## Module Handbook

• Dynamischer Default-Fachbereich geändert auf MAT

# Module MAT-INF-10-M-3

## Module Identification

Module Number Module Name CP (Effort)
MAT-INF-10-M-3 Computer Science for Mathematicians 8.0 CP (240 h)

## Basedata

CP, Effort 8.0 CP = 240 h 1 Sem. in SuSe [3] Bachelor (Core) [DE] German Krumke, Sven Oliver, Prof. Dr. (PROF | DEPT: MAT) Krumke, Sven Oliver, Prof. Dr. (PROF | DEPT: MAT)Schweitzer, Pascal, Prof. Dr. (PROF | DEPT: INF) [MAT-NF] Special Offers for Subsidiary Topics in Math Programmes [MAT-82.105-SG] B.Sc. Mathematics [NORM] Active

## Courses

Type/SWS Course Number Title Choice in
Module-Part
Presence-Time /
Self-Study
SL SL is
required for exa.
PL CP Sem.
4V+2U INF-02-06-K-2
Algorithms and Data Structures
P 84 h 156 h
U-Schein
ja PL1 8.0 SuSe
• About [INF-02-06-K-2]: Title: "Algorithms and Data Structures"; Presence-Time: 84 h; Self-Study: 156 h
• About [INF-02-06-K-2]: The study achievement "[U-Schein] proof of successful participation in the exercise classes (ungraded)" must be obtained.
• It is a prerequisite for the examination for PL1.

## Examination achievement PL1

• Form of examination: written exam (Klausur) (120-150 Min.)
• Examination Frequency: each semester
• Examination number: 67000 ("Computer Science for Mathematicians")

## Evaluation of grades

The grade of the module examination is also the module grade.

## Contents

• pseudocode notation of algorithms;
• growth of functions, recursions;
• fundamental concepts and methods for the analysis of algorithms: effort analysis, runtime estimation;
• complexity theory: input size, reduction, complexity classes P and NP, NP-complete problems;
• algorithm design principles: Divide-and-Conquer, Dynamic Programming, Greedy Algorithms, Backtracking;
• basic algorithms and data structures: search algorithms, sorting algorithms, balanced search trees, priority queues, hashing.

## Competencies / intended learning achievements

Upon successful completion of this module, the students know and understand general strategies for the design and analysis of algorithms as well as essential algorithmic principles of discrete mathematics and computer science and they are able to apply them. They are able to classify problems according to their complexity and structure and to apply suitable fundamental algorithms for their solution.

By completing the given exercises, the students have developed a skilled, precise and independent handling of the terms, propositions and techniques taught in the lecture.

## Literature

• T.H. Cormen, C.E. Leiserson, R.L. Rivest, C. Stein: Algorithmen – Eine Einführung,
• M. Nebel: Entwurf und Analyse von Algorithmen,
• T. Ottmann, P. Widmayer: Algorithmen und Datenstrukturen,
• R. Sedgewick, P. Flajolet: An Introduction to the Analysis of Algorithm.

## Materials

Further literature will be announced in the lecture.

## Requirements for attendance of the module (informal)

Basic programming knowledge from the courses [MAT-14-00-K-2] "Introduction to Scientific Programming" and/or [INF-02-01-K-2] "Foundations of Programming".

None

## References to Module / Module Number [MAT-INF-10-M-3]

Course of Study Section Choice/Obligation
[MAT-82.105-SG] B.Sc. Mathematics [Core Modules (non specialised)] Computer Science [P] Compulsory
[MAT-82.105-SG] B.Sc. Mathematics [Subsidiary Topic] Subsidiary Subject (Minor) [P] Compulsory
[MAT-82.276-SG] B.Sc. Business Mathematics [Core Modules (non specialised)] Computer Science and Computational Methods [P] Compulsory