ECTS - Formal Languages and Automata

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 3 0 0 3 6
Pre-requisite Course(s)
CMPE251
Course Language English
Course Type N/A
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
Major Area Courses
Supportive Courses X
Media and Managment Skills Courses
Transferable Skill Courses

The Relation Between Course Learning Competencies and Program Qualifications

# Program Qualifications / Competencies Level of Contribution
1 2 3 4 5
1 Adequate knowledge in mathematics, science and subjects specific to the software engineering discipline; the ability to apply theoretical and practical knowledge of these areas to complex engineering problems. X
2 The ability to identify, define, formulate and solve complex engineering problems; selecting and applying proper analysis and modeling techniques for this purpose. X
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. X
4 The ability to develop, select and utilize modern techniques and tools essential for the analysis and determination of complex problems in software engineering applications; the ability to utilize information technologies effectively.
5 The ability to gather data, analyze and interpret results for the investigation of complex engineering problems or research topics specific to the software engineering discipline.
6 The ability to work effectively in inter/inner disciplinary teams; ability to work individually.
7 Effective oral and written communication skills in Turkish; the ability to write effective reports and comprehend written reports, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions.
8 The knowledge of at least one foreign language; the ability to write effective reports and comprehend written reports, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions.
9 Recognition of the need for lifelong learning; the ability to access information and follow recent developments in science and technology with continuous self-development
10 The ability to behave according to ethical principles, awareness of professional and ethical responsibility.
11 Knowledge of the standards utilized in software engineering applications.
12 Knowledge on business practices such as project management, risk management and change management.
13 Awareness about entrepreneurship, and innovation.
14 Knowledge on sustainable development.
15 Knowledge of the effects of software engineering applications on the universal and social dimensions of health, environment, and safety.
16 Awareness of the legal consequences of engineering solutions.
17 An ability to apply algorithmic principles, mathematical foundations, and computer science theory in the modeling and design of computer-based systems with the trade-offs involved in design choices. X
18 The ability to apply engineering approach to the development of software systems by analyzing, designing, implementing, verifying, validating and maintaining software systems. X

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 3 48
Presentation/Seminar Prepration
Project
Report
Homework Assignments 3 6 18
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury 2 10 20
Prepration of Final Exams/Final Jury 1 15 15
Total Workload 149