Design and Analysis of Algorithms (MAE581)

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Department of Mathematics
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General

School	School of Science
Academic Unit	Department of Mathematics
Level of Studies	Undergraduate
Course Code	MAE581
Semester	5
Course Title	Design and Analysis of Algorithms
Independent Teaching Activities	Lectures, laboratory exercises, tutorials, quiz (Weekly Teaching Hours: 3, Credits: 6)
Course Type	Special Background
Prerequisite Courses	-
Language of Instruction and Examinations	Greek
Is the Course Offered to Erasmus Students	Yes
Course Website (URL)	See eCourse, the Learning Management System maintained by the University of Ioannina.

Learning Outcomes

Learning outcomes	This course aims at introducing to students the philosophy of fundamental algorithmic background and techniques. After successfully passing this course the students will be able to: Understand basic algorithmic techniques Analyze complex algorithms Design new algorithmic tools Combine already-known techniques for solving new algorithmic problems
General Competences	Search for, analysis and synthesis of data and information, with the use of the necessary technology Working independently Team work Project planning and management.

Syllabus

Fundamental concepts of design and analysis of algorithms
Analysis of algorithms, Asymptotical growing functions
Typical running times and data structures (lists, arrays, queues, stacks)
Stable matching, correctness, priority queue
«Divide & Conquer» technique, sorting, recursive formulations
Graph algorithms: BFS, DFS, connectedness, topological ordering
Greedy algorithms: interval scheduling & shortest paths (Dijkstra)
Minimum spanning trees(Prim & Kruskal algorithms), Huffman coding
Dynamic programming: maximum flow, interval scheduling, and Knapsack
Further Topics: computational complexity and ΝΡ-completeness.

Teaching and Learning Methods - Evaluation

Delivery

Lectures

Use of Information and Communications Technology

Use of projector and interactive board during lectures.
Course website maintenance. Announcements and posting of teaching material (lecture slides and notes, programs).
Announcement of assessment marks via the ecourse platform by UOI.

Teaching Methods

Activity	Semester Workload
Lectures	39
Working independently	78
Team work	33
Course total	150

Student Performance Evaluation

Final written examination (70%)

Design and analyze algorithms

Exercises (30%)

Design and analyze algorithms

Attached Bibliography

See the official Eudoxus site or the local repository of Eudoxus lists per academic year, which is maintained by the Department of Mathematics. Books and other resources, not provided by Eudoxus:

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