Formal Languages and Automata (CMPE326) Course Detail

Course Name	Course Code	Season	Lecture Hours	Application Hours	Lab Hours	Credit	ECTS
Formal Languages and Automata	CMPE326	Area Elective	3	0	0	3	6

Pre-requisite Course(s)
CMPE251

Course Language	English
Course Type	Elective Courses
Course Level	Bachelor’s Degree (First Cycle)
Mode of Delivery	Face To Face
Learning and Teaching Strategies	Lecture.
Course Coordinator
Course Lecturer(s)
Course Assistants
Course Objectives	This course is designed to provide the skills to appreciate and understand the formal definition of computation, and language. The students will be introduced to the definitions and properties of mathematical models of computation with automata theory.
Course Learning Outcomes	The students who succeeded in this course; Use finite automata as a tool to describe computing Analyze grammars and languages as they are applied to computer languages Construct Push-down automata as a parsing tool of compilation Develop Turing machine models for computability Build theoretical machines or models for hardware and software
Course Content	Languages and their representations, finite automata and regular grammars, context-free grammars, concept of abstract machines and language acceptance, deterministic and non-deterministic finite state machines, pushdown automata, Turing machines and introduction to the theory of computation.

Weekly Subjects and Releated Preparation Studies

Week	Subjects	Preparation
1	Introduction	Chapters 0 (main text)
2	Regular Languages	Chapter 1
3	Finite Automata	Chapter 1.1
4	Nondeterminism	Chapter 1.2
5	Finite Automata with Output	(other sources 2)
6	Regular Expressions	Chapter 1.3
7	Context-Free Languages	Chapter 2
8	Context-Free Grammars	Chapter 2.1
9	Chomsky Normal Form	Chapter 2.1
10	Pushdown Automata	Chapter 2.2
11	Equivalence with Context-Free Grammars	Chapter 2.2
12	Computability Theory	Chapter 3
13	Turing Machines	Chapter 3.1
14	Variants of Turing Machines	Chapter 3.2
15	Review
16	Review

Sources

Course Book	1. Introduction to the Theory of Computation, Michael Sipser, 2nd Edition, Thomson Course Technology, 2006.
Other Sources	2. Efim Kinber and Carl Smith, Theory of Computing: A Gentle Introduction",Prentice-Hall, 2001. ISBN # 0-13-027961-7.
	3. Daniel I.A. Cohen, Introduction to Computer Theory (2nd Edition), Wiley, 1997, ISBN # 0-471-13772-3
	4. Yarımağan, Ünal, “Özdevinirler Kuramı ve Biçimsel Diller”, Bıçaklar Kitabevi, 2003, ISBN# 975-8695-05-3
	5. Martin, John C. “Introduction to Languages and the Theory of Computation”,(2nd Edition), McGraw-Hill International Editions, 1997, ISBN# 0-07-115468-X
	6. Linz, Peter, “An Introduction to Formal Languages and Automata”, Jones and Bartlett Publishers, 2001.

Evaluation System

Requirements	Number	Percentage of Grade
Attendance/Participation	-	-
Laboratory	-	-
Application	-	-
Field Work	-	-
Special Course Internship	-	-
Quizzes/Studio Critics	-	-
Homework Assignments	3	10
Presentation	-	-
Project	-	-
Report	-	-
Seminar	-	-
Midterms Exams/Midterms Jury	2	55
Final Exam/Final Jury	1	35
Toplam	6	100

Percentage of Semester Work	65
Percentage of Final Work	35
Total	100

Course Category

Core Courses	X
Major Area Courses
Supportive Courses
Media and Managment Skills Courses
Transferable Skill Courses

The Relation Between Course Learning Competencies and Program Qualifications

#	Program Qualifications / Competencies	Level of Contribution
#	Program Qualifications / Competencies	1	2	3	4	5
1	Acquires skills to use the advanced theoretical and applied knowledge obtained at the mathematics bachelors program to do further academic and scientific research in both mathematics-based graduate programs and public or private sectors.
2	Transplants and applies the theoretical and applicable knowledge gained in their field to the secondary education by using suitable tools and devices.
3	Acquires the skill of choosing, using and improving problem solving techniques which are needed for modeling and solving current problems in mathematics or related fields by using the obtained knowledge and skills.
4	Acquires analytical thinking and uses time effectively in the process of deduction.
5	Acquires basic software knowledge necessary to work in the computer science related fields and together with the skills to use information technologies effectively.					X
6	Obtains the ability to collect data, to analyze, interpret and use statistical methods necessary in decision making processes.
7	Acquires the level of knowledge to be able to work in the mathematics and related fields and keeps professional knowledge and skills up-to-date with awareness in the importance of lifelong learning.
8	Takes responsibility in mathematics related areas and has the ability to work affectively either individually or as a member of a team.
9	Has proficiency in English language and has the ability to communicate with colleagues and to follow the innovations in mathematics and related fields.
10	Has the ability to communicate ideas with peers supported by qualitative and quantitative data.
11	Has professional and ethical consciousness and responsibility which takes into account the universal and social dimensions in the process of data collection, interpretation, implementation and declaration of results in mathematics and its applications.

ECTS/Workload Table

Activities	Number	Duration (Hours)	Total Workload
Course Hours (Including Exam Week: 16 x Total Hours)	16	3	48
Laboratory
Application
Special Course Internship
Field Work
Study Hours Out of Class	16	1	16
Presentation/Seminar Prepration
Project
Report
Homework Assignments	3	2	6
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury	2	10	20
Prepration of Final Exams/Final Jury	1	15	15
Total Workload			105