Course Name 
Discrete Structures in Computer Science

Code

Semester

Theory
(hour/week) 
Application/Lab
(hour/week) 
Local Credits

ECTS

CE 215

Fall

3

0

3

6

Prerequisites 
None


Course Language 
English


Course Type 
Required


Course Level 
First Cycle


Course Coordinator  
Course Lecturer(s)  
Assistant(s)   
Course Objectives  This course seeks to place on solid foundations the most common structures of computer science, to illustrate proof techniques, to provide the background for an introductory course in computational theory, and to introduce basic concepts of probability theory. 
Course Description 
The students who succeeded in this course;

Course Content  Topics include Boolean algebras, logic, set theory, relations and functions, graph theory, counting, combinatorics, and basic probability theory. 

Core Courses 
X

Major Area Courses  
Supportive Courses  
Media and Management Skills Courses  
Transferable Skill Courses 
Week  Subjects  Related Preparation 
1  Logic: Propositional Logic  Rosen, Discrete Mathematics and Its Applications, Chapter 1, Sections 1.1  1.3 
2  Logic: Predicate Logic  Rosen, Discrete Mathematics and Its Applications, Chapter 1, Sections 1.4, 1.5 
3  Logic: Logic and Proofs  Rosen, Discrete Mathematics and Its Applications, Chapter 1, Sections 1.6, 1.8, 1.9 
4  Sets, Functions  Rosen, Discrete Mathematics and Its Applications, Chapter 2, Sections 2.12.3 
5  Sequences and Sums  Rosen, Discrete Mathematics and Its Applications, Chapter 2, Section 2.4, 2.5 
6  Number Theory: Divisibility  Rosen, Discrete Mathematics and Its Applications, Chapter 4, Sections 4.1, 4.2 
7  Midterm Review  
8  MIDTERM  
9  Number Theory: Primes  Rosen, Discrete Mathematics and Its Applications, Chapter 4, Sections 4.34.5 
10  Mathematical Induction  Rosen, Discrete Mathematics and Its Applications, Chapter 5, Sections 5.1, 5.2 
11  Counting  Rosen, Discrete Mathematics and Its Applications, Chapter 6, Sections 6.16.4, Chapter 8, Section 8.5 
12  Discrete Probability  Rosen, Discrete Mathematics and Its Applications, Chapter 7 
13  Relations  Rosen, Discrete Mathematics and Its Applications, Chapter 9, Sections 9.1, 9.3, 9.5, 9.6 
14  Coding Theory  Rosen, Discrete Mathematics and Its Applications, Chapter 12, Section 12.6 
15  Graphs & Trees  Rosen, Discrete Mathematics and Its Applications, Chapter 10, Sections 10.110.3, Chapter 11, 11.1, 11.2 
16  Semester Review 
Course Notes/Textbooks  Discrete Mathematics and Its Applications, Kenneth H. Rosen, 7th edition, McGraw Hill, 2013 
Suggested Readings/Materials  Discrete and combinatorial mathematics: an applied introduction. R.P. Grimaldi. Fifth Edition. ISBN: 0321211030 Discrete Mathematics for Computer Scientists, J.K. Truss, 2nd edition, Pearson, 1999 
Semester Activities  Number  Weigthing 
Participation  
Laboratory / Application  
Field Work  
Quizzes / Studio Critiques  
Homework / Assignments 
10

25

Presentation / Jury  
Project  
Seminar / Workshop  
Portfolios  
Midterms / Oral Exams 
1

30

Final / Oral Exam 
1

45

Total 
Weighting of Semester Activities on the Final Grade  11 
55 
Weighting of EndofSemester Activities on the Final Grade  1 
45 
Total 
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 
16

4


Field Work  
Quizzes / Studio Critiques  
Homework / Assignments 
10

3


Presentation / Jury  
Project  
Seminar / Workshop  
Portfolios  
Midterms / Oral Exams 
1

14


Final / Oral Exam 
1

24


Total 
180

#

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  X  
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  
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 multidisciplinary 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  
10  Information about business life practices such as project management, risk management, and change management; awareness of entrepreneurship, innovation, and sustainable development  
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 
*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest