Bachelor Informatik

Deepening: Technische Informatik

Fast facts

Department
Informatik
Stand/version
2019
Standard period of study (semester)
6
ECTS
180

Study plan

1. Semester	2. Semester	3. Semester	4. Semester	5. Semester	6. Semester
BWL PF 4SWS 5ECTS	Algorithmen und Datenstrukturen PF 4SWS 5ECTS	Datenbanken 1 PF 4SWS 5ECTS	Automatisierungstechnik PF 4SWS 5ECTS	IT-Recht PF 2SWS 2ECTS	Projektarbeit PF 0SWS 15ECTS
Einführung in die Programmierung PF 10SWS 10ECTS	Lern- u. Arbeitstechniken PF 2SWS 2ECTS	Elektronik PF 4SWS 5ECTS	Embedded Systems PF 4SWS 5ECTS	Informatik und Gesellschaft PF 2SWS 2ECTS	Seminar - Inhalt PF 2SWS 2ECTS
Mathematik für Informatik 1 PF 4SWS 5ECTS	Mathematik für Informatik 2 PF 4SWS 5ECTS	Mathematik für Informatik 4 PF 4SWS 5ECTS	Kommunikations- und Rechnernetze PF 4SWS 5ECTS	Studium Generale PF 2SWS 2ECTS	Thesis mit Kolloquium PF 0SWS 15ECTS
Rechnerstrukturen und Betriebssysteme 1 PF 4SWS 5ECTS	Mathematik für Informatik 3 PF 4SWS 5ECTS	Physik PF 4SWS 5ECTS	Softwaretechnik 2 PF 4SWS 5ECTS	Compulsory elective modules (38)
Theoretische Informatik PF 4SWS 5ECTS	Programmierkurs 1 PF 4SWS 5ECTS	Programmierkurs 2 TI PF 4SWS 5ECTS	Systems Engineering PF 4SWS 5ECTS
	Rechnerstrukturen und Betriebssysteme 2 PF 4SWS 5ECTS	Softwaretechnik 1 PF 4SWS 5ECTS
	Studium Generale PF 2SWS 2ECTS
	Technisches Englisch PF 2SWS 2ECTS

Compulsory elective modules 1. Semester

Compulsory elective modules 2. Semester

Compulsory elective modules 3. Semester

Compulsory elective modules 4. Semester

Compulsory elective modules 5. Semester

Anerkannte Wahlpflichtprüfungsleistung

WP
0SWS
5ECTS

Anerkannte Wahlpflichtprüfungsleistung

WP
0SWS
5ECTS

Anerkannte Wahlpflichtprüfungsleistung

WP
0SWS
5ECTS

Anerkannte Wahlpflichtprüfungsleistung

WP
0SWS
5ECTS

Anerkannte Wahlpflichtprüfungsleistung

WP
0SWS
5ECTS

Ausgewählte Aspekte der Informatik

WP
4SWS
5ECTS

Data Mining in Industrie u.Wirtschaft

WP
4SWS
5ECTS

Effiziente Algorithmen und Datenstrukturen

WP
4SWS
5ECTS

Entwicklung verteilter Anwendungen

WP
4SWS
5ECTS

Informations- und Business Performance Management

WP
4SWS
5ECTS

Modellbasierte Softwareentwicklung

WP
4SWS
5ECTS

Softwaretechnik C (Softwaremanagement)

WP
4SWS
5ECTS

Softwaretechnik D (Qualitätssicherung und Wartung)

WP
4SWS
5ECTS

Virtualisierung und Cloud Computing

WP
4SWS
5ECTS

Compulsory elective modules 6. Semester

Module overview

1. Semester of study

BWL
PF

4 SWS

5 ECTS

Number
45281
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

Students recognize the importance of business administration for everyday life and their future professional development as employees or independent entrepreneurs in the IT sector.

Technical and methodological competence:

The students become aware of the legal and economic consequences of wrong business decisions
They learn tools and techniques that enable them to make calculations
They know the differences between cost centers, cost types and cost units.

Interdisciplinary methodological competence:

Students will receive an introduction to project management. They will be able to create a network plan
They will be able to link the acquired knowledge of business administration with the available IT programs. (Excel, MS Project)

Social skills:

Students will work in groups to solve tasks and thus learn the requirements of the team-building process.

Historical development of Business Studies
Legal foundations
Operation and company, structure, organization and task of company divisions
Procurement management
Materials and warehouse management
Production management
Sales management
Business accounting, calculations and cost accounting, BAB
ABC analysis and project management (network planning technique)
Company formation, types of company, capital increase

Teaching methods

Lecture in interaction with the students, with blackboard writing and projection
Solving practical exercises in individual or team work
Group work
Individual work
Active, self-directed learning through internet-supported tasks, sample solutions and accompanying materials

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

written exam paper

Requirements for the awarding of credit points

passed written exam

Applicability of the module (in other degree programs)

Bachelor's degree in Software and Systems Engineering (dual)
Bachelor of Computer Science
Bachelor's degree in Medical Informatics
Bachelor of Medical Informatics Dual
Bachelor of Computer Science Dual

Importance of the grade for the final grade

5 LP out of 167.5 (2.99%)

Literature

Philip Junge: BWL für Ingenieure, Springer Verlag 2012
Kruse/Heun : Betriebswirtschaftslehr, Winklers Verlag
Deitermann, M., Schmolke, S., IKR mit Kosten- und Leistungsrechnung, Winklers Verlag

Einführung in die Programmierung
PF

10 SWS

10 ECTS

Number
41011
Language(s)
de
Duration (semester)
1
Contact time
120 h
Self-study
120 h

Learning outcomes/competences

After completing the course, students will have mastered the most important principles of object-oriented programming on a small scale and have a basic understanding of the structure and functioning of computers.

Technical and methodological competence:
You will acquire the formal competence to understand the principles, methods, concepts and notations of programming on a small scale, to classify them in different contexts and to use them in object-oriented programs. This also includes identifying the algorithmic core of a simple problem and designing an imperative algorithm.
They acquire basic analysis skills that enable them to implement simple object-oriented models in UML notation in the Java programming language. This competence also includes the ability to familiarize themselves independently with applications (such as development environments, learning platforms).
You have the implementation skills to develop and analyze object-oriented programs in Java.

Interdisciplinary methodological competence:
Graduates are familiar with historical developments in computer science. They are aware of the security problems associated with the use of information processing systems. They have key qualifications such as the ability to use new media. They have experience in solving application problems in a team.

Social skills:
Students acquire communicative competence in order to present their ideas and proposed solutions convincingly in writing or orally, even if their counterparts are not familiar with the computer science way of speaking and thinking.

Fundamental concepts of computer science
Procedures for the step-by-step development of programs
Elements of imperative programming: data types, control structures, operations
Elements of object-oriented programming: objects, classes, interfaces, inheritance, polymorphism
Description methods of object-oriented programming, e.g. UML

Teaching methods

Lecture in interaction with the students, with blackboard writing and projection
Solving practical exercises in individual or team work
Processing programming tasks on the computer in individual or team work
Active, self-directed learning through internet-supported tasks, sample solutions and accompanying materials

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

written written examination
study achievements during the semester (bonus points)
Participation in project week (ungraded)

Requirements for the awarding of credit points

passed written exam
successful participation in project week (2 SWS internship)
participation in at least 80% of the attendance dates in the project week

Applicability of the module (in other degree programs)

Bachelor of Business Informatics
Bachelor of Software and Systems Engineering (dual)
Bachelor of Computer Science
Bachelor's degree in Medical Informatics
Bachelor of Medical Informatics Dual
Bachelor of Computer Science Dual

Literature

H. Balzert, Java: Der Einstieg in die Programmierung, 4. Auflage, Springer Campus, 2013
H. Balzert, Java: Objektorientiert programmieren, 3. Auflage, Springer Campus, 2017
H. P. Gumm, M. Sommer, Grundlagen der Informatik: Programmierung, Algorithmen und Datenstrukturen, Oldenbourg, 2016
S. Goll, C. Heinisch, Java als erste Programmiersprache, 8. Auflage, Springer Vieweg, 2016
D. Ratz, J. Scheffler, D. Seese, J. Wiesenberger, Grundkurs Programmieren in Java, 7. Auflage, Hanser, 2014
C. Ullenboom, Java ist auch eine Insel, 12. Auflage, Galileo Press, 2016 (siehe auch http://openbook.galileocomputing.de/javainsel/)

Projektwoche

Das Modul beinhaltet eine Projektwoche (I9PB-41012, 2 SWS). Die Klausurarbeit und die Projektwoche können unabhänig voneinander abgelegt werden. Für das Bestehen des Moduls ist neben einer Klausur die erfolgreiche Teilnahme an der Projektwoche erforderlich. Die Note des Moduls wird ausschließlich über die Klausurarbeit definiert. Die Projektwoche wird als 5-Tägige Blockveranstaltung im Anschluss an die Vorlesung angeboten.

