Study Guide

Objective

Theoretical modeling of computational problems and their solutions, restricted to fundamental methods of describing and validating data in practical software work (that is, lexical analysis and parsing): Finite automata and regular languages, pushdown automata and context free languages.

Content

Grasp of the basics of theoretical computer science.
Obtaining abilities in using techniques to generate and recognize regular languages and context-free languages.
Understanding of the basics of computability and decidability, the Church-Turing thesis and their fundamental justifications and implications.

Qualifications

Introduction to Computing, Data Structures and Algorithms I, Discrete Structures

Materials

Lecture notes. They can be supplemented with suitable books, such as: Kozen D.C.: Automata and Computability (Springer, 1997) or Hopcroft J.E., Motwani R., Ullman J.D.: Introduction to Automata Theory, Languages, and Computation, 3rd Ed. (Pearson, 2006).

Further information

Course evaluation: course exam or its re-take 80%, exercises done 20%. General exams do not take exercises into account