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| Detailed information |
| Pre-requisites |
(*)Erwartete Vorkenntnisse: Modul Einführung in die Softwareentwicklung
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| Original study plan |
Bachelor's programme Business Informatics 2025W |
| Learning Outcomes |
Competences |
| Students are able to work with abstraction concepts, solve tasks algorithmically and transform algorithms into programs and analyze them.
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| Skills |
Knowledge |
- LO2: Students master the design of algorithms and data structures, taking runtime and memory efficiency into account. (K3)
- LO3: They are able to analyze algorithms according to their structure and behavior. (K4)
- LO4: You can implement algorithms in software. (K3)
- LO5: You are familiar with methods and concepts for systematic programming and modeling of complex data structures. (K2)
- LO6: You know algorithms for solving important standard tasks and can apply them. (K3)
- LO7: You can develop recursive algorithms to solve problems in a structured way. (K3)
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LO1: Basic algorithmic concepts; basic terms and forms of notation; structure and design of algorithms; structure and design of elementary and dynamic data structures (linked lists, trees, binary search trees, AVL trees); data abstraction, abstract data types; recursion principle and recursive algorithms; complexity analysis of algorithms; standard algorithms (e.g. sorting and search algorithms); algorithms on character strings; exhaustion algorithms; overview of algorithms with topical relevance (e.g. machine learning).
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| Criteria for evaluation |
Written final exam (theory questions, practical examples for the development of algorithms)
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| Methods |
The course is held in the form of a traditional lecture. The students receive materials which they supplement during the lecture. The lecture is supplemented by an accompanying exercise.
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| Language |
German |
| Study material |
Course materials
- Presentation slides will be made available via Moodle
Basic literature:
- Pomberger, G.; Dobler, H.: Algorithmen und Datenstrukturen: Eine systematische Einführung in die Programmierung. Pearson Verlag, Munich, 2008.
Supplementary literature:
- Sedgewick, R.: Algorithms in Java. Pearson Verlag, Munich, in the current edition.
- Cormen, T. H.; Leiserson, C. E.; Rivest, R. L.: Introduction to Algorithms. The MIT Press, Cambridge, in the current edition.
- Niklaus Wirth: Algorithmen und Datenstrukturen, Teubner Verlag, in the current edition.
- Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest: Introduction to Algorithms, The MIT Press, in the current edition.
- A. Solymosi, U. Grude, Grundkurs Algorithmen und Datenstrukturen in JAVA, Springer Fachmedien Wiesbaden GmbH 2017
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| Changing subject? |
No |
| Further information |
The course is held in the form of a traditional lecture. The students receive materials that they supplement during the lecture. In this way, students are taught the development process of algorithms. The lecture is supplemented by an accompanying exercise.
The exercises serve to consolidate the material covered in the lecture and are intended to give students the opportunity to check whether the knowledge they have acquired can actually be put into practice. In addition, students have the opportunity to reflect on the content of the lecture and discuss unresolved problems with the lecturers.
The courses VL and UE Algorithms and Data Structures form an inseparable didactic unit. The learning outcomes described are achieved through the interaction of the two courses.
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| Earlier variants |
They also cover the requirements of the curriculum (from - to)
1WBWADV: VL Algorithms and Data Structures (2002W-2014S)
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