Mathematik für Informatik 1
PF

4 SWS

5 ECTS

Number
41064
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

Technical and methodological competence:

Students master basic mathematical concepts of computer science and their methods such as set theory, relations, propositional logic, complex numbers as well as groups and solids.
Students who have completed the module have mastered basic and advanced concepts and methods from linear algebra and are able to apply these methods with reference to their practical applications to solve typical tasks in computer science.
The graduates demonstrate a confident handling of the concepts and methods of vector and matrix calculus and their geometric interpretation, setting up and solving linear systems of equations as well as dealing with straight lines and planes.

Interdisciplinary methodological skills and self-competence:

Graduates of the module are able to solve computer science problems by setting up and calculating the corresponding mathematical models (for example by setting up and solving linear systems of equations). They demonstrate confidence in the appropriate selection of problem-specific solution methods and their application.

Social skills:

The participants understand the relevance of the content taught to their field of study and are able to communicate this relevance adequately.

The event includes the following topics:

Basics of mathematics for computer scientists: Introduction to set theory, cardinality of sets, relations, basics of propositional logic, complex numbers, groups and solids.
Vectors and vector calculus: notation and interpretation, operations on vectors and their properties (addition, scalar multiplication, scalar product, cross product), vector spaces, length of vectors, collinearity, linear dependence and independence, concepts of dimension and basis, angles between vectors.
Lines and planes: Representation in linear algebra, applications, positional relationships between points / straight line / planes
Matrices: Notation and interpretation, operations on matrices and their properties (transposing matrices, addition, scalar multiplication, matrix multiplication), Gaussian algorithm, determinants, inverse matrices and their calculation
Linear systems of equations: motivation and applications, matrix-vector form of linear systems of equations, Gaussian algorithm for solving linear systems of equations, homogeneous and inhomogeneous linear systems of equations and their relationships, rank of a matrix and relation to the solution set of linear systems of equations
Eigenvalues and basic transformations

Teaching methods

Lecture in interaction with the students, with blackboard writing and projection
Solving practical exercises in individual or team work

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

written exam paper

Requirements for the awarding of credit points

passed written exam

Applicability of the module (in other degree programs)

Bachelor of Computer Science
Bachelor's degree in Medical Informatics
Bachelor of Medical Informatics Dual
Bachelor of Computer Science Dual

Literature

Skript zur Vorlesung,
G. Teschl und S. Teschl, Mathematik für Informatiker 1, 3. Auflage, Springer Verlag (2008) - im Intranet der FH elektronisch verfügbar.
G. Teschl und S. Teschl, Mathematik für Informatiker 2, 2. Auflage, Springer Verlag (2007) - im Intranet der FH elektronisch verfügbar.
G. Fischer, Lineare Algebra, Vieweg, Braunschweig/Wiesbaden, 12. Auflage (2000).
Preuß, W., Wenisch, G., Lehr- und Übungsbuch Mathematik für Informatiker.

Rechnerstrukturen und Betriebssysteme 1
PF

4 SWS

5 ECTS

Number
41031
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

Students learn about the basic structure of a computer, from simple digital circuits to a typical microprocessor and computer architectures to basic concepts of an operating system.

Technical and methodological competence

Computer-oriented representation of information (numbers and characters)
Describing gates and their function, designing simple switching networks, specifying the function of a switching network as a Boolean expression and as a truth table
Understanding the structure and use of memory elements (selected latches and flip-flops)
Sketch the structure and basic understanding of how microprocessors and computer architectures work
Understanding simple machine programs
Sketch and evaluate simple implementations of the three central tasks of an operating system (process, memory and file management)
Practical application of the Linux operating system

Social skills

Solving programming tasks in groups of two
Presenting the results to the supervisor

Number and character representation (positive and negative integers, fixed and floating point representation IEEE 754, ASCII/Unicode)
Fundamentals of digital technology (switching algebra, gates, normal forms, optimizations)
Arithmetic and logic (simple standard switching networks - from multiplexer to ALU)
Memory (RS latch, reference to automata theory, flip-flops, simple standard switching networks)
Computer architecture (machine types, von-Neumann and Harvard, approaches to modernization, current processors)
Microprocessor architecture and programming (case study Atmel AVR ATmega)
Introduction to the practical application of Linux (files and directories, input/output redirection, processes)
Operating system concepts (architectures)
Processes (administration, scheduling)
Memory management (free memory management, swapping, virtual memory)
File systems (FAT, Unix inodes)

Teaching methods

Lecture in interaction with the students, with blackboard writing and projection
Exercise accompanying the lecture
Internship accompanying the lecture

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

written written examination
study achievements during the semester (bonus points)

Requirements for the awarding of credit points

passed written exam

Applicability of the module (in other degree programs)

Bachelor's degree in Software and Systems Engineering (dual)
Bachelor of Computer Science
Bachelor of Computer Science Dual

Literature

Tanenbaum, A.S., Rechnerarchitektur: Von der digitalen Logik zum Prarallelrechner, 6. Aufl., Pearson Studium, 2014.
Hoffmann, D.W., Grundlagen der Technischen Informatik, 5. Aufl., Hanser, 2016.
Tanenbaum, A.S., Moderne Betriebssysteme, 4. Aufl., Pearson Studium, 2016.
Stallings, W., Operating Systems: Internals and Design Principles, 9th ed., Prentice Hall, 2017.

Theoretische Informatik
PF

4 SWS

5 ECTS

Number
42041
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

Technical and methodological competence:

Be able to name basic terms and properties of formal languages, grammars and the corresponding automata
Create grammars and automata for formal languages and understand how they work.
Be able to convert the representation of languages between grammars, automata and regular expressions.

Interdisciplinary methodological competence:

Be able to independently assess and classify problems in terms of their complexity

Formal languages and grammars: Alphabet; words: languages; grammars; derivations; grammar types in the Chomsky hierarchy
Regular languages: programming finite automata (deterministic and non-deterministic); minimization of automata; regular expressions; conversion between grammars, automata and regular expressions; closure properties, pumping lemma for regular languages
Context-free languages: pushdown automata; Chomsky normal form; word problem with the CYK algorithm; termination properties; pumping lemma for context-free languages
Turing machines: variants (deterministic and non-deterministic); universal Turing machines; Gödel number; P/NP problem

Teaching methods

Lecture in interaction with the students, with blackboard writing and projection
Exercise accompanying the lecture
Solving practical exercises in individual or team work
Group work
Individual work
Presentation
Mini-exams during the semester for regular feedback

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

written written examination
study achievements during the semester (bonus points)

Requirements for the awarding of credit points

passed written exam

Applicability of the module (in other degree programs)

Bachelor's degree in Software and Systems Engineering (dual)
Bachelor of Computer Science
Bachelor's degree in Medical Informatics
Bachelor of Computer Science Dual

Literature

Hopcroft, J.E., Motwani, R., Ullman, J.D.; Einführung in die Automatentheorie, Formale Sprachen und Berechenbarkeit; Pearson Studium; 3. Auflage; 2011
Hoffmann, D.W.; Theoretische Informatik; Hanser; 3. Auflage; 2015
Hedtstück, U.: Einführung in die Theoretische Informatik; Oldenbourg; 5. Auflage; 2012
Erk, K., Priese, L.; Theoretische Informatik; Springer; 4. Auflage; 2018

2. Semester of study

Algorithmen und Datenstrukturen
PF

4 SWS

5 ECTS

Number
42012
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

Students will have mastered selected algorithms and data structures after completing the lecture. They can analyze and qualitatively evaluate algorithms.

Technical and methodological competence:

You will acquire basic analytical skills to be able to evaluate, compare and explain algorithms and data structures and their properties. This competence also includes the ability to familiarize themselves independently with applications (such as APIs and development environments).

You have the implementation skills to transfer data structures and algorithms into object-oriented programs and to use predefined data structures and algorithms in libraries, such as the collections in Java, to solve problems.

You will acquire the formal competence to identify the core of a simple problem and to formulate and use suitable algorithms and data structures to solve it. They recognize the recursive core of a problem and can use a recursive problem-solving strategy. They have the competence to assign selected problems to known problem classes.

