450-2079/01 – Basics of Algorithms and Programming (ZAP)
| Gurantor department | Department of Cybernetics and Biomedical Engineering | Credits | 5 |
| Subject guarantor | prof. Ing. Michal Prauzek, Ph.D. | Subject version guarantor | prof. Ing. Michal Prauzek, Ph.D. |
| Study level | undergraduate or graduate | Requirement | Compulsory |
| Year | 1 | Semester | summer |
| | Study language | Czech |
| Year of introduction | 2019/2020 | Year of cancellation | |
| Intended for the faculties | FEI | Intended for study types | Bachelor |
Subject aims expressed by acquired skills and competences
The aim is to introduce students to the basic problems of algorithms and programming and to demonstrate implementation techniques introduced in higher programming languages. After completing the course, students will be able algorithmize basic tasks and create programs for solving simple problems using basic algorithmic structures in the general development environment. Students will understand the relationship between some features of computer architecture elements and their display in the C programming language needed to handle tasks using non-standard peripherals. Also students will be able to analyze and algorithmize simple problems using a structured approach.
Teaching methods
Lectures
Individual consultations
Tutorials
Experimental work in labs
Project work
Summary
The course is an introductory course on algorithmization and programming in all electrotechnical disciplines due to the wide applicability of language C. Students are familiar with the basic hardware elements of the computer and their relation to selected program constructions. Discussed algorithms and data structures are demonstrated, the students are encouraged to structured approach to algorithmic solved problems. Emphasis is placed on the practical implementation of algorithms and data structures. In the second part of the course students are familiar with solutions of common tasks in higher programming languages with emphasis on fast prototyping and development and solution of practical tasks using functional and object-oriented approach.
Compulsory literature:
Recommended literature:
VAN DER LINDEN, Peter. Expert C programming: deep C secrets. Mountain View: SunSoft Press, 1994.
Additional study materials
Way of continuous check of knowledge in the course of semester
Verification of study:
test
individual project
Conditions for credit:
The student is classifying on base tests and individual projects. Award of 14 th. week. C Total classification 51-100 points according study rules.
E-learning
Other requirements
There are not defined other requirements for student.
Prerequisities
Subject has no prerequisities.
Co-requisities
Subject has no co-requisities.
Subject syllabus:
Lectures:
1. Introduction to algorithmization and programming, motivation, algorithm, computer architecture, compilation process.
2. Electronic memory, types of memory, variables, constants, simple data types, basic operators, formatted input and output.
3. Control structures: Boolean expression, comma operator, conditional expression, conditions, cycles, switch, jump command.
4. Functions: function declarations and definitions, function parameters, validity range, function return value.
5. Memory classes, type modifiers, type casting, preprocessor: macros, includes, conditional compilation, separate compilation.
6. Indicators: pointers and functions, address arithmetic, parameter passing by value and reference.
7. Single-dimensional arrays, multidimensional arrays, strings, structures, union, enumeration types, typedef operator, bit operations.
8. Introduction to the scripting approach to solving algorithmic problems. Program environment - Bash, Python.
9. Program structure, function, console output in the Bash and Python scripting environment.
10. Advanced data types in scripting environments, their use and benefits, optimization, libraries and work with them.
11. Implement Cycles, Conditions, and Recursions in Python Scripting Environment.
12. File system work, search, rights, write and read. JSON format.
13. A brief basis for object programming approach.
14. Discrete phenomena and their simulations. Code documentation.
Labs:
1. Language C: programming environment
2. Language C: variable definition, simple data types, formatted input and output.
3. Language C: boolean expression, comma operator, conditional expression, conditions, cycles, switch, goto command.
4. Language C: function definitions and declaration, function parameters, validity of identifiers, function return value.
5. Language C: memory classes, type modifiers, type casting, preprocessor: macros, includes, conditional compilation, separate compilation.
6. Language C: pointers, pointers and functions, address arithmetic, parameter passing by value and reference.
7. Language C: one-dimensional arrays, multidimensional arrays, strings, structures, union, enumeration types, typedef operator, bit operations.
8. Shell Bash: system utilities and their use in simple scripts.
9. Shell Bash: chaining utilities, working with variables, definition of function, console output.
10. Python Language: Comparison with Bash approach to defining simple scripts. Work with variable output on the console. Formal definition of script structure, output formatting, functions and their chaining.
11. Python Language: working with dictionaries, numerical libraries and computations with them, other commonly used libraries in Python, conditional branching, and use of data types in terms.
12. Python language: cycles and recursion and their use for numerical computations and simulations, file system work, JSON format.
13. Python language: classes and inheritance, practical examples of the use of objects in scripting.
14. Python Language: An introduction to simulation discrete phenomena.
Conditions for subject completion
Occurrence in study plans
Occurrence in special blocks
Assessment of instruction