• Develop algorithmic thinking and skills for developing complex algorithms
• Learning basic tools for developing fundamental algorithms.
• Knowledge of different types of fundamental algorithms and their development methods.
• Use of an advanced programming language for implementing the studied algorithms.

Imperative and language programming

1. Introduction to computer programming. Examples of computer programs.
2. Information coding. 
3. Algorithms. Properties of algorithms. The description algorithms.
4. Subalgorithms. Formal parameters, current parameters.
5. Language description: C. Variables, predefined types.
6. Syntactic units. Operations. Expressions.
7. Instructions. The decisional instruction if.
8. switch ... case instruction
9. Repeated instructions. (while, do ... while, for).
10. Arrays. Declaration and use of arrays.
11. Pointers.
12. Search methods.
13. Sorting methods.
14. Functions in C. Transmission of parameters.
15. Recursion.

Lecture, conversation, exemplification, problem solving, documentation.

• acquisition of basic and specific knowledge about the concept of fundamental algorithms; • the ability to identify the applicability of the studied algorithms in real problems; • understanding the need of using advanced methods to create efficient algorithms when addressing problems from an specific domain; • Acquiring advanced knowledge of algorithms complexity and apply efficient methods to solve different practical problems.

Written exams – 50%; Continuous assessment and laboratory practical works – 50%.

-, • Adriana Bîrluțiu, Maria Muntean, Ovidiu Domsa, Fundamental Algorithms, Course notes and applications, Seria Didactică, 2015., - , - , - , -
-, • Cormen T.H., Leiserson E.C., Rivest R.R., Introduction in algorithms, MIT Press, 2001., - , - , - , -
-, • Dahl O.J., Dijkstra E.W., Hoare C.A.R., Structured Programing, Academic Press, 1972., - , - , - , -