DEPARTMENT OF SOFTWARE ENGINEERING (ENGLISH)
Qualification Awarded	Program Süresi	Toplam Kredi (AKTS)	Öğretim Şekli	Yeterliliğin Düzeyi ve Öğrenme Alanı
Bachelor's (First Cycle) Degree	4	240	FULL TIME	TYÇ, TR-NQF-HE, EQF-LLL, ISCED (2011):Level 6 QF-EHEA:First Cycle TR-NQF-HE, ISCED (1997-2013): 48,52

Ders Genel Tanıtım Bilgileri

Course Code:

1413211001

Ders İsmi:

Data Structures

Ders Yarıyılı:

Fall

Ders Kredileri:

Theoretical	Practical	Labs	Credit	ECTS
3	0	0	3	7

Language of instruction:

Ders Koşulu:

Ders İş Deneyimini Gerektiriyor mu?:

Other Recommended Topics for the Course:

Type of course:

Necessary

Course Level:

Bachelor

TR-NQF-HE:6. Master`s Degree

QF-EHEA:First Cycle

EQF-LLL:6. Master`s Degree

Mode of Delivery:

Face to face

Course Coordinator :

Prof. Dr. Haluk GÜMÜŞKAYA

Course Lecturer(s):

Course Assistants:

Dersin Amaç ve İçeriği

Course Objectives:	The aim of the course is to provide students with knowledge and skills in the design, analysis and development of basic data structures.
Course Content:	Classification of data structures, introduction to algorithm and complexity analysis, basic data structures and derivatives such as lists, stacks, queues, trees, graphs and heaps, analysis of important sorting algorithms, emphasis on programming using dynamic memory allocation, practical exercises in laboratories and term project.

Learning Outcomes

The students who have succeeded in this course;

Learning Outcomes

1 - Knowledge
Theoretical - Conceptual
2 - Skills
Cognitive - Practical
3 - Competences
Communication and Social Competence
Learning Competence
1) Ability to analyze, design and implement lists, stacks, queues, trees, graphs and stacks; ability to use basic data structures for problem solving.
Field Specific Competence
1) Adequate knowledge in sequential algorithm analysis; Ability to analyze sequential algorithms.
2) Ability to use and compare data structures in different application areas.
Competence to Work Independently and Take Responsibility

Ders Akış Planı

Week	Subject	Related Preparation
1)	SORTING ALGORITHMS II	Data Structures – A Pseudocode Approach with C, R. Gillberg, B. Forouzan, Thomson Course Technology Second Edition
2)	RECOGNITION, ABSTRACT DATA STRUCTURES	Data Structures – A Pseudocode Approach with C, R. Gillberg, B. Forouzan, Thomson Course Technology Second Edition
3)	RECOGNITION, ABSTRACT DATA STRUCTURES	Data Structures – A Pseudocode Approach with C, R. Gillberg, B. Forouzan, Thomson Course Technology Second Edition
4)	Queue	Data Structures – A Pseudocode Approach with C, R. Gillberg, B. Forouzan, Thomson Course Technology Second Edition
5)	LINKED LISTS	Data Structures – A Pseudocode Approach with C, R. Gillberg, B. Forouzan, Thomson Course Technology Second Edition
6)	LINKED LISTS II	Data Structures – A Pseudocode Approach with C, R. Gillberg, B. Forouzan, Thomson Course Technology Second Edition
7)	GRAPH I	Data Structures – A Pseudocode Approach with C, R. Gillberg, B. Forouzan, Thomson Course Technology Second Edition
8)	mıdterm	Data Structures – A Pseudocode Approach with C, R. Gillberg, B. Forouzan, Thomson Course Technology Second Edition
9)	GRAPH II	Data Structures – A Pseudocode Approach with C, R. Gillberg, B. Forouzan, Thomson Course Technology Second Edition
10)	TREES	Data Structures – A Pseudocode Approach with C, R. Gillberg, B. Forouzan, Thomson Course Technology Second Edition
11)	BINARY SEARCH TREES	Data Structures – A Pseudocode Approach with C, R. Gillberg, B. Forouzan, Thomson Course Technology Second Edition
12)	PILES	Data Structures – A Pseudocode Approach with C, R. Gillberg, B. Forouzan, Thomson Course Technology Second Edition
13)	RANKING ALGORITHMS I	Data Structures – A Pseudocode Approach with C, R. Gillberg, B. Forouzan, Thomson Course Technology Second Edition
14)	RANKING ALGORITHMS II	Data Structures – A Pseudocode Approach with C, R. Gillberg, B. Forouzan, Thomson Course Technology Second Edition
15)	RANKING ALGORITHMS II	Data Structures – A Pseudocode Approach with C, R. Gillberg, B. Forouzan, Thomson Course Technology Second Edition
16)	Final	Data Structures – A Pseudocode Approach with C, R. Gillberg, B. Forouzan, Thomson Course Technology Second Edition

Sources

Course Notes / Textbooks:	Data Structures – A Pseudocode Approach with C, R. Gillberg, B. Forouzan, Thomson Course Technology Second Edition
References:	Data Structures – A Pseudocode Approach with C, R. Gillberg, B. Forouzan, Thomson Course Technology Second Edition

