COURSE INFORMATION Course Title: THEORY OF COMPUTATION

Code	Course Type	Regular Semester	Theory	Practice	Lab	Credits	ECTS
CEN 350	C	5	2	2	0	3	6

Academic staff member responsible for the design of the course syllabus (name, surname, academic title/scientific degree, email address and signature)	NA
Lecturer (name, surname, academic title/scientific degree, email address and signature) and Office Hours:	Enea Mançellari , 10:00 - 12:00
Second Lecturer(s) (name, surname, academic title/scientific degree, email address and signature) and Office Hours:	NA
Teaching Assistant(s) and Office Hours:	NA
Language:	English
Compulsory/Elective:	Elective
Classroom and Meeting Time:	A128
Course Description:	This course introduces the theory of computation through a set of abstract machines that serve as models for computation - finite automata, pushdown automata, and Turing machines - and examines the relationship between these automata and formal languages. Additional topics beyond the automata classes themselves include deterministic and non-deterministic machines, regular expressions, context free grammars, undecidability, and the P = NP question.
Course Objectives:	This course introduces the theory of computation through a set of abstract machines that serve as models for computation - finite automata, pushdown automata, and Turing machines - and examines the relationship between these automata and formal languages. Additional topics beyond the automata classes themselves include deterministic and non-deterministic machines, regular expressions, context free grammars, undecidability, and the P = NP question.

COURSE OUTLINE

Week	Topics
1	Introduction to Computational theory , Growth of Function
2	Solving Recurrences
3	String Algorithms complexity
4	Finite Automata
5	Information Theory
6	Compression Theory
7	Randomized computation
8	Midterm
9	Lempel Ziv Family
10	Edit Distance - Dynamic Programming theory
11	Cryptosystems 1
12	Cryptosystems 2
13	Turing machines. Universal Turing Machine.
14	Polynomial time. The class NP

Prerequisite(s):
Textbook:	Introduction-To-The-Theory-Of-Computation-Michael-Sipser
Other References:	Arora-Barak: Computational Complexity. Cambridge University Press, ISBN-13: 9780521424264
Laboratory Work:	YES
Computer Usage:	YES
Others:	No

COURSE LEARNING OUTCOMES

1	Analyze and develop an ability to develop and implement appropriate algorithms or prove that the problem that is given has no algorithm or has no fast algorithm.

COURSE CONTRIBUTION TO... PROGRAM COMPETENCIES (Blank : no contribution, 1: least contribution ... 5: highest contribution)

No	Program Competencies	Cont.
Bachelor in Computer Engineering (3 years) Program
1	Engineering graduates with sufficient theoretical and practical background for a successful profession and with application skills of fundamental scientific knowledge in the engineering practice.	5
2	Engineering graduates with skills and professional background in describing, formulating, modeling and analyzing the engineering problem, with a consideration for appropriate analytical solutions in all necessary situations	5
3	Engineering graduates with the necessary technical, academic and practical knowledge and application confidence in the design and assessment of machines or mechanical systems or industrial processes with considerations of productivity, feasibility and environmental and social aspects.	5
4	Engineering graduates with the practice of selecting and using appropriate technical and engineering tools in engineering problems, and ability of effective usage of information science technologies.	5
5	Ability of designing and conducting experiments, conduction data acquisition and analysis and making conclusions.	5
6	Ability of identifying the potential resources for information or knowledge regarding a given engineering issue.	5
7	The abilities and performance to participate multi-disciplinary groups together with the effective oral and official communication skills and personal confidence.	5
8	Ability for effective oral and official communication skills in foreign language.	5
9	Engineering graduates with motivation to life-long learning and having known significance of continuous education beyond undergraduate studies for science and technology.	5
10	Engineering graduates with well-structured responsibilities in profession and ethics.	5
11	Engineering graduates who are aware of the importance of safety and healthiness in the project management, workshop environment as well as related legal issues.	5
12	Consciousness for the results and effects of engineering solutions on the society and universe, awareness for the developmental considerations with contemporary problems of humanity.	5

COURSE EVALUATION METHOD

Method	Quantity	Percentage
Homework	4	5
Midterm Exam(s)	1	30
Laboratory	5	2
Final Exam	1	40
	Total Percent:	100%

ECTS (ALLOCATED BASED ON STUDENT WORKLOAD)

Activities	Quantity	Duration(Hours)	Total Workload(Hours)
Course Duration (Including the exam week: 16x Total course hours)	16	4	64
Hours for off-the-classroom study (Pre-study, practice)	16	4	64
Mid-terms	1	10	10
Assignments			0
Final examination	1	12	12
Other			0
Total Work Load:			150
Total Work Load/25(h):			6
ECTS Credit of the Course:			6