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University of Oldenburg
19.11.2019 16:09:02
inf401 - Foundations of Theoretical Computer Science (Complete module description)
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Module label Foundations of Theoretical Computer Science
Module code inf401
Credit points 6.0 KP
Workload 180 h
Faculty/Institute Department of Computing Science
Used in course of study
  • Bachelor's Programme Computing Science (Bachelor) >
  • Bachelor's Programme Mathematics (Bachelor) >
  • Dual-Subject Bachelor's Programme Computing Science (Bachelor) >
Contact person
Module responsibility
Authorized examiners
Entry requirements
Skills to be acquired in this module
Introduction to the theory of automata, formal languages, computability, and complexity

Professional competence
The students:
  • Know different classes of languages (e.g. regular and context-free languages)
  • Know automata models corresponding to the respective language classes (e.g. finite automata, pushdown automata, Turing machines)
  • Construct automata, Turing machines, and grammars for given tasks
  • Know equivalent formalisations of the concept of algorithm
  • Classify functions as algorithmically computable and problems as algorithmically decidable
  • Know and recognize undecidable problems
  • Evaluate the complexity of algorithms
  • Know problems that are solvable deterministically or nondeterministically in polynomial time


Methodological competence
The students:
  • Learn about the power of abstract models of computation


Social competence
The students:
  • Work together in small groups to solve problems
  • Present solutions to problems to groups of other students


Self-competence
The students:
  • Learn persistence in pursuing difficult tasks
  • Learn precision in writing down solutions
Module contents
In the first part of the course, different classes of languages are introduced (regular and context-free languages).
For each class a matching automata model is presented (finite automata, pushdown automata). Various properties are proven for the introduced classes of languages and models of automata.

In the second part of the course, we examine which functions are computable and which problems are decidable. To this end, the concept of algorithm is formalised. Turing machines and grammars turn out as equivalent approaches. We show that there are problems that are undecidable. Many of these problems are of practical interest.

The third part of the course deals with the complexity of algorithms, i.e. how much time and space is required to solve a problem. In particular, we consider problems that are solvable in polynomial time, either deterministically or non-deterministically. These problems are classified as P and NP.
Reader's advisory
- essentiell: Skript "Grundbegriffe der Theoretischen Informatik", jeweils in aktueller Ausgabe
- empfohlen: Schöning: "Theoretische Informatik kurzgefasst", 5. Auflage, Spektrum, 2008
- Gute Sekundärliteratur: Hopcroft, Motwani, Ullman: "Einführung in die Automatentheorie, Formale Sprachen und Komplexitätstheorie", Pearson, 2002 (ein Klassiker...)
Links
Language of instruction German
Duration (semesters) 1 Semester
Module frequency jährlich
Module capacity unlimited
Modullevel AC (Aufbaucurriculum / Composition)
Modulart je nach Studiengang Pflicht oder Wahlpflicht
Lern-/Lehrform / Type of program V+Ü
Vorkenntnisse / Previous knowledge
Course type Comment SWS Frequency Workload attendance
Lecture 3.00 WiSe 42 h
Exercise or tutorial 1.00 WiSe 14 h
Total time of attendance for the module 56 h
Examination Time of examination Type of examination
Final exam of module
At the end of the lecture period
Written or oral exam