Ders - Program Öğrenme Kazanım İlişkisi

Ders Öğrenme Kazanımları	1	3	2
Program Outcomes
1) Knowledge of mathematics, science, basic engineering, computer computing, and engineering discipline-specific topics; ability to use this knowledge in solving complex engineering problems
2) Sufficient knowledge of issues related to software engineering; theoretical and To be able to use applied knowledge in solving algorithmic and software problems Skill.
3) Ability to define, formulate and analyze complex engineering problems using basic science, mathematics and engineering knowledge and taking into account the UN Sustainable Development Goals relevant to the problem under consideration.
4) Ability to design creative solutions to complex engineering problems; The ability to design complex systems, processes, devices or products to meet current and future requirements, taking into account realistic constraints and conditions.
5) Ability to choose and use appropriate techniques, resources, modern engineering computational tools for the analysis, solution, prediction and modelling of complex engineering problems.
6) Ability to use research methods to examine complex engineering problems, including researching literature, designing experiments, conducting experiments, collecting data, analyzing and interpreting results.
7) Information about the effects of engineering practices on society, health and safety, economy, sustainability and the environment within the scope of the UN Sustainable Development Goals; Awareness of the legal consequences of engineering solutions
8) Acting in accordance with engineering professional principles and knowledge about ethical responsibility; Awareness of acting impartially, without discrimination on any issue, and being inclusive of diversity.
9) Ability to work effectively as a team member or leader in intradisciplinary and multidisciplinary teams (face-to-face, remote or hybrid).
10) Individual working ability.
11) Ability to communicate effectively verbally and in writing on technical issues, taking into account the various differences of the target audience (such as education, language, profession).
12) Knowledge of business practices such as project management and economic feasibility analysis
13) Awareness about entrepreneurship and innovation.
14) A lifelong learning skill that includes being able to learn independently and continuously, adapting to new and developing technologies, and thinking inquisitively about technological changes.

Ders - Öğrenme Kazanımı İlişkisi

No Effect	1 Lowest	2 Low	3 Average	4 High	5 Highest

	Program Outcomes	Level of Contribution
1)	Knowledge of mathematics, science, basic engineering, computer computing, and engineering discipline-specific topics; ability to use this knowledge in solving complex engineering problems
2)	Sufficient knowledge of issues related to software engineering; theoretical and To be able to use applied knowledge in solving algorithmic and software problems Skill.
3)	Ability to define, formulate and analyze complex engineering problems using basic science, mathematics and engineering knowledge and taking into account the UN Sustainable Development Goals relevant to the problem under consideration.
4)	Ability to design creative solutions to complex engineering problems; The ability to design complex systems, processes, devices or products to meet current and future requirements, taking into account realistic constraints and conditions.
5)	Ability to choose and use appropriate techniques, resources, modern engineering computational tools for the analysis, solution, prediction and modelling of complex engineering problems.
6)	Ability to use research methods to examine complex engineering problems, including researching literature, designing experiments, conducting experiments, collecting data, analyzing and interpreting results.
7)	Information about the effects of engineering practices on society, health and safety, economy, sustainability and the environment within the scope of the UN Sustainable Development Goals; Awareness of the legal consequences of engineering solutions
8)	Acting in accordance with engineering professional principles and knowledge about ethical responsibility; Awareness of acting impartially, without discrimination on any issue, and being inclusive of diversity.
9)	Ability to work effectively as a team member or leader in intradisciplinary and multidisciplinary teams (face-to-face, remote or hybrid).
10)	Individual working ability.
11)	Ability to communicate effectively verbally and in writing on technical issues, taking into account the various differences of the target audience (such as education, language, profession).
12)	Knowledge of business practices such as project management and economic feasibility analysis
13)	Awareness about entrepreneurship and innovation.
14)	A lifelong learning skill that includes being able to learn independently and continuously, adapting to new and developing technologies, and thinking inquisitively about technological changes.

Öğrenme Etkinliği ve Öğretme Yöntemleri

Course
Labs
Homework

Ölçme ve Değerlendirme Yöntemleri ve Kriterleri

Yazılı Sınav (Açık uçlu sorular, çoktan seçmeli, doğru yanlış, eşleştirme, boşluk doldurma, sıralama)
Homework

Assessment & Grading

Semester Requirements	Number of Activities	Level of Contribution
Laboratory	10	% 10
Homework Assignments	10	% 10
Midterms	1	% 20
Semester Final Exam	1	% 60
total		% 100
PERCENTAGE OF SEMESTER WORK		% 40
PERCENTAGE OF FINAL WORK		% 60
total		% 100

İş Yükü ve AKTS Kredisi Hesaplaması

Activities	Number of Activities	Duration (Hours)	Workload
Course Hours	14	3	42
Laboratory	14	2	28
Study Hours Out of Class	14	4	56
Homework Assignments	10	2	20
Midterms	1	2	2
Final	1	3	3
Total Workload			151