Course syllabus BIAX10031 - Data Structures and Algorithms (FI - SS 2019/2020)
|Faculty:||Faculty of Informatics|
|Course unit code:||BIAX10031|
|Course unit title:||Data Structures and Algorithms|
|Planned learning activities and teaching methods:|
|Recommended semester/trimester:||Applied Informatics, 1. year, 2. semester|
|Level of study:||1.|
|Prerequisites for registration:||none|
|in-class tests and programming assignments - 40 %|
final written exam - 60 %
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.|
|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:|
|Language of instruction:||Slovak, English|
|Assessed students in total: 355|
|Name of lecturer(s):||prof. RNDr. Frank Schindler, PhD. (examiner, instructor, lecturer, person responsible for course)|
Ing. Erich Stark, PhD. (instructor)
|Last modification:||11. 6. 2019|
|Supervisor:||prof. RNDr. Frank Schindler, PhD.|
Last modification made by Ján Lukáš on 06/11/2019.