SoSe 24: Algorithms and Data Structures
Wolfgang Mulzer
Comments
Qualification goals
The students can analyze algorithms and data structures and their implementations with respect to running time, space requirements, and correctness. The students can describe different algorithms and data structures for typical applications and know how to use them in concrete settings. They can choose appropriate algorithms and data structures for a given task and are able to adapt them accordingly. Students can explain, identify and use different paradigms for designing new algorithms.
Contents
- abstract machine models
- running time, correctness and space requirements
- worst-case analysis
- algorithms and randomness
- algorithmic paradigms: divide and conquer, greedy, dynamic programming, exhaustive search
- priority queues
- ordered and unordered dictionaries (e.g., search trees, hash tables, skiplists)
- algorithms for strings (string searching and radix trees)
- graph algorithms
Suggested reading
- P. Morin: Open Data Structures, an open content textboox.
- T. H. Cormen, C. Leiserson, R. Rivest, C. Stein: Introduction to Algorithms, MIT Press, 2022.
- R. Sedgewick, K. Wayne: Algorithms, Addison-Wesley, 2011.
- M. Dietzfelbinger, K. Mehlhorn, P. Sanders. Algorithmen und Datenstrukturen: Die Grundwerkzeuge, Springer, 2014.
- J. Erickson. Algorithms, 2019
- T. Roughgarden. Algorithms Illuminated. Cambridge University Press, 2022.
28 Class schedule
Additional appointments
Tue, 2024-07-23 12:00 - 14:00
Location:
T9/053 Seminarraum (Takustr. 9)
Location:
I Hörsaal (Vant-Hoff-Str. 8)
Regular appointments
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Qualification goals
The students can analyze algorithms and data structures and their implementations with respect to running time, space requirements, and correctness. The students ... read more