## Module Handbook

• Dynamischer Default-Fachbereich geändert auf INF

# Module INF-82-54-M-2

## Module Identification

Module Number Module Name CP (Effort)
INF-82-54-M-2 Algorithms and Data Structures 8.0 CP (240 h)

## Basedata

CP, Effort 8.0 CP = 240 h 1 Sem. in SuSe [2] Bachelor (Fundamentals) [DE] German Schürmann, Bernd, PD Dr.-Ing. (WMA | DEPT: INF, GS) Schweitzer, Pascal, Prof. Dr. (PROF | DEPT: INF) [INF-LA] Teacher Education [INF-31.79-SG] B.Ed. LaGR Computer Science [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 summer semester

## Contents

• Basic data structures, abstract data types and their realization through data structures (lists, trees) and advanced data structures (balanced trees, hash tables)
• Basic algorithms (e.g. search and sort, graph algorithms)
• Algorithmic principles (divide and conquer, systematic search)
• Design of simple algorithms
• Distributed algorithms, concurrent processes
• Efficiency analysis of algorithms
• Time and space complexity of algorithms
• Asymptotic growth of complexity
• NP-completion and reduction
• Specification, test and verification

## Competencies / intended learning achievements

The students
• know basic data structures, algorithms and basic modeling concepts;
• develop an understanding of the interaction between algorithm and data structure;
• can model, design and implement software modules and evaluate the quality of the results;
• use mathematical methods for correctness proofing and efficiency analysis and can assess the quality of algorithms.

## Literature

• Cormen, Leiserson, Rivest, Stein: Algorithmen - Eine Einführung. Oldenbourg Verlag, 2013.
• Mehlhorn, Kurt, and Peter Sanders. Algorithms and data structures: The basic toolbox. Springer Science & Business Media, 2008.
• Nebel: Entwurf und Analyse von Algorithmen. Springer-Verlag, 2012.
• Ottmann, Widmayer: Algorithmen und Datenstrukturen. Springer-Verlag, 2012.

## Requirements for attendance of the module (informal)

Programming skills.

None

## References to Module / Module Number [INF-82-54-M-2]

Course of Study Section Choice/Obligation
[INF-31.79-SG] B.Ed. LaGR Computer Science [Compulsory Modules] Further modules [P] Compulsory
[INF-47.79-SG] B.Ed. LaBBS Computer Science [Compulsory Modules] Further modules [P] Compulsory
[INF-B4.79-SG] ZEP LaG Computer Science [Compulsory Modules] Certificate course of studies [P] Compulsory
[INF-B5.79-SG] ZEP LaBBS Computer Science [Compulsory Modules] Certificate course of studies [P] Compulsory
[INF-B2.?-SG] ZEP LaRSP Computer Science [Compulsory Modules] Certificate course of studies [P] Compulsory