Sep 25, 2020   3:31 a.m.      Vladislav        
University information system

Course syllabus BIAX10031 - Data Structures and Algorithms (FI - SS 2020/2021)


     Information sheet          


     Slovak          English          


University: Pan-european University
Faculty:
Course unit code:
BIAX10031
Course unit title:
Data Structures and Algorithms
Planned learning activities and teaching methods:
lecture
2 hours weekly / 24 hours per semester of study (on-site method)
seminar2 hours weekly (on-site method)

Credits allocated:
6
Recommended semester/trimester:
-- item not defined --
 
Level of study: 1.
Prerequisites for registration:
none
 
Assessment methods:
in-class tests and programming assignments - 40 %
final written exam - 60 %

Assigned Marks
A = 94 - 100 points
B = 86 - 93 points
C = 76 - 85 points
D = 66 - 75 points
E = 56 - 65 points
FX = 0 - 55 points
 
Learning outcomes of the course unit:
Students gain basic knowledge about data abstraction, abstract data types and other data structures including stack, queue, tree, graph, list etc. involving their specifications and various implementations. In addition to that the course also deals with analysis of algorithms for sorting and searching stressing their complexity.
 
Course contents:
1. Data abstraction, abstract data types, specification and implementation of abstract data types and their initialization.
2. Introduction into data structures, data types and data structures, overview of data structures: stack, queue, array, table, set, list, tree and graph.
3. Design and implementation of abstract data types, implementation of data structures: string, stack, array, hash table, set.
4. Pointers and dynamic data, pointer data type, concept of dynamic data, allocation and freeing of dynamic memory, dynamic programming.
5. Linked lists, their implementation via arrays and dynamic memory, doubly-linked lists, circular lists, trees and graphs.
6. Recursion: definition, recursive functions, infinite recursion, implementation and complexity of recursion.
7. Complexity analysis of algorithms: memory and operating complexity of algorithms.
8. Sorting algorithms classification.. Algorithms with quadratic operating complexity.
9. Sorting algorithms with complexity n log n, special sorting algorithms.
10. The searching problem.
11. Associative searching and search trees.
12. More dimensional search and more dimensional trees, search algorithms with return.
 
Recommended or required reading:
Basic:
RILEY, D D. -- HEADINGTON, M R. Data Abstraction and Structures using C++. Lexington Massachusetts: D. C. Heath and Company, 1994. ISBN 0-669-29220-6.
LEISERSON, C E. -- RIVEST, R L. -- CORMEN, T H. Introduction to Algorithms. Massachusetts: MIT Press, 2001. ISBN 0-262-53196-8.

 
Language of instruction:
Slovak, English
 
Notes:
 
Courses evaluation:
Assessed students in total: 386

A
BCD
E
FX
11,7 %
18,4 %
29,8 %
18,9 %
18,1 %
3,1 %
 
Name of lecturer(s): prof. RNDr. Frank Schindler, PhD. (examiner, lecturer, person responsible for course)
Last modification: 4. 6. 2020
Supervisor: prof. RNDr. Frank Schindler, PhD.


Last modification made by Mgr. Lenka Sekretárová on 06/04/2020.

Type of output: