GRADUATE SCHOOL

M.SC. in Computer Engineering (With 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
Service Course
Course Level
Second Cycle
Mode of Delivery -
Teaching Methods and Techniques of the Course -
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
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

#
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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