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
3
0
3
7

Prerequisites
  CE 215 To succeed (To get a grade of at least DD)
Course Language
English
Course Type
Required
Course Level
First Cycle
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.
Course Description 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 Content 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
X
Major Area Courses
Supportive Courses
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 Regular expressions Chapter 1. Sections 1.3. Introduction to the theory of computation. Michael Sipser. ISBN 053494728X
5 Contextfree grammars Chapter 2. Sections 2.1. Introduction to the theory of computation. Michael Sipser. ISBN 053494728X
6 Pushdown automata Chapter 2. Sections 2.2. Introduction to the theory of computation. Michael Sipser. ISBN 053494728X
7 Turing machines Chapter 3. Sections 3.1. Introduction to the theory of computation. Michael Sipser. ISBN 053494728X
8 Turing machines Chapter 3. Sections 3.2, 3.3. Introduction to the theory of computation. Michael Sipser. ISBN 053494728X
9 Decidability and undecidability Chapter 4. Introduction to the theory of computation. Michael Sipser. ISBN 053494728X
10 The class P Chapter 7. Sections 7.2. Introduction to the theory of computation. Michael Sipser. ISBN 053494728X
11 The class NP Chapter 7. Sections 7.3. Introduction to the theory of computation. Michael Sipser. ISBN 053494728X
12 NP completeness Chapter 7. Sections 7.4. Introduction to the theory of computation. Michael Sipser. ISBN 053494728X
13 NP completeness Chapter 7. Sections 7.4. Introduction to the theory of computation. Michael Sipser. ISBN 053494728X
14 The clique problem Chapter 7. Sections 7.5. Introduction to the theory of computation. Michael Sipser. ISBN 053494728X
15 The subsetsum problem Chapter 7. Sections 7.5. Introduction to the theory of computation. Michael Sipser. ISBN 053494728X
16 Review of the Semester  

 

Course Notes/Textbooks Introduction to the theory of computation. Michael Sipser. ISBN 053494728X
Suggested Readings/Materials

 

EVALUATION SYSTEM

Semester Activities Number Weigthing
Participation
1
15
Laboratory / Application
Field Work
Quizzes / Studio Critiques
Homework / Assignments
Presentation / Jury
Project
Seminar / Workshop
Portfolios
Midterms / Oral Exams
2
50
Final / Oral Exam
1
35
Total

Weighting of Semester Activities on the Final Grade
3
65
Weighting of End-of-Semester Activities on the Final Grade
1
35
Total

ECTS / WORKLOAD TABLE

Semester Activities Number Duration (Hours) Workload
Course Hours
Including exam week: 16 x total hours
16
3
48
Laboratory / Application Hours
Including exam week: 16 x total hours
16
Study Hours Out of Class
15
8
Field Work
Quizzes / Studio Critiques
Homework / Assignments
Presentation / Jury
Project
Seminar / Workshop
Portfolios
Midterms / Oral Exams
2
13
Final / Oral Exam
1
16
    Total
210

 

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#
Program Competencies/Outcomes
* Contribution Level
1
2
3
4
5
1 Adequate knowledge in Mathematics, Science and Software Engineering; ability to use theoretical and applied information in these areas to model and solve Software Engineering problems
2 Ability to identify, define, formulate, and solve complex Software Engineering problems; ability to select and apply proper analysis and modeling methods for this purpose X
3 Ability to design, implement, verify, validate, measure and maintain a complex software system, process or product under realistic constraints and conditions, in such a way as to meet the desired result; ability to apply modern methods for this purpose X
4 Ability to devise, select, and use modern techniques and tools needed for Software Engineering practice X
5 Ability to design and conduct experiments, gather data, analyze and interpret results for investigating Software Engineering problems
6 Ability to work efficiently in Software Engineering disciplinary and multi-disciplinary teams; ability to work individually
7 Ability to communicate effectively in Turkish, both orally and in writing; knowledge of a minimum of two foreign languages
8 Recognition of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself
9 Awareness of professional and ethical responsibility X
10 Information about business life practices such as project management, risk management, and change management; awareness of entrepreneurship, innovation, and sustainable development X
11 Knowledge about contemporary issues and the global and societal effects of engineering practices on health, environment, and safety; awareness of the legal consequences of Software Engineering solutions X

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