new and upcoming applications in the field and learns them whenever necessary.
    -
    -
    -
    -
    X
    5 Defines and formulates problems related to Computer Engineering, develops methods to solve them and uses progressive methods in solutions.
    -
    -
    -
    -
    X
    6 Develops novel and/or original methods, designs complex systems or processes and develops progressive/alternative solutions in designs.
    X
    -
    -
    -
    -
    7 Designs and implements studies based on theory, experiments and modelling, analyses and resolves the complex problems that arise in this process.
    X
    -
    -
    -
    -
    8 Can work effectively in interdisciplinary teams as well as teams of the same discipline, can lead such teams and can develop approaches for resolving complex situations, can work independently and takes responsibility.
    -
    X
    -
    -
    -
    9 Engages in written and oral communication at least in Level B2 of the European Language Portfolio Global Scale.
    -
    X
    -
    -
    -
    10 Communicates the process and the results of his/her studies in national and international venues systematically, clearly and in written or oral form.
    X
    -
    -
    -
    -
    11 Is knowledgeable about the social, environmental, health, security and law implications of Computer Engineering applications, knows their project management and business applications, and is aware of their limitations in Computer Engineering applications.
    X
    -
    -
    -
    -
    12 Highly regards scientific and ethical values in data collection, interpretation, communication and in every professional activity.
    X
    -
    -
    -
    -

    *1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest

     


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