Design, analysis and runtime behavior of algorithms
Recursion
Search and sorting methods
Lists, trees, graphs, hash tables
Reference to modern class libraries such as Java Collections
Design methods, e.g. divide&conquer, backtracking
Algorithmic problem classes

Teaching methods

Lecture in interaction with the students, with blackboard writing and projection
Exercise accompanying the lecture
Internship accompanying the lecture
Group work

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

written written examination
study achievements during the semester (bonus points)

Requirements for the awarding of credit points

passed written exam

Applicability of the module (in other degree programs)

Bachelor of Business Informatics
Bachelor of Software and Systems Engineering (dual)
Bachelor of Computer Science
Bachelor's degree in Medical Informatics
Bachelor of Medical Informatics Dual
Bachelor of Computer Science Dual

Literature

H. Balzert, Lehrbuch Grundlagen der Informatik, Elsevier 2004
G. Saake, K. Sattler, Algorithmen und Datenstrukturen, dpunkt.verlag 2021

Lern- u. Arbeitstechniken
PF

2 SWS

2 ECTS

Number
411031
Language(s)
de
Duration (semester)
1
Contact time
30 h
Self-study
45 h

Learning outcomes/competences

Interdisciplinary methodological competence:

The participants know professional standards and procedures in the field of learning and working techniques (including time and self-management, learning theory, communication and effective collaboration as well as creativity techniques).
The students can apply these across disciplines

Self-competence:

The participants are able to use learning methods, communication and presentation techniques, creativity and problem-solving techniques as well as methods of time and self-management profitably for themselves in their studies and work.

Social skills:

The participants know techniques for effective collaboration in groups.
Students know how to present content in groups.
Students are familiar with creativity and problem-solving techniques for groups.

The course includes modules on the following topics:

Learning techniques and learning types
Working techniques (literature research in the library)
Time and self-management
Motivation
Communication techniques and collaboration
Creativity and problem-solving techniques
Burnout
Basics of scientific work
Mentoring discussions (include questions about choosing a course of study, organizing studies, individual time and learning planning, dealing with difficult situations and preparing for internships)

Teaching methods

Seminar-style teaching with flipchart, smartboard or projection

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

Homework

Requirements for the awarding of credit points

Successful homework
Participation in at least 80% of the attendance dates
Participation in the mentoring program

Applicability of the module (in other degree programs)

Bachelor of Business Informatics
Bachelor of Software and Systems Engineering (dual)
Bachelor of Computer Science
Bachelor's degree in Medical Informatics
Bachelor of Medical Informatics Dual
Bachelor of Computer Science Dual

Literature

Friedrich Rost; Lern- und Arbeitstechniken für das Studium; Vs Verlag 6. Auflage 2010; ISBN-13: 978-3531172934

Begründung zur Teilnahmeverpflichtung

Die Studierenden sollen durch die Lehrveranstaltung in die Lage versetzt werden, verschiedene Lern-, Arbeits-, Kommunikations- und Selbstmanagementechniken in ihrem Studium und beruflichen Alltag anzuwenden. Das Erlernen dieser Kompetenzen erfordert durch ihre Natur sowohl eine intensive Zusammenarbeit mit und persönliche Anleitung durch die jeweiligen Dozent/-innen, als auch eine Vielzahl praktischer Arbeiten in der Gruppe unter aktiver Supervision durch die Dozent/-innen. Um diese Ziele zu erreichen, ist eine Mindestanwesenheitspflicht in dieser Lehrveranstaltung erforderlich.

Mathematik für Informatik 2
PF

4 SWS

5 ECTS

Number
41061
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

After successful participation in the module:

the students have understood the proof principle of complete induction and can apply it.
the students are familiar with the Cartesian representation of complex numbers and can apply the basic arithmetic operations to complex numbers.
the students know the concept of functions and can determine and name the properties of functions.
the students are able to determine the limit behavior of sequences, series and functions.
the students are able to determine Taylor series and approximate functions with the help of Taylor polynomials.
can differentiate and integrate functions and use this knowledge in applications (e.g. extreme value calculations, de l'Hospital's rule, area calculations).
know functions in higher dimensions. They can determine extreme points of these functions and calculate multidimensional integrals.

Number ranges, full induction
Functions: Polynomials, rational functions, exponential and logarithmic functions, trigonometric functions and their inverse functions, and other elementary functions
Convergence of sequences and series
Limit values and continuity of functions, calculation of zeros of functions
Differentiability of functions; one- and multidimensional differential calculus
Rule of de l'Hospital
Taylor series expansion, approximation of functions by polynomials
Local and global extrema of functions in one or more variables
Integration of continuous functions in one and more variables (antiderivative, partial integration, substitution rule)

Teaching methods

Lecture in interaction with the students
lecture-accompanying exercise
active, self-directed learning through tasks and accompanying materials

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

The module examination consists of a written exam in which students should recall and remember basic knowledge of the content covered. In addition, they should be able to transfer and apply this knowledge to new issues.
Duration: 90 minutes.

Requirements for the awarding of credit points

The performances are graded and must be completed with a minimum grade of sufficient (4.0).

The performance is considered at least sufficient if at least 50% of the possible points are achieved in both the basic part and the entire examination.

Applicability of the module (in other degree programs)

Bachelor of Computer Science
Bachelor's degree in Medical Informatics
Bachelor of Medical Informatics Dual

Literature

Forster, O.: Analysis 1, Wiesbaden, Springer Spektrum, 2023, 13. Auflage.
Forster, O.: Analysis 2, Wiesbaden, Springer Spektrum, 2025, 12. Auflage.
Papula, L.: Mathematik für Ingenieure und Naturwissenschaftler Band 1 , Wiesbaden, Springer Vieweg, 2024, 16. Auflage.
Papula, L.: Mathematik für Ingenieure und Naturwissenschaftler Band 2 , Wiesbaden, Springer Vieweg, 2025, 15. Auflage.
Teschl, G. & Teschl, S.: Mathematik für Informatiker Band 2, Wiesbaden, Springer Vieweg, 2014, 3. Auflage

Mathematik für Informatik 3
PF

4 SWS

5 ECTS

Number
42073
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

Acquisition of basic knowledge of applied statistics and the ability to select and apply descriptive and inductive statistical methods to solve problems of practical relevance.

Technical and methodological competence:

Acquisition of methodological basics of descriptive and inferential statistics
Describing essential structures in data by selecting suitable descriptive means
Converting problems into random variables and suitable distribution assumptions
Drawing inferences from samples to populations using parameter and interval estimation
Formulation of test problems and independent implementation of hypothesis tests
First experience with the computer-aided analysis of data

Interdisciplinary methodological competence:

Supporting decision-making processes through descriptive data analysis and statistically sound statements
Transferring estimation and test procedures to problems in computer science
Applying statistical methods in connection with the evaluation of databases
Simulation of stochastic processes with the help of theoretical distributions
Derivation of forecasts with the help of statistical estimation methods

Empirical frequency distributions and graphical representations
Location measures, measures of dispersion and box plots
Measures of correlation and exploratory regression
Concept of probability, random events, Laplace model
Combinatorics
Conditional probability, independence of events, Bayes' theorem
Distribution and parameters of discrete random variables
Equal distribution, binomial distribution, hypergeometric distribution
Distribution and parameters of continuous random variables
Equal distribution, normal distribution, central limit theorem
Point estimators and their properties
Confidence intervals for expected value and proportion value
Testing hypotheses, binomial test, Gaussian test, t-test
Independent computer-aided analysis of data sets, e.g. in Excel. Python or R

Teaching methods

Lecture in interaction with the students, with blackboard writing and projection
Solving practical exercises in individual or team work
Processing programming tasks on the computer in individual or team work
Active, self-directed learning through internet-supported tasks, sample solutions and accompanying materials

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

written exam paper

Requirements for the awarding of credit points

passed written exam

Applicability of the module (in other degree programs)

Bachelor's degree in Business Informatics
Bachelor of Computer Science
Bachelor's degree in Medical Informatics
Bachelor of Medical Informatics Dual

Literature

Fahrmeir et al.; Statistik: Der Weg zur Datenanalyse; Springer; Berlin Heidelberg; 8. Auflage; 2016
Vorlesungsskript

Programmierkurs 1
PF

4 SWS

5 ECTS

Number
42021
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

Providing the knowledge required to implement application software from a professional point of view. This includes the realization of graphical user interfaces, the connection of technical concept classes and the persistence of data. Concepts of object-oriented programming are applied in a problem-oriented manner.

