COURSE INFORMATION Course Title: ANALYSIS OF ALGORITHMS

Code	Course Type	Regular Semester	Theory	Practice	Lab	Credits	ECTS
CEN 309	B	5	2	0	2	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 , Friday 9:45 - 11:00
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:	Compulsory
Classroom and Meeting Time:	A 001 - Monday 11:30
Course Description:	The objective of this course is to equip the students with the basic understanding of algorithms and programming concepts. Flowcharts are also covered in the course.
Course Objectives:	The objective of this course is to introduce methods for designing efficient algorithms using basic data structures for fundamental problems and evaluating their performance. Topics covered are algorithm design and analysis, algorithm runtimes, asymptotic notations, sets, searching and sorting methods, binary tree and binary tree algorithms, graph and graph algorithms, graph traversals, shortest-path, balanced search trees, basic algorithm design techniques.

COURSE OUTLINE

Week	Topics
1	Asymptotic Notation - Recurrences - Substitution, Master Method
2	Analyses of String Algorithms, On-Line Pattern Matching: Sliding window techniques
3	Boyer Moore Algorithm
4	Suffix arrays, Suffix Trees, Ukkonnen Algorithm
5	Finite State automata
6	Multiple Patterns Searching
7	Aho Corasick Algorithm
8	MIDTERM EXAM
9	Intro. To Information Theory
10	Lossles Compression:Huffman, Shanon-Fano ,
11	Arithmetic and Elias code
12	Lossless Compression: Lempel Ziv family algorithms
13	NP completeness,Ethics, Problem Solving
14	Fuzzy Logic Concepts

Prerequisite(s):	To have a satisfactory level in a programming language. (e.g. CEN 112, CEN 251).
Textbook:	Data Structures and Algorithm Analysis in C 2nd Edition. Mark Allen Weiss Introduction to Design and Analysis of Algorithms, Levitin, 3rd edition
Other References:
Laboratory Work:	YES
Computer Usage:	Yes
Others:	No

COURSE LEARNING OUTCOMES

1	Understand methods for designing efficient algorithms.
2	Discuss and use fundamental algorithms and algorithmic techniques.
3	Decide which algorithm among a set of possible choices is best for a given application.
4	Prove correctness and analyze the running time of a given algorithm.
5	Design efficient algorithms for new situations, using as building blocks the techniques learned.
6	Use the divide-and-conquer, greedy, induction, and dynamic Programming paradigms to design algorithms
7	Engineering graduates with sufficient theoretical and practical background for a successful profession and with application skills of fundamental scientific knowledge in the engineering practice.
8	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.
9	Ability of designing and conducting experiments, conduction data acquisition and analysis and making conclusions
10	Consciousness for the results and effects of engineering solutions on the society and universe, awareness for the developmental considerations with contemporary problems of humanity

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.	3
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
Midterm Exam(s)	1	30
Project	1	20
Final Exam	1	40
Attendance		10
	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	2	32
Mid-terms	1	7	7
Assignments	5	2	10
Final examination	1	12	12
Other			0
Total Work Load:			125
Total Work Load/25(h):			5
ECTS Credit of the Course:			6