COURSE INTRODUCTION AND APPLICATION INFORMATION

se.cs.ieu.edu.tr

Course Name

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

Prerequisites

CE 221

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

Course Language

Course Type

Required

Course Level

Mode of Delivery

Teaching Methods and Techniques of the Course

Course Coordinator

Doç. Dr. Cem EVRENDİLEK

Course Lecturer(s)

Assistant(s)

Araş. Gör. Onur ÇAĞIRICI

Course Objectives
Learning Outcomes	The students who succeeded in this course; be able to assess the relative advantages of using hashing or balanced tree implementations in efficiently solving search problems with concurrent insertion, and/or deletions on collections of data be able to use leftist heaps when efficient merging of heaps is needed be able to use the ultrafast disjoint set class for solving problems that rely on an efficient set implementation for their performance be able to model complex problems in terms of graphs be able to search for an efficient solution that is made possible by the applications of the graph algorithms be able to have awareness of the lower bound associated with sorting and the conditions in which it holds be able to describe the usage of various data structures be able to explain the operations for maintaining common data structures be able to design and apply appropriate data structures for solving computing problems be able to design simple algorithms for solving computing problems
Course Description

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

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week	Subjects	Required Materials
1	Hashing	Course Book (Ch. 5.1, 5.2, 5.3, 5.4.1)
2	Hashing	Course Book (Ch. 5.4.2, 5.4.3, 5.5, 5.6, 5.7)
3	Leftist Heaps	Course Book (Ch. 6.6)
4	Sorting (Indirect Sorting, Lower Bound for Sorting, Bucket Sort)	Course Book (Ch. 7.8, 7.9, 7.10)
5	Disjoint Set Class	Course Book (Ch. 8.1, 8.2, 8.3, 8.4, 8.5)
6	Disjoint Set Class	Course Book (Ch. 8.6, 8.7)
7	Midterm
8	Graphs: Topological Sorting	Course Book (Ch. 9.1, 9.2)
9	Graphs: Unweighted Shortest Paths, Dijkstra’s Algorithm	Course Book (Ch. 9.3.1, 9.3.2)
10	Graphs: Shortest Paths for graphs with negative edges and acyclic graphs	Course Book Ch. 9.3.3, 9.3.4, 9.3.5, 9.3.6)
11	Graphs: Maximum Flow Algorithm	Course Book (Ch. 9.4)
12	Graphs: Minimum Spanning Tree	Course Book (Ch. 9.5)
13	Graphs: Depth First Search, Connected Components, Biconnectivity	Course Book (Ch. 9.6.1, 9.6.2)
14	Graphs: Euler Circuits	Course Book (Ch. 9.6.3)
15	Graphs: Directed Graphs and Finding Strong Components	Course Book (Ch. 9.6.4, 9.6.5)
16	Review of the Semester

Course Notes/Textbooks	M. A. Weiss, Data Structures and Algorithm Analysis in C++, 3/e, AddisonWesley, 2006
Suggested Readings/Materials

EVALUATION SYSTEM

Semester Activities	Number	Weigthing
Participation
Laboratory / Application	6	30
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments	15	0
Presentation / Jury
Project
Seminar / Workshop
Oral Exam
Midterm	1	30
Final Exam	1	40
Total

Weighting of Semester Activities on the Final Grade		60
Weighting of End-of-Semester Activities on the Final Grade		40
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	2
Study Hours Out of Class	15	3
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments	15	3
Presentation / Jury
Project
Seminar / Workshop
Oral Exam
Midterms	1	12
Final Exams	1	20
		Total	202

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		X
3	Be able to develop software by coding, verifying, doing unit testing and debugging					X
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		X
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			X
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		X
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