Technical and methodological competence:

Implementing flexible systems through the use of polymorphism and interfaces
Recognizing the advantages of regulated exception handling
Implementing a flexible graphical user interface using components and layout managers
Using data streams
Identifying and solving concurrent programming problems
Reusing components via the targeted use of an application programming interface (API)

Interdisciplinary methodological competence:

Application of programming techniques in the implementation of commercial, technical and multimedia applications

In-depth study of object-oriented programming in Java (abstract classes, interfaces, polymorphism)
Professional exception handling via exceptions
Use of collections for object management
Access to the file system and organization of files (Java IO)
Use of data streams
Serialization of objects
Programming graphical user interfaces (JavaFX)
Event handling
Concurrent programming (threads)
Java Stream API and lambda expressions
Architecture of application programs from an implementation perspective

Teaching methods

Lecture in interaction with the students, with blackboard writing and projection
Solving practical exercises in individual or team work
Processing programming tasks on the computer in individual or team work

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

written exam paper

Requirements for the awarding of credit points

passed written exam

Applicability of the module (in other degree programs)

Bachelor's degree in Business Informatics
Bachelor of Computer Science
Bachelor's degree in Medical Informatics
Bachelor of Medical Informatics Dual

Literature

Horstmann, C., Cornell, G.; "Core Java, Volume 1: Fundamentals", Pearson, Boston, 2018
Horstmann, C., Cornell, G.; "Core Java, Volume 2: Advanced Feature", Prentice Hall, Boston, 2016
Krüger, G., Hansen, H.; "Java-Programmierung - Das Handbuch zu Java 8", OReilly Verlag, Köln, 2014
Urma, R.-G., Fusco, M., Mycroft, A.; "Java 8 in Action: Lambda, streams, and functional-style programming", Manning, 2015
Epple, A.; "Java FX 8", dpunkt.verlag, Heidelberg, 2015
Sharan, K.; "Learn JavaFX8", Apress, Springer Science, New York, 2015
Sierra, K., Bates, B.; "Head First Java", OReilly, 2005

Rechnerstrukturen und Betriebssysteme 2
PF

4 SWS

5 ECTS

Number
42032
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

Students will be able to understand and explain the functioning of the elementary components of an operating system: process and thread management, mechanisms for communication and synchronization. Furthermore, students will be able to evaluate advanced computer structures.

Professional competence:

implement system programs on the basis of system calls
implement concurrent applications with processes and threads.
differentiate the means of inter-process communication.
recognize the problems of race conditions, select suitable synchronization mechanisms and avoid deadlocks.

Social skills:

Solving programming tasks in groups of two
Presenting the results to the supervisor

Operating system programming (C, JAVA and Java Native Interface (JNI))
Threads (thread model, comparison to processes, threads in Unix and Windows)
Communication (pipes, FIFOs, semaphores, shared memory, sockets, RPC)
Synchronization of processes and threads (race condition, mutual exclusion, semaphore, monitor, deadlock)
Input and output (hardware, interrupt, DMA, driver)
Multiprocessor systems (hardware, scheduling, synchronization)
Virtual machines (overview of machine types, JavaVM as a virtual stack machine, instruction set of JavaVM)
Case study (e.g. Linux/Android, Windows)

Teaching methods

Lecture in interaction with the students, with blackboard writing and projection

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

written written examination
study achievements during the semester (bonus points)

Requirements for the awarding of credit points

passed written exam

Applicability of the module (in other degree programs)

Bachelor's degree in Software and Systems Engineering (dual)
Bachelor of Computer Science
Bachelor of Computer Science Dual

Literature

Tanenbaum, A.S.; Moderne Betriebssysteme; Pearson Studium; 2009
Stallings, W.; Operating Systems; Prentice Hall, 2006
Glatz, R.; Betriebssysteme; dpunkt.verlag, 2010
Tanenbaum, A.S.; Computerarchitektur: Strukturen - Konzepte - Grundlagen, Pearson Studium, 2006

Studium Generale
PF

2 SWS

2 ECTS

Number
411033
Duration (semester)
1

Technisches Englisch
PF

2 SWS

2 ECTS

Number
41102
Language(s)
en
Duration (semester)
1
Contact time
30 h
Self-study
45 h

Learning outcomes/competences

After successful completion of the module, students will be able to:

Present technical content correctly and comprehensibly in English
Use subject-specific vocabulary from IT and technology with confidence.
Structure presentations logically and convey technical information in a target group-oriented way.
Participate actively and constructively in technical discussions in English
Perform academic work and presentations in English (e.g. citing and using sources).

Basics of technical English:
- Introduction to technical vocabulary
- Description of technical objects and processes.
Presentation techniques:
- Structuring presentations (introduction, main part, conclusion)
- Use of visual aids (diagrams, tables, images).
- Rhetorical devices and presentation phrases.
Scientific work:
- Correct source references and citation techniques
- Summary of technical content in a precise form.
Discussion techniques:
- Asking questions, giving feedback and arguing in discussions
Practical application:
- Semester-accompanying presentations on technical IT topics.

Teaching methods

Seminar-style teaching in English
Practical exercises:
- Oral and written exercises to describe technical content
- Discussions and role plays on current IT topics.
Presentation workshops: Preparation and delivery of presentations.
Independent research and academic work.

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

R ("Unit")

Requirements for the awarding of credit points

Passed presentation (10-15 minutes) on a technical topic during the semester, followed by a Q&A session.
Attendance and active participation in at least 9 courses.

Applicability of the module (in other degree programs)

Bachelor of Business Informatics
Bachelor of Software and Systems Engineering (dual)
Bachelor of Computer Science
Bachelor's degree in Medical Informatics
Bachelor of Medical Informatics Dual
Bachelor of Computer Science Dual

Literature

A1:
"Fairway. A1. Lehr- und Arbeitsbuch"; Herbert Puchta, Klett Verlag, 2005, ISBN-10: 3125014603
A2, B1, B2:
Williams, E., Kleinschroth, R., Courtney, B. (2018). "Matters Technik - IT Matters 3rd Edition: B1/B2 - Englisch für IT-Berufe". Cornelsen Verlag. ISBN-13: 978-3-06-451522-2 (E-Book: ISBN 978 – 3 –06-451523 – 9)

3. Semester of study

Datenbanken 1
PF

4 SWS

5 ECTS

Number
43052
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

Technical and methodological competence:

Know the definition of a DBS and the schema architecture of a DBMS.
Know the transaction concept and recovery mechanisms.
Know and use SQL commands for setting up, storing and querying information (DDL, DML, DRL, DCL).
Exemplarily carry out the administration of database systems.
Develop stored functions, procedures and triggers.

Social skills:

Developing, communicating and presenting relational models and database programs in teams of two
Collaboratively creating and evaluating learning posters or review questions on the course content.

Professional field orientation:

Know the requirements of different job profiles in the database environment (database administrator. Database developer, application developer, data protection officer)

Database and transaction concept
Relational model and operations
SQL Data Definition Language and Database Integrity
SQL Data Manipulation Language
SQL Data Retrieval Language
SQL Views
Roles and rights management
Stored functions, procedures and triggers
Backup and recovery

Teaching methods

seminar-style teaching with flipchart, smartboard or projection
Solving practical exercises in individual or team work
Processing programming tasks on the computer in individual or team work
active, self-directed learning through tasks, sample solutions and accompanying materials
Exercises or projects based on practical examples
mini-exams during the semester for regular feedback
The lecture is offered as a video
Inverted teaching (inverted classroom)

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

written examination paper
examinations during the semester

Requirements for the awarding of credit points

passed written examination
successful internship project (project-related work)

Applicability of the module (in other degree programs)

Bachelor of Business Informatics
Bachelor of Software and Systems Engineering (dual)
Bachelor of Computer Science
Bachelor's degree in Medical Informatics
Bachelor of Medical Informatics Dual
Bachelor of Computer Science Dual

Literature

Beighley, L., SQL von Kopf bis Fuß, O'Reilly, 2008.
Kemper, A., Wimmer, M.; Übungsbuch Datenbanksysteme, Oldenbourg; 2. aktualisierte Auflage, 2009.
Saake, G., Sattler, K., Heuer A., Datenbanken - Konzepte udn Sprachen, 6. Auflage, mitp, 2018.

Elektronik
PF

4 SWS

5 ECTS

Number
43211
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

The student is given an overview of the topics and most important contents of electronics, based on the fundamentals of electrical engineering. The aim is for the student to know the most important electronic components and be able to use them to implement simple circuits.

