COURSE INTRODUCTION AND APPLICATION INFORMATION

se.cs.ieu.edu.tr

Course Name

Code	Semester	Theory (hour/week)	Application/Lab (hour/week)	Local Credits	ECTS
	Fall/Spring

Prerequisites

ISE 204

To succeed (To get a grade of at least DD)

Course Language

Course Type

Elective

Course Level

Mode of Delivery

Teaching Methods and Techniques of the Course

Course Coordinator

Doç. Dr. Selin ÖZPEYNİRCİ

Course Lecturer(s)

Assistant(s)

Course Objectives
Learning Outcomes	The students who succeeded in this course; Will be able to understand combinatorial problems and their properties Will be able to solve combinational problems using basic counting techniques Will be able to identify famous combinatorial optimization problems Will be able to use the mathematical techniques and heuristics related to famous combinatorial optimization problems Will be able to apply simple algorithms involving combinatorial applications in graph theory, trees and searching, and networks
Course Description

Course Category	Core Courses
	Major Area Courses
	Supportive Courses
	Media and Managment Skills Courses
	Transferable Skill Courses

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week	Subjects	Required Materials
1	What is Combinatorics?
2	Introduction to Counting	Reading the slides supplied by the instructor Inroduction to Basic Counting Rules
3	Basic counting rules I	Reading the slides supplied by the instructor Basic Counting Rules
4	Basic counting rules II	Reading the slides supplied by the instructor Basic Counting Rules
5	Basic counting rules III	Reading the slides supplied by the instructor Basic Counting Rules
6	Recurrence relations I	Reading the slides supplied by the instructor Recurrence relations
7	Recurrence relations II	Reading the slides supplied by the instructor Recurrence relations
8	Midterm Exam
9	Graph Theory I Famous Problems in Combinatorial Optimization I	Reading the slides supplied by the instructor Graph Theory
10	Graph Theory II Famous Problems in Combinatorial Optimization II	Reading the slides supplied by the instructor Graph Theory
11	Graph Theory III Famous Problems in Combinatorial Optimization III	Reading the slides supplied by the instructor Graph Theory
12	Graph Theory IV Famous Problems in Combinatorial Optimization IV	Reading the slides supplied by the instructor Graph Theory
13	Computational Complexity, Analysis of algorithms	Reading the slides supplied by the instructor Computational Complexity
14	Optimization Methods Famous Problems in Combinatorial Optimization V	Reading the slides supplied by the instructor Optimization Methods
15	Midterm Exam
16	Review of the Semester

Course Notes/Textbooks

Suggested Readings/Materials

Introductory Combinatorics, R.A. Brualdi, Prentice Hall, NJ, 1999 Applied Combinatorics, F.S. Roberts, Prentice Hall, NJ, 1984 Applied Combinatorics, A. Tucker, John Wiley & Sons, NY, 1984 A Friendly Introduction to Graph Theory, F. Buckley and M. Lewinter, Prentice Hall, NJ, 2002 Discrete and Combinatorial Mathematics: An Applied Introduction, Fifth Edition. Ralph P. Grimaldi, Addison Wesley, 2003. Combinatorial Optimization: Algorithms and Complexity, Christos H. Papadimitriou and Kenneth Steiglitz, Dover Publications, 1998. Lecture handouts.

EVALUATION SYSTEM

Semester Activities	Number	Weigthing
Participation	1	10
Laboratory / Application
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments	1	20
Presentation / Jury
Project
Seminar / Workshop
Oral Exam
Midterm	2	70
Final Exam
Total

Weighting of Semester Activities on the Final Grade		100
Weighting of End-of-Semester Activities on the Final Grade
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	14	1
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments	1	18
Presentation / Jury
Project
Seminar / Workshop
Oral Exam
Midterms	2	20
Final Exams
		Total	120

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#	Program Competencies/Outcomes	* Contribution Level
#	Program Competencies/Outcomes	1	2	3	4	5
1	Be able to define problems in real life by identifying functional and nonfunctional requirements that the software is to execute
2	Be able to design and analyze software at component, subsystem, and software architecture level
3	Be able to develop software by coding, verifying, doing unit testing and debugging
4	Be able to verify software by testing its behaviour, execution conditions, and expected results
5	Be able to maintain software due to working environment changes, new user demands and the emergence of software errors that occur during operation
6	Be able to monitor and control changes in the software, the integration of software with other software systems, and plan to release software versions systematically
7	To have knowledge in the area of software requirements understanding, process planning, output specification, resource planning, risk management and quality planning
8	Be able to identify, evaluate, measure and manage changes in software development by applying software engineering processes
9	Be able to use various tools and methods to do the software requirements, design, development, testing and maintenance
10	To have knowledge of basic quality metrics, software life cycle processes, software quality, quality model characteristics, and be able to use them to develop, verify and test software
11	To have knowledge in other disciplines that have common boundaries with software engineering such as computer engineering, management, mathematics, project management, quality management, software ergonomics and systems engineering			X
12	Be able to grasp software engineering culture and concept of ethics, and have the basic information of applying them in the software engineering
13	Be able to use a foreign language to follow related field publications and communicate with colleagues				X

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