Stud.IP Uni Oldenburg
University of Oldenburg
25.05.2022 20:51:05
inf405 - Algorithmic Graph Theory (Complete module description)
 Module label Algorithmic Graph Theory Module code inf405 Credit points 6.0 KP Workload 180 h Institute directory Department of Computing Science Applicability of the module Bachelor's Programme Computing Science (Bachelor) > Akzentsetzungsbereich - Wahlbereich Informatik Dual-Subject Bachelor's Programme Computing Science (Bachelor) > Wahlpflicht Theoretische Informatik (30 KP) Master of Education Programme (Gymnasium) Computing Science (Master of Education) > Wahlpflichtmodule (Theoretische Informatik) Responsible persons Lehrenden, Die im Modul (Authorized examiners) Lehrenden, Die im Modul (Module responsibility) Prerequisites Skills to be acquired in this module Graphs are the most frequently used abstraction in computer science. Every system which consists of discrete states or objects and relations between these can be modelled as a graph. Most applications require efficient algorithms to process such graphs (Turau, 1996). This module provides typical graph theory problems and algorithmic solutions. They are discussed with regard to their efficiency and applicability and many of the algorithms will be implemented. An important aspect of this module is to consider different approaches to problems and learn different solution strategies.Professional competenceThe students:identify basic terms of graph theory and optimization and illustrate them with examplesname typical graph theory problems and algorithmic solutionsidentify situations where graph algorithms can be applieddiscuss typical graph theory problems and algorithmic solutions with regard to their efficiency and applicability.implement graph algorithmsknow proof strategies and are able to apply themMethodological competenceThe students:extend their knowledge about algorithms and their complexitydevelop their programming skillsexpand their range of methods of mathematical modellingSocial competenceThe students:use the language of mathematics to discuss problems in groups with different knowledge levelspresent their ideas in a comprehensible wayExpand and improve their own ideas through the comments of their fellow studentsSelf-competenceThe students:reflect their knowledge about algorithms and their complexitydevelop appropriate solutions for given problemschallenge methods of resolution Module contents A) TreesB) Search AlgorithmsC) Graph ColoringD) Flows in NetworksE) Applications of Network AlgorithmsF) Shortest PathsG) Approximation AlgorithmsG) Approximation Algorithms Reader's advisory Jungnickel, Dieter: Graphs, Networks and Algorithms. Springer, Berlin,Heidelberg, 4th edition, 2013. Available as an E-Book in BIS.A detailed bibliography is contained in the lecture notes of this module. Links Language of instruction German Duration (semesters) 1 Semester Module frequency jährlich Module capacity unlimited Modullevel / module level AS (Akzentsetzung / Accentuation) Modulart / typ of module je nach Studiengang Pflicht oder Wahlpflicht Lehr-/Lernform / Teaching/Learning method V+Ü Vorkenntnisse / Previous knowledge Grundveranstaltungen Mathematik und Informatik
Course type Comment SWS Frequency Workload of compulsory attendance
Lecture
3 SuSe 42
Exercises
1 SuSe 14
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 exam