Technical and methodological skills:

knows electronic components and can analyze and calculate given simple circuits.
can close the gap between physical effects (physics course) and the application of digital circuit technology (e.g. hardware engineering)
can design and analyze simple circuits
knows the relevant orders of magnitude and units of measurement
knows metrological procedures and can apply them in a real laboratory situation
the trail-and-error method used in programming work is reflected on and reconsidered, as it does not lead to success in the laboratory situation (successful and certified completion of an experiment is therefore assessed as a semester-long course achievement with two bonus points)

Social skills:

can prepare, carry out and evaluate laboratory experiments in a team
can document the results and present them to the supervisor

Current/voltage/ohmic resistance
Row and parallel circuits, mesh and node rule
Capacitor and coil
Complex alternating current calculation, high-pass/low-pass, transfer functions
Diodes and diode circuits
Bipolar transistors, field-effect transistors, basic circuits
Operational amplifiers, basic circuits
Vibration generation, resonant circuits
Logic circuits, NMOS, PMOS, CMOS circuits
SRAM, DRAM, EEPROM, Flash

Teaching methods

Lecture in interaction with the students, with blackboard writing and projection
Solving practical exercises in individual or team work

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

written written examination
study achievements during the semester (bonus points)

Requirements for the awarding of credit points

passed written exam

Applicability of the module (in other degree programs)

Bachelor's degree in computer science

Literature

Zastrow, D.: Elektronik, 9. Auflage, Vieweg + Teubner, 2010
Herberg, H.: Elektronik Einführung für alle Studiengänge, Vieweg, 2002
Böhmer, E.: Elementer der Elektronik - Repetitorium und Prüfungstrainer, 7. Auflage, Vieweg + Teubner, 2009
Lindner, H.: Elektro-Aufgaben, Band 1 + 2, 29. + 23. Auflage, Hanser, 2007

Mathematik für Informatik 4
PF

4 SWS

5 ECTS

Number
41067
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

Students know solution methods for the treatment of ordinary differential equations and can apply these methods. Students on the course also know special numerical and number theory procedures for solving computer science-related problems.

Technical and methodological competence:
Students have reliable knowledge of the possible solutions to differential equations and special problems in numerics and number theory: they are familiar with solution patterns for such problems and are able to transfer mathematical methods to other problems.

Interdisciplinary methodological competence:
Students are able to recognize that mathematical methods can be used to describe the properties of technical systems (e.g. control and regulation systems, signal processing) and analyze their behavior.

Self-competence:
Students can present ideas and proposed solutions in writing and orally, the independent presentation of solutions contributes to the development of self-confidence/professional competence; the development of strategies for acquiring knowledge and skills is supported by the combination of seminar-style lectures and intensive practice phases with continuous feedback.

Social skills:
Cooperation and teamwork skills are trained during the practice phases. Students can argue in discussions in a goal-oriented manner and deal with criticism objectively; they can recognize and reduce existing misunderstandings between discussion partners.

Orientation to the professional field:
Communication with cooperation partners from technology-specific subject areas/departments is made easier as they have become familiar with the relevant language schemes within mathematics education.

1st order differential equations
Higher-order linear differential equations with constant coefficients
Laplace transformation and linear differential equations with constant coefficients, convolution theorem
Fourier series, Fourier transform, sampling theorem
Characterizing functions of linear differential equations (transfer function, impulse, step and frequency response, stability)
Newton method and numerical integration
Gradient descent method
Numerics of differential equations
Equivalence classes, groups, rings
Divisibility and prime numbers, Euclid's algorithm and Diophantine equations
Congruences
Homomorphism/isomorphism on groups

Teaching methods

Lecture in seminar style, with blackboard and projection
Exercise to accompany the lecture
Solving practical exercises in individual or team work
Processing programming tasks on the computer in individual or team work
active, self-directed learning through tasks, sample solutions and accompanying materials
exercises or projects based on practical examples
immediate feedback and success monitoring

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

written written examination
study achievements during the semester (bonus points)

Requirements for the awarding of credit points

passed written exam

Applicability of the module (in other degree programs)

Bachelor's degree in computer science

Literature

Skript zum Kurs.
Fischer, G.: Lineare Algebra, Wiesbaden, Springer-Spektrum, 2014, 18. Auflage.
Heuser, H.: Gewöhnliche Differentialgleichungen, Wiesbaden, Vieweg-Teubner, 2009, 6. Auflage.
Knabner, P.; Barth, W.: Lineare Algebra, Berlin-Heidelberg, Springer-Spektrum, 2018, 2. Auflage.
Liesen, J; Mehrmann, V.: Lineare Algebra, Wiesbaden, Springer-Spektrum, 2015, 2. Auflage.
Weber, H.; Ulrich, H.: Laplace-, Fourier- und Z-Transformation, Wiesbaden, Vieweg + Teubner, 2012, 9. Auflage.

Physik
PF

4 SWS

5 ECTS

Number
43212
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

Technical and methodological competence:

Know and be able to explain basic physical laws, models and idealizations for describing physical processes from classical physics and atomic physics.
Prepare, carry out and evaluate exemplary physical experiments.

Social skills:

Developing, communicating and presenting physical calculations in partner work
Preparing, carrying out and evaluating physics experiments in a cooperative manner.
Creating and evaluating revision questions on the teaching content.

Mechanics
- Kinematics
- Dynamics
- Maintenance laws
- Vibrations and waves
Electrodynamics
- Electrostatic
- Magnetostatics
- Electromagnetic induction
- Maxwell's equations
- Electromagnetic waves
Atomic and solid state physics
- Atomic models
- Conduction mechanisms in metals and semiconductors
- Technical applications of physical effects in hardware components (e.g. transistor, laser)

Teaching methods

Lecture in seminar style, with blackboard writing and projection
Solving practical exercises in individual or team work

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

written written examination
study achievements during the semester (bonus points)

Requirements for the awarding of credit points

passed written exam

Applicability of the module (in other degree programs)

Bachelor's degree in computer science

Literature

Paul Dobrinski ; Gunter Krakau ; Anselm Vogel: Physik für Ingenieure, Teubner, 2006
Christian Gerthsen, Hans O. Kneser, Helmut Vogel: Physik, Springer, 1989
Ulrich Harten: Physik - Einführung für Ingenieure und Naturwissenschaftler, Springer, 2007

Programmierkurs 2 TI
PF

4 SWS

5 ECTS

Number
43025
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

Technical and methodological competence:

After completing the course, students will be able to

implement programs in C/C++
apply programming techniques for embedded systems.
apply a systematic development process with IDE, documentation, versioning and developer testing.

Social skills:

Solving more complex development tasks (hardware configuration, software development) in groups of two
Presenting the results to the supervisor

Organization of C projects
Role of the preprocessor
C programming language C (in the C99 version)
- Control structures, scalar data types, arrays, strings
- Structures, unions, bit fields, enumeration types, type definitions
- Pointer concept, operations on pointers, arrays/strings, memory management with malloc()
- Call-by-reference, string operations, data structures, typ. Errors
- Functions and libraries: parameter passing, main(), memory classes, function pointers, overview of relevant libraries
Programming techniques for embedded systems
- Standard integer types, access to hardware registers
- Concurrent programming with interrupts, state machines
C++
- Changes compared to C (namespaces, references, )
- Classes
- Inheritance
- Templates
- Qt Application Framework
Tools (e.g. Eclipse/CDT, gcc, doxygen, SVN and CUnit)

Teaching methods

Lecture in interaction with the students, with blackboard writing and projection
Solving practical exercises in individual or team work

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

written written examination
study achievements during the semester (bonus points)

Requirements for the awarding of credit points

passed written exam

Applicability of the module (in other degree programs)

Bachelor's degree in computer science

Literature

Carsten Vogt; C für JAVA Programmierer , Hanser, 2007
Ulrich Breymann; Der C++ Programmierer , Hanser, 2015
Achim Köhler; Der C/C++ Projektbegleiter dpunkt.Verlag, 2007
Jasmin Blanchette, Mark Summerfield; C++ GUI Programmierung mit Qt 4: Die offizielle Einführung , Addison Wesley, 2008

Softwaretechnik 1
PF

4 SWS

5 ECTS

Number
43051
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

Introduction to the implementation of software projects with a special focus on the early phases of development and modeling of software-based solutions with the help of creative methods (e.g. design thinking) and the methods of requirements engineering. Consideration of the integration of AI-based modules in the development process and in the design of the software project, taking into account social implications and regulatory framework conditions.

Modeling of the software system with the Unified Modeling Language (UML) and Domain Driven Design (DDD) methods. Knowledge of various process models and practical experience with agile methods such as Scrum.

