| School/Faculty/Institute | Faculty of Engineering | ||||
| Course Code | MATH 321 | ||||
| Course Title in English | Automata Theory and Formal Language | ||||
| Course Title in Turkish | Biçimsel Diller ve Otomatlar Kuramı | ||||
| Language of Instruction | EN | ||||
| Type of Course | Flipped Classroom | ||||
| Level of Course | Introductory | ||||
| Semester | Fall | ||||
| Contact Hours per Week |
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| Estimated Student Workload | 160 hours per semester | ||||
| Number of Credits | 6 ECTS | ||||
| Grading Mode | Standard Letter Grade | ||||
| Pre-requisites | None | ||||
| Expected Prior Knowledge | Basic Discrete Mathematics and Data Structures Knowledge | ||||
| Co-requisites | None | ||||
| Registration Restrictions | Only Undergraduate Students | ||||
| Overall Educational Objective | To learn the fundamentals of theory of computation, basic graph theory and introductory discrete mathematics, learn the classification between classes of languages (regular, context-free, and more) and design grammars and machines that will generate/recognize these languages. | ||||
| Course Description | This course covers the fundamentals of theory of computation: basic graph theory, introductory discrete mathematics, regular languages, finite state machines, push-down automata, regular expressions, context-free grammars, Turing machines, decidability, reducibility, time complexity | ||||
| Course Description in Turkish | Bu derste, biçimsel diller ve otomatlar kuramının temel kavramları şu başlıklar altında işlenmektedir: temel çizge teorisi, sonlu küme matematiğine giriş, düzenli diller, sonlu durum makineleri, ters otomat, düzenli ifadeler, bağlama duyarsız gramerler, Turing makineleri, karar verilebilirlik, indirgenebilirlik, zaman karmaşıklığı |
Course Learning Outcomes and CompetencesUpon successful completion of the course, the learner is expected to be able to:1) know basic discrete mathematics and graph theory 2) identify finite state machines, regular languages, regular expressions, determinism and nondeterminism and their connection 3) know context-free languages, push-down automata and their connection 4) comprehend Turing machines, decidability and reducibility 5) apply new knowledge as needed, using appropriate learning strategies |
| Program Learning Outcomes/Course Learning Outcomes | 1 | 2 | 3 | 4 | 5 |
|---|---|---|---|---|---|
| 1) Thorough knowledge of the major concepts, theoretical perspectives, empirical findings, and historical trends in psychology. | |||||
| 2) Understanding of and ability to apply essential research methods in psychology, including research design, data analysis, and data interpretation. | |||||
| 3) Competence to use critical and creative thinking, skeptical inquiry and a scientific approach to solving problems related to behavior and mental processes. | |||||
| 4) Understanding and ability to apply psychological principles, skills and values in personal, social, and organizational contexts. | |||||
| 5) Ability to weigh evidence, to tolerate ambiguity, and to reflect other values that underpin psychology as a discipline. | |||||
| 6) Internalization and dissemination of professional ethical standards. | |||||
| 7) Demonstration of competence in information technologies, and the ability to use computer and other technologies for purposes related to the pursuit of knowledge in psychology and the broader social sciences. | |||||
| 8) Skills to communicate the knowledge of psychological science effectively, in a variety of formats, in both Turkish and in English (in English, at least CEFR B2 level). | |||||
| 9) Recognition, understanding, and respect for the complexity of sociocultural and international diversity. | |||||
| 10) Recognition for the need for, and the skills to pursue, lifelong learning, inquiry, and self-improvement. | |||||
| 11) Ability to formulate critical hypotheses based on psychological theory and literature, and design studies to test those hypotheses. | |||||
| 12) Ability to acquire knowledge independently, and to plan one’s own learning. | |||||
| 13) Demonstration of advanced competence in the clarity and composition of written work and presentations. |
| N None | S Supportive | H Highly Related |
| Program Outcomes and Competences | Level | Assessed by | |
