Data Structures (MAE681)

General

School	School of Science
Academic Unit	Department of Mathematics
Level of Studies	Undergraduate
Course Code	MAE541
Semester	5
Course Title	Data Structures
Independent Teaching Activities	Lectures and laboratory exercises (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)	-

Learning Outcomes

Learning outcomes	The course is an introduction to basic data structures such as strings, arrays, lists, stacks, queues, trees, graphs. It studies properties and implementation issues as well as basic properties on the data structures and their complexity. It also examines basic applications of the above data structures. The main purpose is the design and use of appropriate data structures for storing and retrieving the data of a problem in order for a most efficient processing during the problem solving process. After completing the course the student: Has an understanding of basic data structures and the different ways they can be implemented using a programming language. Can choose appropriate data structures for efficiently storing the data of a problem and their use by an algorithms for solving the problem.
General Competences	Working independently Problem data analysis Can use data structures for solving problems in other scientific areas or in the workplace.

Syllabus

Elements Of Analysis Of Algorithms
Abstract Data Types
Strings
Arrays
Algorithms for Searching, Sorting, Selection
Lists (Single Linked Lists, Doubly Linked Lists, Circular Lists, Generalised Lists)
Stacks
Queues, DeQueues, Priority Queues
Trees (General Trees, Binary Trees, Binary Search Trees, Threaded Trees)
Heaps
AVL-Trees, 2-3 Trees, 2-3-4 Trees, B Trees
Directed Graphs, Undirected Graphs
Set Manipulation
Hashing
Dynamic Memory Management

Teaching and Learning Methods - Evaluation

Delivery

Face to face

Use of Information and Communications Technology

-

Yes

Teaching Methods

Activity	Semester Workload
Lectures	39
Self study	78
Exercises	33
Course total	150

Student Performance Evaluation

Written final exam (70%) comprised of: • questions about the theory of data structures • Questions crisis in the form of exercises that require the use of data structures • Exercises testing the understanding of the implementation issues and use of data structures Laboratory exercises / midterm (30%)

Attached Bibliography

Data structures, algorithms and applications using c ++, Sahnii Sartaj, Publicer A. Tziola (Greek translation)
Algorithms in C ++, parts 1-4: fundamental concepts, data structures, sorting, searching, Robert Sedgewick, Prentice Hall (Greek translation)
Algorithms in C, parts 1-4: fundamental concepts, data structures, sorting, searching, Robert Sedgewick, Prentice Hall (Greek translation)
Data Structures with C, Nicholas Misirlis (Greek)
Data Structures, Bozanis Panagiotis, Publicer A. Tziola (Greek)
Michael T. Goodrich, Roberto Tamassia, and David M. Mount, Data Structures and Algorithms in C ++, John Wiley & Sons
Michael Goodrich, Roberto Tamassia, Data Structures and Algorithms in Java, Publicer DIAYLOS
Cormen, Leiserson and Rivest, Introduction to Algorithms, MIT Press, 1990. (there is also a translation from the University of Crete)
Mark Allen Weiss, Data Structures & Algorithm Analysis in Java, Addison-Wesley
Clifford A. Shaffer, Data Structures and Algorithm Analysis, ebook, http://people.cs.vt.edu/shaffer/Book/
Website: opendatastructures.org