Technical and methodological competence:

Overview of procedure and process models of software development
Name and apply various requirements engineering methods
- Differentiate, specify and formulate user and system requirements
- Verifying and validating requirements
Overview of the consequences of digitalization and digital transformation with a special focus on the effects in the area of software engineering

Knowing and applying innovation methods
Be able to integrate AI-based modules into the development process

a) Impact on the development process
b) Consideration of regulatory framework conditions
c) Analysis of social implications

Describe the methodological approach in object-oriented analysis
Know and apply the relevant UML description tools in the context of OOA

UML use case diagram
UML package diagram
UML class diagram
UML activity diagram
UML sequence diagram
UML communication diagram
UML state diagram

Interdisciplinary methodological competence:

Modeling the static and dynamic aspects of an OOA model for an object-oriented software system to be developed
Object-oriented specification of software systems using the Unified Modeling Language (UML)
Creation of a technical concept or product model for a software system
Recognizing contradictions, incompleteness, inconsistencies

Social skills:

Systematically analyze problems of medium complexity in a team
Develop a requirements specification in a cooperative and collaborative team
Specify an OOA model for a software system in a cooperative and collaborative team

General basics of software engineering (motivation, definitions, goals,...)
Procedure models (classic to agile)
Fundamental terms, phases, activities and procedures in the context of requirements engineering
Digitalization, change and creative methods in the context of software engineering
Peculiarities of the integration of AI-based modules
Fundamental terms, methods and notation in the context of object-oriented analysis (OOA) and domain-driven design (DDD)
Object-oriented analysis with UML (including use cases, packages, activity diagram, class diagram, state diagram, scenario)
Analysis patterns, static/dynamic concepts and sample applications
Checklists for the OOA model
Components and contents of the OOA documentation

Teaching methods

Lecture in interaction with the students, with blackboard writing and projection
Internship to accompany the lecture
Project work accompanying the lecture with final presentation
Workshops
Group work
Individual work
Case studies
Excursion
Project work
The lecture is offered as a video
Inverted classroom teaching
Concluding presentation

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

Oral examination
Project work with oral examination
Homework
Presentation

Requirements for the awarding of credit points

successful project work
successful term paper
successful presentation
successful internship project (project-related work)
participation in at least 90% of the attendance dates for exercise and internship

Applicability of the module (in other degree programs)

Bachelor of Business Informatics
Bachelor of Software and Systems Engineering (dual)
Bachelor of Computer Science
Bachelor's degree in Medical Informatics
Bachelor of Medical Informatics Dual
Bachelor of Computer Science Dual
Bachelor of Computer Science Dual

Literature

Balzert, H. (2009): Lehrbuch der Softwaretechnik - Basiskonzepte und Requirements Engineering (3. Aufl.), Heidelberg: Spektrum Akademischer Verlag.

Ludewig, J.; Lichter, H. (2013): Software Engineering - Grundlagen, Menschen, Prozesse, Techniken, 3. korrigierte Auflage, Heidelberg: dpunkt-Verlag.
Oestereich, B., Scheithauer, A. (2013): Analyse und Design mit UML 2.5, 11. Auflage, München: Oldenbourg Verlag.
OMG (2017): UML Specification Version 2.5.1, http://www.omg.org/spec/UML/2.5.1/PDF.
Pichler, R. (2008): Scrum, Heidelberg: dpunkt-Verlag.
Pohl, K., Rupp, C. (2015): Basiswissen Requirements Engineering, 4. überarbeitete Auflage, Heidelberg: dpunkt-Verlag.
Rupp et. al. (2012): UML 2 glasklar. 4. Auflage, Hanser-Verlag.
Sommerville, I. (2012): Software Engineering, 9. Auflage, München: Pearson Studium.

Begründung zur Teilnahmeverpflichtung

Die Studierenden erarbeiten in Teamarbeit sowohl kreative Lösungen als auch formale Beschreibungen für konkrete Fragestellungen und UseCases aus der Industrie. Dabei werden Sie von den Lehrkräften begleitet und gecoacht. Um die dabei gemachten Erfahrungen zu analysieren und die sich daraus ergebenden Lernziele zu erreichen ist eine Mindestanwesenheitspflicht im Praktikum erforderlich.

4. Semester of study

Automatisierungstechnik
PF

4 SWS

5 ECTS

Number
44233
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

Technical and methodological competence:

After completing the lecture, students will be able to

Understand and apply automation technology methods and concepts
Design and implement automation technology applications
Model continuous-time dynamic systems and simulate them with Matlab/Simulink
apply classical methods of controller synthesis
Design classic PID controllers and fuzzy controllers and implement them in software
Identify and control non-linear dynamic systems using artificial neural networks

Introduction
- Objectives of control and regulation of technical systems
- Model-based development of dynamic systems
- Basic structures of closed-loop and open-loop control systems
- Modeling and simulation of dynamic systems
Fuzzy control
- Fuzzy logic
- Fuzzy controller according to Mamdani
- Fuzzy controller according to Sugeno
- Synthesis of fuzzy controllers with Matlab/Simulink
Neural Network Control
- Mathematical model of neural networks
- Direct Inverse Control
- Model Reference Control
- Internal Model Control
- Feed-Forward Control
- Neuro Fuzzy Systems
Reinforcement Learning
- Optimal Control
- Computational decision making
- Learning algorithms
Design of intelligent control systems
- Stability criteria
- Model-based design of control loops
- Realization in software and hardware
- Code generation with Matlab/Simulink
Extended controller structures

Teaching methods

Lecture in interaction with the students, with blackboard writing and projection
Exercise accompanying the lecture
Solving practical exercises in individual or team work
Internship accompanying the lecture

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

written written examination
study achievements during the semester (bonus points)

Requirements for the awarding of credit points

passed written exam

Applicability of the module (in other degree programs)

Bachelor of Computer Science
Bachelor of Software and Systems Engineering (dual)

Literature

Marco P. Schoen: Introduction to Intelligent Systems, Control, and Machine Learning Using MATLAB, Cambridge University Press, 2023
Heinz Unbehauen: Regelungstechnik I, Klassische Verfahren zur Analyse und Synthese linearer kontinuierlicher Regelsysteme, Fuzzy-Regelsysteme, 15. Auflage, Vieweg-Verlag, 2008
S.N. Sivanandam, S. Sumathi, S. N. Deepa: Introduction to Fuzzy Logic using MATLAB, Springer-Verlag, 2007
Adamy, Jürgen: Fuzzy-Logik, neuronale Netze und evolutionäre Algorithmen, 5. Auflage, Shaker Verlag, 2019

Embedded Systems
PF

4 SWS

5 ECTS

Number
44114
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

After successfully completing the module, students will be able to:

Knowledge and understanding

explain the structure, functionality and programming of microcontrollers (incl. interrupts, timers, PWM)
explain scheduling procedures and preemptive multitasking in embedded systems as well as the use of FreeRTOS.
Describe power management strategies and low-power modes in microcontrollers.
Explain debugging tools such as GDB and OpenOCD.

Use, application and generation of knowledge

Programming and controlling microcontrollers (interrupts, timers, PWM)
implement scheduling strategies and preemptive multitasking and configure a real-time operating system such as FreeRTOS
Integrate sensors, troubleshoot error sources and perform D/A conversion and DC motor control
implement power management strategies in software and test embedded software with debugging tools.

Communication and cooperation

communicate and document technical solutions clearly
work in teams on projects and present results

Scientific self-image / professionalism

Evaluate and optimize embedded software solutions
to consider ethical implications in the development of embedded systems
to reflect on and scrutinize developments in embedded systems.

Microcontroller:
- Design and structure of a typical microcontroller
- Programming and control: interrupt control, timer/counter, watchdogs, capture/compare, PWM
- Scheduling methods for embedded systems with and without an operating system
- Preemptive multitasking and static priorities in embedded systems
- Introduction to FreeRTOS and building a simple real-time operating system
Sensor technology:
- Active and passive sensors
- A/D conversion and signal processing
- Transfer functions of sensors and their influence on the measurement results
- Systematic and statistical sources of error in sensor measurement and their effects
- Error propagation in sensor systems
Actuator technology:
- D/A conversion and control of DC motors
- Application of actuators in embedded systems
Energy-efficient software development:
- Power management strategies for software
- Utilization of sleep and low-power modes in microcontrollers to save energy
Monitoring, debugging and test strategies:
Use of JTAG, SWD and debugging tools such as GDB and OpenOCD
Debugging embedded software

Internship and application examples:

Introduction to the internship board and practical implementation

Basics of autonomous robotics

Real-time control in practical examples (e.g. motor control and sensor integration)

Teaching methods

Lecture in interaction with the students, in which theoretical principles are taught and illustrated using blackboard notes and projections. This is supplemented by practicals and exercises accompanying the lectures, in which students work on practical programming tasks alone or in teams. Project work is also carried out, the results of which are presented in a final presentation. The courses include practical applications of embedded systems in realistic scenarios

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

Written examination paper [scope: 100%] (90min); examinations during the semester (bonus points)

Requirements for the awarding of credit points

Passing a 90-minute graded written exam with a minimum grade of sufficient (4.0)

Applicability of the module (in other degree programs)

Bachelor's degree in computer science

Literature

Berns, K., Schürmann, B., Trapp, M.: Eingebettete Systeme, Systemgrundlagen und Entwicklung eingebetteter Software, Vieweg+Teubner, 2010.
Brinkschulte, U., Ungerer, T.: Mikrocontroller und Mikroprozessoren, Springer, Berlin, 2010.
Fraden, Jacob: Handbook of modern sensors: physics, design, and applications,
Springer-Verlag New York, Inc., 5th ed., 2015.
The FreeRTOS Reference Manual, http://www.freertos.org/, Amazon.com, 2017.
Douglass, B. P.: Design Patterns for Embedded Systems in C, Newnes Elsevier, 2011.
Brandes, U.: Mikrocontroller ESP32, Rheinwerk Technik, Bonn, 2020
ausgewählte Datenblätter von Sensor- und Mikrocontroller-Herstellern (werden in der Veranstaltung bekannt gegeben)