| 1) | Thorough knowledge of the major concepts, theoretical perspectives, empirical findings, and historical trends in psychology. | N | |
| 2) | Understanding of and ability to apply essential research methods in psychology, including research design, data analysis, and data interpretation. | N | |
| 3) | Competence to use critical and creative thinking, skeptical inquiry and a scientific approach to solving problems related to behavior and mental processes. | H | Exam,HW,Participation |
| 4) | Understanding and ability to apply psychological principles, skills and values in personal, social, and organizational contexts. | N | |
| 5) | Ability to weigh evidence, to tolerate ambiguity, and to reflect other values that underpin psychology as a discipline. | N | |
| 6) | Internalization and dissemination of professional ethical standards. | N | |
| 7) | Demonstration of competence in information technologies, and the ability to use computer and other technologies for purposes related to the pursuit of knowledge in psychology and the broader social sciences. | N | |
| 8) | Skills to communicate the knowledge of psychological science effectively, in a variety of formats, in both Turkish and in English (in English, at least CEFR B2 level). | N | |
| 9) | Recognition, understanding, and respect for the complexity of sociocultural and international diversity. | S | Participation |
| 10) | Recognition for the need for, and the skills to pursue, lifelong learning, inquiry, and self-improvement. | S | HW,Participation |
| 11) | Ability to formulate critical hypotheses based on psychological theory and literature, and design studies to test those hypotheses. | N | |
| 12) | Ability to acquire knowledge independently, and to plan one’s own learning. | S | Exam,HW |
| 13) | Demonstration of advanced competence in the clarity and composition of written work and presentations. | H | Exam,HW |
| Prepared by and Date | ŞENİZ DEMİR , November 2023 |
| Course Coordinator | ŞENİZ DEMİR |
| Semester | Fall |
| Name of Instructor | Assoc. Prof. Dr. ŞENİZ DEMİR |
| Week | Subject |
| 1) | Basic Discrete Mathematics and Graph Theory |
| 2) | Basic Discrete Mathematics and Graph Theory |
| 3) | Finite State Machines and Regular Languages |
| 4) | Finite State Machines and Regular Languages |
| 5) | Nondeterminism and Regular Expressions |
| 6) | Equivalence of Regular Expressions and Finite State Machines |
| 7) | Nonregular Languages and Pumping Lemma |
| 8) | Nonregular Languages and Pumping Lemma |
| 9) | Context-Free Grammars and Ambiguity |
| 10) | Push-Down Automata |
| 11) | Non-Context-Free Languages and Pumping Lemma |
| 12) | Turing Machines |
| 13) | Turing Machines |
| 14) | Advanced Topics (Decidability, reducibility, time complexity) |
| 15) | Final Exam/Project/Presentation |
| 16) | Final Exam/Project/Presentation |
| Required/Recommended Readings | Introduction To The Theory Of Computation – Michael Sipser 3rd ed. | |||||||||||||||
| Teaching Methods | Flipped classroom. In-class flipped practices. | |||||||||||||||
| Homework and Projects | In-class flipped practices. No Project. | |||||||||||||||
| Laboratory Work | None | |||||||||||||||
| Computer Use | For in-class practices | |||||||||||||||
| Other Activities | None | |||||||||||||||
| Assessment Methods |
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| Course Administration |
demirse@mef.edu.tr 536 Instructor’s office: Room 535 (5th floor) Office hours: TBA. E-mail address: demirse@mef.edu.tr Rules for attendance: No attendance required. Missing an in-class practice: Provided that proper documents of excuse are presented, a make-up will be given to each missed practice. Missing a midterm: Provided that proper documents of excuse are presented, make-up for missed midterms will be given. Missing a final: No final exam. A reminder of proper classroom behavior, code |
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| Activity | No/Weeks | Hours | Calculation | ||||
| No/Weeks per Semester | Preparing for the Activity | Spent in the Activity Itself | Completing the Activity Requirements | ||||
| Course Hours | 14 | 3 | 3 | 84 | |||
| Quiz(zes) | 8 | 2 | 1 | 24 | |||
| Midterm(s) | 2 | 23 | 3 | 52 | |||
| Total Workload | 160 | ||||||
| Total Workload/25 | 6.4 | ||||||
| ECTS | 6 | ||||||