Computer Engineering (English)
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

General course introduction information

Course Code:

CENG313

Course Name:

Automata Theory

Course Semester:

Fall

Course Credits:

Theoretical	Practical	Credit	ECTS
3	0	3	5

Language of instruction:

Course Requisites:

CENG108 - Discrete Structures | CENG110 - Discrete Structures

Does the Course Require Work Experience?:

Type of course:

Compulsory

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. SEMİH BİLGEN

Course Lecturer(s):

Prof. Dr. SEMİH BİLGEN

Course Assistants:

Course Objective and Content

Course Objectives:

At the end of the course the student will be able to:
• Understand and elaborate on the mathematical definition of a Finite State Machine (FSM).
• Simplify a given regular expression (RE) and derive the FSM that accepts the language represented by it.
• Given an FSM, derive the RE that it accepts.
• Given a non-deterministic FSM, derive the deterministic FSM that accepts the same language.
• Given a RL, constructing the FSM that will accept it.
• Use the Pumping Lemma to show that a given language is NOT regular, and so, not acceptable by a FSM.

Course Content:

This course aims to introduce students to the fundamentals of formal languages and the theory of computation.

Learning Outcomes

The students who have succeeded in this course;

Learning Outcomes

1 - Knowledge
Theoretical - Conceptual
1) Recognition of the Finite State Machine model, representation of intelligent systems as FSMs; being able to analyze how a given FSM works.
2 - Skills
Cognitive - Practical
1) 2.1) Being able to differentiate Deterministic and Non-Deterministics FSMS; being able to convert a given NFSM to a DFSM
2) Understanding the concepts of Formal Language and Regular Language; being able to determine the FSM that recognizes a given regular language, and the regular language recognized by a given FSM
3) Understanding the concept of a formal grammar; being able to go back and forth among regular grammar, regular language and FSM; being able to determine the regular language generated by a given regular grammar and be,ng able to construct an FSM that will recognize that regular language
3 - Competences
Communication and Social Competence
Learning Competence
Field Specific Competence
Competence to Work Independently and Take Responsibility

Lesson Plan

Week	Subject	Related Preparation
1)	• Introduction and course overview
2)	• Formal languages
3)	Identify regular languages (RL), use regular espressions to represent regular languages, determine the regular language represented by a given regular expression
4)	Identify regular languages (RL), use regular espressions to represent regular languages, determine the regular language represented by a given regular expression
5)	• Deterministic FSM’s • Correspondence of FSM’s with regular languages
6)	• Deterministic FSM’s • Correspondence of FSM’s with regular languages
7)	• Identify and trace the behaviour of Non-Deterministic FSM’s (NFSM) • Determine the RL accepted by a given NFSM
8)	Midterm exam
9)	• Recognition and tracing the behaviour of Λ-NFSM’s • Determine the RL accepted by a given Λ-NFSM • Construction of equivalent non-Λ-NFSMs • Construction of equivalent DFSM’s.
10)	• Recognition and tracing the behaviour of Λ-NFSM’s • Determine the RL accepted by a given Λ-NFSM • Construction of equivalent non-Λ-NFSMs • Construction of equivalent DFSM’s.
11)	• Given a RL, constructing the Λ-NFSM to accept it • Convert Λ-NFSM to NFSM and to DFSM
12)	• Given a RL, constructing the Λ-NFSM to accept it • Convert Λ-NFSM to NFSM and to DFSM
13)	• Non regular languages • Pumping Lemma • Using the PL to show that a language is NOT regular
14)	• Non regular languages • Pumping Lemma • Using the PL to show that a language is NOT regular
15)	Final exam

Sources

Course Notes / Textbooks:	O'LEARN sistemindedir.
References:	J. Martin, Introduction to Languages and the Theory of Computation, Mc Graw-Hill, Ed.3 (2003) or Ed. 4 (2010)

Course-Program Learning Outcome Relationship

Learning Outcomes	1		3	4
Program Outcomes
1) Sufficient knowledge in mathematics, science and engineering related to their branches; the ability to apply theoretical and practical knowledge in these areas to model and solve engineering problems.
2) The ability to identify, formulate, and solve complex engineering problems; selecting and applying appropriate analysis and modeling methods for this purpose.
3) The ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; the ability to apply modern design methods for this purpose. (Realistic constraints and conditions include such issues as economy, environmental issues, sustainability, manufacturability, ethics, health, safety, social and political issues, according to the nature of design.)
4) Ability to develop, select and use modern techniques and tools necessary for engineering applications; ability to use information technologies effectively.
5) Ability to design experiments, conduct experiments, collect data, analyze and interpret results for examination of engineering problems.
6) The ability to work effectively in disciplinary and multidisciplinary teams; individual work skill.
7) Effective communication skills in Turkish oral and written communication; at least one foreign language knowledge.
8) Awareness of the need for lifelong learning; access to knowledge, ability to follow developments in science and technology, and constant self-renewal.
9) Professional and ethical responsibility.
10) Information on project management and practices in business life such as risk management and change management; awareness about entrepreneurship, innovation and sustainable development.
11) Information on the effects of engineering applications on health, environment and safety in the universal and social dimensions and the problems of the times; awareness of the legal consequences of engineering solutions.

Course - Learning Outcome Relationship

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

	Program Outcomes	Level of Contribution
1)	Sufficient knowledge in mathematics, science and engineering related to their branches; the ability to apply theoretical and practical knowledge in these areas to model and solve engineering problems.
2)	The ability to identify, formulate, and solve complex engineering problems; selecting and applying appropriate analysis and modeling methods for this purpose.
3)	The ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; the ability to apply modern design methods for this purpose. (Realistic constraints and conditions include such issues as economy, environmental issues, sustainability, manufacturability, ethics, health, safety, social and political issues, according to the nature of design.)
4)	Ability to develop, select and use modern techniques and tools necessary for engineering applications; ability to use information technologies effectively.
5)	Ability to design experiments, conduct experiments, collect data, analyze and interpret results for examination of engineering problems.
6)	The ability to work effectively in disciplinary and multidisciplinary teams; individual work skill.
7)	Effective communication skills in Turkish oral and written communication; at least one foreign language knowledge.
8)	Awareness of the need for lifelong learning; access to knowledge, ability to follow developments in science and technology, and constant self-renewal.
9)	Professional and ethical responsibility.
10)	Information on project management and practices in business life such as risk management and change management; awareness about entrepreneurship, innovation and sustainable development.
11)	Information on the effects of engineering applications on health, environment and safety in the universal and social dimensions and the problems of the times; awareness of the legal consequences of engineering solutions.

Learning Activity and Teaching Methods

Expression
Lesson
Reading
Homework
Problem Solving
Q&A / Discussion
Web Based Learning

Assessment & Grading Methods and Criteria

Written Exam (Open-ended questions, multiple choice, true-false, matching, fill in the blanks, sequencing)

Assessment & Grading

Semester Requirements	Number of Activities	Level of Contribution
Quizzes	1	% 32
Midterms	1	% 30
Final	1	% 38
total		% 100
PERCENTAGE OF SEMESTER WORK		% 62
PERCENTAGE OF FINAL WORK		% 38
total		% 100

Workload and ECTS Credit Grading

Activities	Number of Activities	Duration (Hours)	Workload
Course Hours	14	3	42
Study Hours Out of Class	14	6	84
Quizzes	8	1	8
Midterms	1	2	2
Final	1	2	2
Total Workload			138