Kommunikations- und Rechnernetze
PF

4 SWS

5 ECTS

Number
46832
Language(s)
en, de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

Technical and methodological competence:

After completing the course, students will be able to

Understand the principles, protocols and architecture of the internet
Use elementary commands of the Linux and Windows operating systems for network configuration and network testing
Perform and interpret protocol and network analyses with analysis tools
Analyze existing wired and wireless networks
Design and implement wired and wireless networks
Configure network components (router, switch) including VLAN and NAT

Reference models (ISO/OSI, TCP/IP)
Bit transmission layer, transmission media
Ethernet, network components: Hub, switch, router; virtual LANs (VLAN)
IP protocols, addressing, routing
Network Address Translation (NAT)
Protocols of the transport layer
IPv6, IPSec, SSL/TLS
Wireless communication

Teaching methods

Lecture in interaction with the students, with blackboard writing and projection
Exercise accompanying the lecture
Processing programming tasks on the computer in individual or team work

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

written written examination
study achievements during the semester (bonus points)

Requirements for the awarding of credit points

passed written exam

Applicability of the module (in other degree programs)

Bachelor of Business Informatics
Bachelor of Software and Systems Engineering (dual)
Bachelor of Computer Science
Bachelor of Computer Science
Bachelor's degree in Medical Informatics
Bachelor of Medical Informatics Dual
Bachelor of Computer Science Dual
Bachelor of Computer Science Dual

Literature

Andrew S. Tanenbaum, David J. Wetherall; Computernetzwerke; Pearson Studium; 5. Auflage; 2012
Douglas E. Comer, Ralph Droms; Computernetzwerke und Internets; Pearson Studium; 3. Auflage; 2001

Softwaretechnik 2
PF

4 SWS

5 ECTS

Number
44121
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

Introduction to the topic of software architecture. Starting with terms, methods and perspectives, via architecture models in UML (distribution and component diagrams) to various architectural styles from classic to modern.

Students learn how to convert OOA and/or DDD models into an implementation. In addition to business logic and design patterns, a key focus is on the classification and targeted use of tools/frameworks from the areas of communication, persistence and interface design.

Technical and methodological expertise:

Understanding the concepts of object-oriented design
Design and documentation of applications with UML
Understand the principles, patterns and aspects of software architecture
Defining, documenting and evaluating architectures
Describing the architecture and design process
Describing and classifying modern software techniques

Interdisciplinary methodological competence:

Thinking in systems
Designing and documenting target systems
Process-oriented approach

Social skills:

Working in small teams
Results-oriented group work

General basics of software architecture (concept, motivation, definitions, goals,...)
Architecture modeling with UML (distribution and component diagram)
Architecture drivers and overview of different architecture styles
Architectural principles and views
Tier architecture, brokers, component-based architecture, SOA, microservice architectures, cloud native architectures, etc.
Object-oriented design with UML
Design patterns
Communication frameworks and tools
Databases, persistence frameworks and tools
Frameworks and tools for interface design

Teaching methods

Lecture in interaction with the students, with blackboard writing and projection
Internship to accompany the lecture
Project work accompanying the lecture with final presentation
Workshops
Group work
Case studies
Excursion
Project work
The lecture is offered as a video
Inverted classroom teaching
Concluding presentation

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

Oral examination
Project work with oral examination
Homework
Presentation

Requirements for the awarding of credit points

successful project work
successful term paper
successful presentation
successful internship project (project-related work)
participation in at least 90% of the attendance dates for exercise and internship

Applicability of the module (in other degree programs)

Bachelor of Business Informatics
Bachelor of Software and Systems Engineering (dual)
Bachelor of Computer Science
Bachelor of Medical Informatics Dual
Bachelor of Computer Science Dual
Bachelor of Computer Science Dual

Literature

Bass et al: Software Architecture in Practice, 3. Auflage, Addison Wesley, 2012.
M. Fowler: Patterns für Enterprise Application-Architekturen, 1. Auflage (Taschenbuch), mitp, 2003.
Gamma et al.: Entwurfsmuster: Entwurfsmuster als Elemente wiederverwendbarer objektorientierter Software, mitp, 2014.
C. Richardson: Microservice Patterns. 1. Auflage, Manning Publications, 2018.
Rupp et al: UML 2 glasklar, 4. Auflage, Hanser-Verlag, 2012.
G. Starke: Effektive Softwarearchitekturen: Ein praktischer Leitfaden, 9. Auflage, Hanser-Verlag,2020.
Vogel et al: Software-Architektur: Grundlagen Konzepte Praxis, 2. Auflage, Spektrum, 2009.
E. Wolff: Microservices: Grundlagen flexibler Softwarearchitekturen, 1. Auflage, dpunkt-Verlag, 2015.

Systems Engineering
PF

4 SWS

5 ECTS

Number
44232
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

Students are familiar with the different levels of systems engineering: technical management and the path from system analysis and design to product realization.

They acquire knowledge about the classification of phase models and the interaction of the phases. Students will be able to apply UML and SysML and use them for technical applications. They are able to create project plans for complex projects.

Technical and methodological skills:

Explaining phase models and the interplay of project phases
Describe the sub-processes of systems engineering
Recognize the interaction between project management and system design
Applying requirements and risk management
Applying UML and SysML for technical applications in various project phases (UML: in-depth study only)

Interdisciplinary methodological competence:

Sketching the organization and process of large-scale projects for the development of complex technical systems
Applying methods and tools for planning complex projects

Professional field orientation:

Familiarity with the process of typical major projects
Insight into the work of a systems engineer

Characteristics and definition of systems
Project planning and management
Sub-processes of systems engineering, including life cycle models, system analysis,
Risk assessment, conceptual design, detailed design, implementation,
Quality assurance
Specific methods for describing system properties
- Modeling concurrent systems under real-time conditions
- Deepening finite automata as a means of description
Teaching knowledge of common tools and standards such as UML/SysML and ISO 15288

Teaching methods

Lecture in interaction with the students, with blackboard writing and projection
Solving practical exercises in individual or team work
Internship to accompany the lecture
Planning game

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

written written examination
study achievements during the semester (bonus points)

Requirements for the awarding of credit points

passed written exam

Applicability of the module (in other degree programs)

Bachelor's degree in computer science

Literature

INCOSE technical board, Systems Engineering Handbook , Version 4, INCOSE, www.incose.org, 2015.
Delligatti, L., "SysML distilled, a brief guide to the systems modeling language", Addison-Wesley, NJ, 2014.
Haberfellner et. al., Systems Engineering Methodik und Praxis , Orell Füssli Verlag, Zürich,
2012.
www.sysml.org

5. Semester of study

IT-Recht
PF

2 SWS

2 ECTS

Number
45202
Language(s)
de
Duration (semester)
1
Contact time
30 h
Self-study
45 h

Learning outcomes/competences

After attending the course, students will be able to master the legal basics and recognize problems in the context of the design of IT contractual relationships or IT law in general and its specific characteristics, including at EU level. They will learn the special features of the application of the law with regard to IT and will essentially be able to analyze and classify the existing connections between technology and law within the framework of our legal system. They are also able to independently break down the relevant technical issues into the existing legal environment and, on this basis, recognize the legal consequences of their actions and, at the same time, differentiate between those that can be implemented on their own and those that can only be implemented with qualified legal assistance. At the same time, they are also able to assess the consequences of the legal classification for technical development and implementation and to use this knowledge for their further practical work in order to design result-oriented technical processes and developments in a legally resilient manner and to take the path of legally secure IT solutions as part of project management.

Contract initiation and conclusion
Other terminology
IT law and general terms and conditions
Other typical problem areas
The end of contractual relationships
Choice of law
Ownership and acquisition of rights
Copyright
Warranty and guarantee / typical problem areas
Liability for breaches of duty and legal violations
Legal structuring of IT projects
Data protection
E-commerce
Liability/responsibility of the provider
Legal framework conditions of social networks
Cloud computing
Open source software
Compliance in the company and IT security
Compliance in the contract
BYOD
Advertising, telemarketing and law
Telephone, telecommunications, unified communications
IT security law

Teaching methods

Lecture in seminar style, with blackboard writing and projection

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

written exam paper

Requirements for the awarding of credit points

passed written exam

Applicability of the module (in other degree programs)

Bachelor's degree in Software and Systems Engineering (dual)
Bachelor of Computer Science
Bachelor of Medical Informatics Dual
Bachelor of Computer Science Dual

Literature

IT- und Computerrecht, Gesetzessammlung, Beck-Texte im dtv;
Telekommunikations- und Multimediarecht, Beck-Texte im dtv;

jeweils in der aktuellen Ausgabe

Informatik und Gesellschaft
PF

2 SWS

2 ECTS

Number
45201
Language(s)
de
Duration (semester)
1
Contact time
30 h
Self-study
45 h

Learning outcomes/competences

Expert knowledge

Students can describe the subject of computer science and its significance for society
The students understand that technology design and appropriation are social processes and can relate this understanding to their own projects and current social IT topics.
Students are familiar with theories and concepts of the socio-technical perspective and can describe their contribution to the success of IT projects.

