M.SC. in Computer Engineering (Without Thesis)

CE 611 | Course Introduction and Application Information

Course Name

Design Patterns and Code Refactoring

Code	Semester	Theory (hour/week)	Application/Lab (hour/week)	Local Credits	ECTS
CE 611	Fall/Spring	3	0	3	7.5

Prerequisites	None
Course Language	English
Course Type	Elective
Course Level	Third Cycle
Mode of Delivery	-
Teaching Methods and Techniques of the Course	-
National Occupation Classification	-
Course Coordinator	-
Course Lecturer(s)	Doç. Dr. Kaya OĞUZ Yrd. Doç. Dr. Ufuk ÇELİKKAN
Assistant(s)	-

Course Objectives

The goal of this course is an in depth study of design patterns and code refactoring. Design Patterns enable software professionals to avoid designing solutions from scratch which have been worked before, while refactoring studies techniques to root out bugs and identify and correct poorly structured code without changing the external behavior of the system. Design patterns improve the design “before code is written”, refactoring improves the design “after code is written”. Both design patterns and refactoring techniques allow the development of complex maintainable and extensible software systems. The pros and cons of each technique will be discussed and the students shall get an opportunity to apply these techniques through hands-on assignments

Learning Outcomes

#	Content	PC Sub	* Contribution Level
#	Content	PC Sub	1	2	3	4	5
1	describe the form and content of design patterns,
2	determine what is not included in the patterns and how they fit into software design,
3	identify and choose the appropriate design pattern and apply it to software solutions,
4	use refactoring to improve design and make existing applications more maintainable and extendible,
5	choose the appropriate type of refactoring technique to solve specific problems.

Course Description

This course is an in depth study of design patterns and code refactoring techniques which is used to develop complex, maintainable and extendible sofware systems.

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

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week	Subjects	Related Preparation	Learning Outcome
1	Introduction to Software, Software Design, UML, Design Patterns, and Refactoring	Chapter 1 Design Patterns.
2	Structural Design Patterns 1	-
3	Structural Design Patterns 2	-
4	Creational Design Patterns 1	-
5	Creational Design Patterns 2	-
6	Behavioral Design Patterns 1	-
7	Behavioral Design Patterns 2
8	Presentation 1 - Patterns in the Literature
9	Midterm	-
10	Test Driven Development	-
11	Refactoring 1	-
12	Refactoring 2	-
13	Refactoring 3
14	Presentation 2 - Refactoring in the Literature
15	Review
16	Final

Course Notes/Textbooks	“Design patterns: Elements of Reusable Object-Oriented Software” by E. Gamma, R. Helm, R. Johnson and J. Vlissides.Addison-Wesley. 1995. ISBN-13: 978-0-201-63361, ISBN-10: 0-201-63361-2 “Refactoring, Improving the design of existing code” by Martin Fowler, Kent Beck, John Brant, William Opdyke, Don Roberts. 1999 ISBN-13: 978-0-201-48567-7, ISBN-10: 0-201-48567-2
Suggested Readings/Materials	Instructor slides.

EVALUATION SYSTEM

Semester Activities	Number	Weighting	LO 1	LO 2	LO 3	LO 4	LO 5
Participation
Laboratory / Application
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments	2	10
Presentation / Jury	2	10
Project	1	20
Seminar / Workshop
Oral Exams
Midterm	1	20
Final Exam	1	40
Total

Weighting of Semester Activities on the Final Grade	3	70
Weighting of End-of-Semester Activities on the Final Grade	1	30
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		0
Study Hours Out of Class	14	4	56
Field Work			0
Quizzes / Studio Critiques			0
Portfolio			0
Homework / Assignments	2	10	20
Presentation / Jury	2	20	40
Project	1	20	20
Seminar / Workshop			0
Oral Exam			0
Midterms	1	21	21
Final Exam	1	40	40
		Total	245

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#	PC Sub	Program Competencies/Outcomes	* Contribution Level
#	PC Sub	Program Competencies/Outcomes	1	2	3	4	5
1	Accesses information in breadth and depth by conducting scientific research in Computer Engineering, evaluates, interprets and applies information.		-	-	-	-	-
2	Is well-informed about contemporary techniques and methods used in Computer Engineering and their limitations.		-	-	-	-	-
3	Uses scientific methods to complete and apply information from uncertain, limited or incomplete data, can combine and use information from different disciplines.		-	-	-	-	-
4	Is informed about new and upcoming applications in the field and learns them whenever necessary.		-	-	-	-	-
5	Defines and formulates problems related to Computer Engineering, develops methods to solve them and uses progressive methods in solutions.		-	-	-	-	-
6	Develops novel and/or original methods, designs complex systems or processes and develops progressive/alternative solutions in designs.		-	-	-	-	-
7	Designs and implements studies based on theory, experiments and modelling, analyses and resolves the complex problems that arise in this process.		-	-	-	-	-
8	Can work effectively in interdisciplinary teams as well as teams of the same discipline, can lead such teams and can develop approaches for resolving complex situations, can work independently and takes responsibility.		-	-	-	-	-
9	Engages in written and oral communication at least in Level B2 of the European Language Portfolio Global Scale.		-	-	-	-	-
10	Communicates the process and the results of his/her studies in national and international venues systematically, clearly and in written or oral form.		-	-	-	-	-
11	Is knowledgeable about the social, environmental, health, security and law implications of Computer Engineering applications, knows their project management and business applications, and is aware of their limitations in Computer Engineering applications.		-	-	-	-	-
12	Highly regards scientific and ethical values in data collection, interpretation, communication and in every professional activity.		-	-	-	-	-