FACULTY OF ARTS AND SCIENCES

Department of Mathematics

CE 308 | Course Introduction and Application Information

Course Name
Computing Theory
Code
Semester
Theory
(hour/week)
Application/Lab
(hour/week)
Local Credits
ECTS
CE 308
Fall/Spring
3
2
4
7

Prerequisites
  CE 215 To succeed (To get a grade of at least DD)
Course Language
English
Course Type
Elective
Course Level
First Cycle
Mode of Delivery -
Teaching Methods and Techniques of the Course Discussion
Problem Solving
Q&A
Critical feedback
Lecture / Presentation
Course Coordinator
Course Lecturer(s)
Assistant(s)
Course Objectives The objective of this course is to introduce the theory of automata and formal languages as a further step in abstracting the attention away from any particular kind of programming language. Basic models of computation will be presented which will set the grounds for many branches of computer science such as compiler design and software engineering. At the end of the course, students are expected to deal with all these concepts from an engineering viewpoint.
Learning Outcomes The students who succeeded in this course;
  • will be able to articulate Chomsky language hierarchy and corresponding automata and grammar types,
  • will be able to trace a given automata or grammar,
  • will be able to convert a given automata (DFA, NFA, PDA, TM) or grammar to another equivalent form,
  • will be able to design an automata or grammar for a given language,
  • will be able to define basic computational complexity concepts of polynomial time, non-deterministic polynomial time, NP-completeness, decidability and undecidability.
Course Description The following topics will be included: regular expressions and contextfree languages, finite and pushdown automata, Turing machines, computability, undecidability, and complexity of problems.

 



Course Category

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

 

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week Subjects Related Preparation
1 Deterministic Finite Automata Chapter 1. Sections 1.1. Introduction to the theory of computation. Michael Sipser. ISBN 053494728X
2 Deterministic Finite Automata Chapter 1. Sections 1.1. Introduction to the theory of computation. Michael Sipser. ISBN 053494728X
3 Nondeterministic finite automata Chapter 1. Sections 1.2. Introduction to the theory of computation. Michael Sipser. ISBN 053494728X
4 Nondeterministic finite automata Chapter 1. Sections 1.2. Introduction to the theory of computation. Michael Sipser. ISBN 053494728X
5 Regular Expressions Chapter 1. Sections 1.3. Introduction to the theory of computation. Michael Sipser. ISBN 053494728X
6 Regular Expressions Chapter 1. Sections 1.3. Introduction to the theory of computation. Michael Sipser. ISBN 053494728X
7 Context-free Grammars Chapter 2. Sections 2.1. Introduction to the theory of computation. Michael Sipser. ISBN 053494728X
8 Context-free Grammars Chapter 2. Sections 2.1. Introduction to the theory of computation. Michael Sipser. ISBN 053494728X
9 Pushdown Automata Chapter 2. Sections 2.2. Introduction to the theory of computation. Michael Sipser. ISBN 053494728X
10 Pushdown Automata Chapter 2. Sections 2.2. Introduction to the theory of computation. Michael Sipser. ISBN 053494728X
11 Turing Machines Chapter 3. Sections 3.1. Introduction to the theory of computation. Michael Sipser. ISBN 053494728X
12 Turing Machines Chapter 3. Sections 3.2, 3.3. Introduction to the theory of computation. Michael Sipser. ISBN 053494728X
13 The class P and NP Chapter 7. Sections 7.2, 7.3. Introduction to the theory of computation. Michael Sipser. ISBN 053494728X
14 NP completeness Chapter 7. Sections 7.4. Introduction to the theory of computation. Michael Sipser. ISBN 053494728X
15 Decidability and undecidability Chapter 4. Introduction to the theory of computation. Michael Sipser. ISBN 053494728X
16 Review of Semester

 

Course Notes/Textbooks

Introduction to the theory of computation, Michael Sipser. ISBN 053494728X

Suggested Readings/Materials

https://ocw.mit.edu/courses/18-404j-theory-of-computation-fall-2020/

 

EVALUATION SYSTEM

Semester Activities Number Weigthing
Participation
Laboratory / Application
Field Work
Quizzes / Studio Critiques
1
20
Portfolio
Homework / Assignments
1
12
Presentation / Jury
Project
Seminar / Workshop
Oral Exams
Midterm
1
28
Final Exam
1
40
Total

Weighting of Semester Activities on the Final Grade
3
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
2
32
Study Hours Out of Class
14
5
70
Field Work
0
Quizzes / Studio Critiques
1
10
10
Portfolio
0
Homework / Assignments
2
5
10
Presentation / Jury
0
Project
0
Seminar / Workshop
0
Oral Exam
0
Midterms
1
20
20
Final Exam
1
20
20
    Total
210

 

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#
Program Competencies/Outcomes
* Contribution Level
1
2
3
4
5
1

To be able to have a grasp of basic mathematics, applied mathematics or theories and applications of statistics.

2

To be able to use advanced theoretical and applied knowledge, interpret and evaluate data, define and analyze problems, develop solutions based on research and proofs by using acquired advanced knowledge and skills within the fields of mathematics or statistics.

3

To be able to apply mathematics or statistics in real life phenomena with interdisciplinary approach and discover their potentials.

4

To be able to evaluate the knowledge and skills acquired at an advanced level in the field with a critical approach and develop positive attitude towards lifelong learning.

X
5

To be able to share the ideas and solution proposals to problems on issues in the field with professionals, non-professionals.

X
6

To be able to take responsibility both as a team member or individual in order to solve unexpected complex problems faced within the implementations in the field, planning and managing activities towards the development of subordinates in the framework of a project.

7

To be able to use informatics and communication technologies with at least a minimum level of European Computer Driving License Advanced Level software knowledge.

8

To be able to act in accordance with social, scientific, cultural and ethical values on the stages of gathering, implementation and release of the results of data related to the field.

9

To be able to possess sufficient consciousness about the issues of universality of social rights, social justice, quality, cultural values and also environmental protection, worker's health and security.

X
10

To be able to connect concrete events and transfer solutions, collect data, analyze and interpret results using scientific methods and having a way of abstract thinking.

11

To be able to collect data in the areas of Mathematics or Statistics and communicate with colleagues in a foreign language.

12

To be able to speak a second foreign language at a medium level of fluency efficiently.

13

To be able to relate the knowledge accumulated throughout the human history to their field of expertise.

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

 


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