SubjectsSubjects(version: 949)
Course, academic year 2019/2020
Programming Techniques - N445055
Title: Programovací techniky
Guaranteed by: Department of Computing and Control Engineering (445)
Faculty: Faculty of Chemical Engineering
Actual: from 2013 to 2019
Semester: winter
Points: winter s.:5
E-Credits: winter s.:5
Examination process: winter s.:
Hours per week, examination: winter s.:1/3, C+Ex [HT]
Capacity: 30 / 30 (unknown)
Min. number of students: unlimited
Language: Czech
Teaching methods: full-time
Teaching methods: full-time
For type:  
Note: course can be enrolled in outside the study plan
enabled for web enrollment
Guarantor: Kukal Jaromír doc. Ing. Ph.D.
Is interchangeable with: B445013
Examination dates   Schedule   
Annotation -
Last update: Kukal Jaromír doc. Ing. Ph.D. (11.09.2013)
Lessons are oriented to understanding of basic data structures and algorithms over them.
Aim of the course -
Last update: Kukal Jaromír doc. Ing. Ph.D. (11.09.2013)

Students will be able to:

Design efficient data structures for given task realization

Design efficient implementation of algorithm for task solution

Evaluate memory and time complexities of the algorithm

Literature -
Last update: TAJ445 (30.09.2013)

R:Wirth N.: Algoritms+data structures=programs, Addison-Wesley, Reading, 1981.

A:Sedgewick R.: Algorithms, Addison-Wesley, Reading, 1988.

Learning resources -
Last update: Kukal Jaromír doc. Ing. Ph.D. (11.09.2013)

internal support materials

Syllabus -
Last update: Kukal Jaromír doc. Ing. Ph.D. (11.09.2013)

1. List: sense, realization, list operations.

2. Queue, stack, priority queue as special lists.

3. Tree: sense, realization, tree operations.

4. Dynamic data structures: sense, realization in array, file and operation memory.

5. OOP: class, object, encapsulation, inheritence, polymorphism, overlay of operátors and methods.

6. Dynamic data structures as objects: array, lists, trees.

7. Recursion: sense, realization, divide et impera, subproblem, subtree analysis.

8. Algorithm: definition, time and memory complexity, NP-complete problems.

9. Event: sense, generation, interruption, event driven programming.

10. Realization of series, finite and infinite sums and products.

11. Realization of iterative procedures: solving of nonlinear equations and their systems.

12. Searching of optimum solution: brutal force, random shooting and walk, local extrems.

13. Symbolic computing: sense, principles, realization.

14. Realization of algorithms in real time, multiprocessor algorithms.

Entry requirements -
Last update: Kukal Jaromír doc. Ing. Ph.D. (11.09.2013)

Knowledge of any programming language.

Registration requirements -
Last update: Kukal Jaromír doc. Ing. Ph.D. (11.09.2013)

Algorithmization and programming

Teaching methods
Activity Credits Hours
Konzultace s vyučujícími 1 28
Účast na přednáškách 0.5 14
Práce na individuálním projektu 1.5 42
Příprava na zkoušku a její absolvování 0.5 14
Účast na seminářích 1.5 42
5 / 5 140 / 140
Coursework assessment
Form Significance
Regular attendance 40
Oral examination 60