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Module code: PIB-INF2 |
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3V+1U (4 hours per week) |
5 |
Semester: 2 |
Mandatory course: yes |
Language of instruction:
German |
Assessment:
Written exam, Duration 120 min.
[updated 13.10.2024]
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PIB-INF2 (P221-0025) Applied Informatics, Bachelor, ASPO 01.10.2022
, semester 2, mandatory course
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60 class hours (= 45 clock hours) over a 15-week period. The total student study time is 150 hours (equivalent to 5 ECTS credits). There are therefore 105 hours available for class preparation and follow-up work and exam preparation.
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Recommended prerequisites (modules):
PIB-INF1 Informatics 1 PIB-MA1 Mathematics 1
[updated 29.07.2024]
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Recommended as prerequisite for:
PIB-PA Project work PIB-PRA Work Experience Phase PIB-TI Theoretical Informatics PIB-WA Scientific Work PIB-WEB Principles of Web Development
[updated 03.07.2024]
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Module coordinator:
Prof. Dr. Klaus Berberich |
Lecturer: Prof. Dr. Klaus Berberich
[updated 28.09.2016]
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Learning outcomes:
After successfully completing this module, students will be familiar with basic problems on undirected and directed graphs, as well as character strings. They will be able to define and differentiate basic terms from the graph theory. Students will be aware of the relevance of graph problems (e. g. topological sorting and finding minimum spanning trees) for solving practical tasks (e. g. scheduling). They will be able to use efficient algorithms for solving basic problems on graphs and strings. For their description and analysis, students use the skills acquired in the “Informatics 1” module. Students will also be capable of formulating a given practical task as a problem and of solving it by applying the algorithms they have learned.
[updated 13.10.2024]
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Module content:
1. Introduction 2. Searching and sorting 2.1 Breadth-first search 2.2 Depth-first search 2.3 Topological sorting 3. Shortest paths 3.1 Bellman-Ford algorithm 3.2 Dijkstra’s algorithm 3.3 Floyd-Warshall algorithm 4. Components and spanning trees 4.1 Determining connected components 4.2 Kruskal’s algorithm 4.3 Prim’s algorithm 5. Algorithms for character strings 5.1 Pattern matching 5.2 Longest common strings 5.3 Levenshtein distance 5.4 Pattern search in strings
[updated 13.10.2024]
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Teaching methods/Media:
Slides, theoretical exercises.
[updated 24.02.2018]
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Recommended or required reading:
Cormen Thomas H., Leiserson Charles E., Rivest Ronald L. und Stein Clifford: Algorithmen - Eine Einführung, Oldenbourg , 2013 Gunther Saake und Kai-Uwe Sattler: Algorithmen und Datenstrukturen: Eine Einführung mit Java, dpunkt.verlag, 2020 Sedgewick Robert, Wayne Kevin: Algorithmen und Datenstrukturen, Pearson Studium, 2014
[updated 13.10.2024]
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Module offered in:
SS 2024,
SS 2023,
SS 2022,
SS 2021,
SS 2020,
...
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