Algorithms and Data Structures
This module handbook serves to describe contents, learning outcome, methods and examination type as well as linking to current dates for courses and module examination in the respective sections.
Module version of SS 2011
There are historic module descriptions of this module. A module description is valid until replaced by a newer one.
Whether the module’s courses are offered during a specific semester is listed in the section Courses, Learning and Teaching Methods and Literature below.
|available module versions|
|WS 2011/2||SS 2011|
BV440007 is a semester module in English language at Master’s level which is offered in summer semester.
This Module is included in the following catalogues within the study programs in physics.
- Catalogue of non-physics elective courses
|Total workload||Contact hours||Credits (ECTS)|
|90 h||28 h||3 CP|
Content, Learning Outcome and Preconditions
• Recursive algorithms
• Introduction into the complexity analysis of algorithms
• Data structures (arrays, trees, linked lists)
• Sorting algorithms (sequential approaches, divide-and-conquer approach)
• Search algorithms (sequential and recursive approaches, balancing, hashing)
• Foundations of graph theory and graph applications (minimal-spanning trees, shortest-path-search, maximum network flow)
• Code optimisation and cache-blocking algorithms
• develop algorithms and, thus, to formulate rules using programming concepts in order to solve problems with the help of computers,
• understand recursive approaches and to apply them on own problems,
• analyse and classify algorithms concerning runtime and memory usage via a complexity evaluation,
• know different data structures and according to their strong and weak aspects to chose appropriate structures for specific problem classes,
• known, understand, and apply different sorting and searching algorithms together with their respective runtime and memory complexity,
• understand the foundations of graph theory and to apply graph-based algorithms for questions regarding minimal-spanning trees, shortest-path-search, and maximum network flow,
• know and understand methods for code optimisation (such as cache-blocking) and to apply them on own problems.
Courses, Learning and Teaching Methods and Literature
Courses and Schedule
|VO||2||Algorithms and Data Structures||Mundani, R.||
Fri, 09:45–11:15, 2601
Learning and Teaching Methods
- R. Sedgewick: Algorithms, 2nd ed., Addison-Wesley, 1988
- V. Heun: Grundlegende Algorithmen, Vieweg, 2003