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:

1413211003

Ders İsmi:

Theory of Computation

Ders Yarıyılı:

Fall

Ders Kredileri:

Theoretical	Practical	Labs	Credit	ECTS
3	0	0	3	5

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 Adem ÖZYAVAŞ

Course Lecturer(s):

Course Assistants:

Dersin Amaç ve İçeriği

Course Objectives:

The aim of this course is to introduce students to the mathematical foundations of computation, including automata theory and the theory of formal languages and grammars; At the same time, automata, equivalent regular expressions, equivalence of languages defined by automatons, regular expressions, pushdown automaton, equivalent context-free grammars, equivalent of languages defined by pushdown automata, context. equivalence of languages defined by free grammars, Turing machines, and Turing machines.

Course Content:

Course Content Mathematical Tools (Definitions, Theorems and Proofs); Types of Proof; Regular Languages; Finite Automata; Nondeterministic Machines; Regular Expressions; Irregular Languages; Context-free Languages; Context-free Grammars; Press Automatic; Turing Machines; Types of Turing Machines; Definition of "Algorithm"; Decision Making; Decidable Languages; NP-integrity; Reducibility; Recognizability.

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
Field Specific Competence
1) Students will be able to analyze finite automata, deterministic and non-deterministic automata, regular expressions, push automata, turing machines, formal languages and grammars.
2) Students will be able to design for finite automata, deterministic and non-deterministic automata, regular expressions, push automata, turing machines, formal languages and grammars.
3) Students will demonstrate an understanding of key concepts such as algorithm, computability, decidability, and complexity through problem solving.
4) Students will become familiar with Turing Machines and Problem Classes.
5) Students will develop their problem posing and solving skills.
6) Students will be able to prove the basic results of the Theory of Computation.
Competence to Work Independently and Take Responsibility

Ders Akış Planı

Week	Subject	Related Preparation
1)	Formation of preliminary concepts, mathematical tools, definitions, theorems and proofs, types of proofs	Data Structures – A Pseudocode Approach with C, R. Gillberg, B. Forouzan, Thomson Course Technology Second Edition
2)	Deterministic finite automata (DFA)	Data Structures – A Pseudocode Approach with C, R. Gillberg, B. Forouzan, Thomson Course Technology Second Edition
3)	Non-deterministic finite automata (NFA)	Data Structures – A Pseudocode Approach with C, R. Gillberg, B. Forouzan, Thomson Course Technology Second Edition
4)	Equivalence of DFA and NFA and regular expressions	Data Structures – A Pseudocode Approach with C, R. Gillberg, B. Forouzan, Thomson Course Technology Second Edition
5)	Epsilon transition, pumping Lemma, pigeon principle and closure features	Data Structures – A Pseudocode Approach with C, R. Gillberg, B. Forouzan, Thomson Course Technology Second Edition
6)	Optimal DFA and overview	Data Structures – A Pseudocode Approach with C, R. Gillberg, B. Forouzan, Thomson Course Technology Second Edition
7)	Context-free languages, context-free grammars, parse tree, ambiguity, closure properties	Data Structures – A Pseudocode Approach with C, R. Gillberg, B. Forouzan, Thomson Course Technology Second Edition
8)
9)
10)	Overview of context-free grammars and the Church-Turing hypothesis	Data Structures – A Pseudocode Approach with C, R. Gillberg, B. Forouzan, Thomson Course Technology Second Edition
11)	Stacked Vending Machines	Data Structures – A Pseudocode Approach with C, R. Gillberg, B. Forouzan, Thomson Course Technology Second Edition
12)	Overview of context-free grammars and the Church-Turing hypothesis
13)	Turing Machines, Recognition and Computation, Church-Turing Hypothesis	Data Structures – A Pseudocode Approach with C, R. Gillberg, B. Forouzan, Thomson Course Technology Second Edition
14)	Turing Machines, Recognition and Computation, Church-Turing Hypothesis
15)	NP-completeness, decidability, reducibility and recognizability	Data Structures – A Pseudocode Approach with C, R. Gillberg, B. Forouzan, Thomson Course Technology Second Edition
16)		Data Structures – A Pseudocode Approach with C, R. Gillberg, B. Forouzan, Thomson Course Technology Second Edition

Sources

Course Notes / Textbooks:	Michael Sipser, Introduction to the Theory of Computation, Cengage Learning, 3rd Edition, 2012 Daniel I. A. Cohen, Introduction to Computer Theory, Prentice-Hall, 2nd Edition, 1997
References:	Michael Sipser, Introduction to the Theory of Computation, Cengage Learning, 3rd Edition, 2012 Daniel I. A. Cohen, Introduction to Computer Theory, Prentice-Hall, 2nd Edition, 1997

Ders - Program Öğrenme Kazanım İlişkisi

Ders Öğrenme Kazanımları	1	2	3	4	5	6
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.	4
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.
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.	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.

Öğrenme Etkinliği ve Öğretme Yöntemleri

Ölçme ve Değerlendirme Yöntemleri ve Kriterleri

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

Assessment & Grading

Semester Requirements	Number of Activities	Level of Contribution
Quizzes	3	% 30
Midterms	1	% 30
Semester Final Exam	1	% 40
total		% 100
PERCENTAGE OF SEMESTER WORK		% 60
PERCENTAGE OF FINAL WORK		% 40
total		% 100

İş Yükü ve AKTS Kredisi Hesaplaması

Activities	Number of Activities	Duration (Hours)	Workload
Course Hours	12	3	36
Study Hours Out of Class	6	3	18
Quizzes	2	10	20
Midterms	1	25	25
Final	1	35	35
Total Workload			134