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:

1400221026

Ders İsmi:

Design and Analysis of Algorithms

Ders Yarıyılı:

Spring

Ders Kredileri:

Theoretical	Practical	Labs	Credit	ECTS
3	0	0	3	6

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 :

Dr.Öğr.Üyesi Recep DURANAY

Course Lecturer(s):

Course Assistants:

Dersin Amaç ve İçeriği

Course Objectives:	The aim of this course is to provide students with the knowledge and skills to design programming languages using modern design methods and to implement the designed languages using modern development tools.
Course Content:	Algorithm design concepts and knowledge of algorithm complexity analysis, solving and proving recursive equations, formal and heuristic introduction to level and growth rate, brute force approach, divide and conquer approach, dynamic programming, greedy approach, graph algorithms and NP theory.

Learning Outcomes

The students who have succeeded in this course;

Learning Outcomes

1 - Knowledge
Theoretical - Conceptual
1) Adequate knowledge of algorithm design techniques and algorithmic solutions of basic problems
2 - Skills
Cognitive - Practical
1) Ability to use design techniques to model and solve problems; Ability to adapt basic algorithms to complex problems.
3 - Competences
Communication and Social Competence
Learning Competence
1) Adequate knowledge in algorithm analysis; ability to analyze sequential and recursive algorithms using theoretical and experimental methods; Adequate knowledge of NP theory
Field Specific Competence
Competence to Work Independently and Take Responsibility

Ders Akış Planı

Week	Subject	Related Preparation
1)	THEORETICAL INFRASTRUCTURE	Neapolitan, and K. Naimipour, Foundations of Algorithms
2)	EFFICIENCY, ANALYSIS AND GROWTH RATE	Neapolitan, and K. Naimipour, Foundations of Algorithms
3)	RECURSION	Neapolitan, and K. Naimipour, Foundations of Algorithms
4)	RECURSION II	Neapolitan, and K. Naimipour, Foundations of Algorithms
5)	ROUGH FORCE ALGORITHMS	Neapolitan, and K. Naimipour, Foundations of Algorithms
6)	DIVIDE AND CONQUER I	Neapolitan, and K. Naimipour, Foundations of Algorithms
7)	DIVIDE AND CONQUER II	Neapolitan, and K. Naimipour, Foundations of Algorithms
8)	MIDTERM	Neapolitan, and K. Naimipour, Foundations of Algorithms
9)	DYNAMIC PROGRAMMING I	Neapolitan, and K. Naimipour, Foundations of Algorithms
10)	DYNAMIC PROGRAMMING II	Neapolitan, and K. Naimipour, Foundations of Algorithms
11)	GREEDY APPROACH	Neapolitan, and K. Naimipour, Foundations of Algorithms
12)	GRAPH ALGORITHMS	Neapolitan, and K. Naimipour, Foundations of Algorithms
13)	GRAPH ALGORITHMS II	Neapolitan, and K. Naimipour, Foundations of Algorithms
14)	REVIEW	Neapolitan, and K. Naimipour, Foundations of Algorithms
15)	REVIEW	Neapolitan, and K. Naimipour, Foundations of Algorithms
16)	FINAL	Neapolitan, and K. Naimipour, Foundations of Algorithms

Sources

Course Notes / Textbooks:	Neapolitan, and K. Naimipour, Foundations of Algorithms
References:	Neapolitan, and K. Naimipour, Foundations of Algorithms

Ders - Program Öğrenme Kazanım İlişkisi

Ders Öğrenme Kazanımları	1	2	3
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	5
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.	5
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
5)	Ability to choose and use appropriate techniques, resources, modern engineering computational tools for the analysis, solution, prediction and modelling of complex engineering problems.	5
6)	Ability to use research methods to examine complex engineering problems, including researching literature, designing experiments, conducting experiments, collecting data, analyzing and interpreting results.	3
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.	5
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.	3

Öğrenme Etkinliği ve Öğretme Yöntemleri

Course
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
Homework Assignments	1	% 10
Midterms	1	% 30
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
Study Hours Out of Class	14	5	70
Homework Assignments	10	2	20
Midterms	1	2	2
Final	1	3	3
Total Workload			137