Self-competence

Students can address their responsibility as computer scientists
Students begin to reflect on their own role as computer scientists

Social competence

Students are sensitized to the impact of IT on an individual and societal level

Professional field orientation

Students are aware of the importance of social processes for the success of IT projects

Current IT topics and projects: Big data, health apps, UN resolution on privacy on the internet, Network Enforcement Act, General Data Protection Regulation, ethical guidelines, digital disruption ...
Classification of the subject computer science & society
Socio-technical systems: fundamentals, principles and methods of design
Related disciplines: sociology of technology, work and organizational psychology
IT tools for social systems and digital social networks
Organizations in the IT environment

Teaching methods

Lecture in seminar style, with blackboard writing and projection
Project work accompanying the lecture with final presentation
Group work
Individual work
Presentation
active, self-directed learning through internet-based tasks, sample solutions and accompanying materials
the lecture is offered as a video
Inverted classroom teaching
Concluding presentation
Concluding presentation

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

Presentation
Examinations during the semester

Requirements for the awarding of credit points

successful presentation
successful participation in discussion forum

Applicability of the module (in other degree programs)

Bachelor of Computer Science
Bachelor of Medical Informatics
Bachelor of Computer Science Dual

Literature

Bücher, Artikel und Statuten

ACM. 1992. ACM Code of Ethics and Professional Conduct. Available: http://www.acm.org/about-acm/acm-code-of-ethics-and-professional-conduct; CONTENTS [Accessed 2. Mai 2021].
ACM. 2015. Software Engineering Code of Ethics and Professional Practice [Online]. Available: https://ethics.acm.org/code-of-ethics/software-engineering-code/ [Accessed 2. Mai 2021].
GI. 2018. Die Ethischen Leitlinien der Gesellschaft fu r Informatik e.V. Deutschland. Available: https://gi.de/fileadmin/GI/Allgemein/PDF/GI_Ethische_Leitlinien_2018.pdf [Accessed 2. Mai 2021].
BAUMS, A., SCHÖSSLER, M. & SCOTT, B. (eds.) 2015. Kompendium Industrie 4.0: Wie digitale Plattformen die Wirtschaft verändern und wie die Politik gestalten kann, Berlin.
GLASER, T. 2009. Die Rolle der Informatik im gesellschaftlichen Diskurs. Informatik Spektrum, 32, 223-227.
KIENLE, A. & KUNAU, G. 2014. Informatik und Gesellschaft - eine sozio-technische Perspektive, München, Oldenbourg.
LOLL, A. C. 2017. Akteure im Bereich Informatik und Gesellschaft. Informatik Spektrum, 40, 345-350.
MÜLLER, L.-S. & ANDERSEN, N. 2017. Denkimpuls Digitale Ethik: Warum wir uns mit Digitaler Ethik beschäftigen sollten Ein Denkmuster. Available: http://initiatived21.de/app/uploads/2017/08/01-2_denkimpulse_ag-ethik_digitale-ethik-ein-denkmuster_final.pdf [Accessed 2. Mai 2021].
RAHWAN, I., BONNEFON, J.-F. & SHARIFF, A. 2017. The Moral Mashine [Online]. Available: http://moralmachine.mit.edu/hl/de [Accessed 2. Mai 2021].
SOUROUR, B. 2016. The code I m still ashamed of. freeCodeCamp. https://medium.freecodecamp.org/the-code-im-still-ashamed-of-e4c021dff55e [Accessed 2. Mai 2021].

Webseiten

https://gi.de
https://netzpolitik.org
http://humanetech.com
https://irights.info

Studium Generale
PF

2 SWS

2 ECTS

Number
451815
Duration (semester)
1
Contact time
30 h
Self-study
45 h

Adaptive Systeme
WP

4 SWS

5 ECTS

Number
46901
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

In this course, complex and adaptive systems for problem solving are discussed and implemented. Students acquire various skills in the process.

Technical and methodological competence:

After the students have attended the course

are able to develop and analyze problem solutions with adaptive systems
use the most important concepts of adaptive and adaptable information systems to explain systems.

Computational Intelligence

implement adaptive systems on the basis of the models explained.
recognize the limits of adaptive systems.

Interdisciplinary methodological competence:
The student is able to recognize that methods of adaptive systems can be used to describe properties of technical but also business and social systems and to analyze their behavior.

Social skills:
Cooperation and teamwork skills are trained during the practical phases. Students develop practical implementations in teams of size 2 and 3 and are able to present the developed solution together.

Basics and examples of adaptive and complex systems and their application to control systems, networks and the web
Modeling of adaptation processes using various adaptive techniques
Application of soft computing methods (including evolutionary algorithms, particle swarm optimization, ant colony optimization, fuzzy logic, neural networks and modern machine learning methods) for system adaptation to (context) changes
Personalization and modelling of user profiles and context
Application of data classification methods in decision support systems (including rating systems, collaborative and social recommendation systems)
Model-based self-adaptive systems
Time series prediction
Current applications of adaptive systems in the context of computer science and medical informatics

Teaching methods

Lecture in seminar style, with blackboard and projection
Exercise accompanying the lecture
Internship accompanying the lecture
Processing programming tasks on the computer in individual or team work
project work accompanying the lecture with final presentation

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

written examination paper or oral examination (according to current examination schedule)
semester-accompanying coursework (bonus points)

Requirements for the awarding of credit points

passed written examination or passed oral examination (according to current examination schedule)

Applicability of the module (in other degree programs)

Bachelor's degree in Software and Systems Engineering (dual)
Bachelor's degree in Software and Systems Engineering (dual)
Bachelor of Computer Science
Bachelor of Computer Science
Bachelor's degree in Medical Informatics
Bachelor of Medical Informatics Dual
Bachelor of Computer Science Dual
Bachelor of Computer Science

Literature

J. Schmidt, Chr. Klüver, J. Klüver, Programmierung naturanaloger Verfahren, Vieweg+Teubner Verlag (2010)
R. Kruse, C. Borgelt, F. Klawonn, C. Moewes, G. Ruß, M. Steinbrecher, Computational Intelligence, Zweite Auflage, Vieweg+Teubner Verlag (2015)
W.-M. Lippe, Soft-Computing, Springer Verlag (2005)
A. Kordon, Applying Computational Intelligence, Springer Verlag (2010)
I. Witten, E. Frank und M. Hall, Data Mining: Practical Machine Learning Tools and Techniques, 4. Auflage, Morgan Kaufmann (2017), elektronische Version im Intranet verfügbar

Anerkannte Wahlpflichtprüfungsleistung
WP

0 SWS

5 ECTS

Number
46991
Duration (semester)
1

Anerkannte Wahlpflichtprüfungsleistung
WP

0 SWS

5 ECTS

Number
46993
Duration (semester)
1

Anerkannte Wahlpflichtprüfungsleistung
WP

0 SWS

5 ECTS

Number
46994
Duration (semester)
1

Anerkannte Wahlpflichtprüfungsleistung
WP

0 SWS

5 ECTS

Number
46992
Duration (semester)
1

Anerkannte Wahlpflichtprüfungsleistung
WP

0 SWS

5 ECTS

Number
46999
Duration (semester)
1

Angewandte Logiken
WP

4 SWS

5 ECTS

Number
46817
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

Technical and methodological competence:

Completers of the module have mastered advanced formal logic concepts in computer science and are able to transfer concrete classical and non-classical logics, logic concepts and methodologies to various computer science problems, adapt them to the respective needs and finally apply them in practice.
In particular, students will master the basics of formal logic modeling of dynamic processes and their applicability as well as techniques of formal specification and verification of models.

Self-competence:

The participants are able to independently deal with current research papers on formal logic modeling and verification in computer science and to understand the core statements.

Social skills:

The participants are able to present formal-logical topics and questions in a didactic manner in presentations and written papers. In particular, they are able to present complex formal-logical issues at different levels of granularity (from conveying the pure underlying idea to formulating the exact mathematical facts).

The event includes the following topics:

Classical concepts of modal logic (such as possibility and necessity) and their relevance in computer science
Syntax and semantics of classical modal and temporal logics (such as CTL*, CTL and LTL) and their applications
Formal-logical specification and modeling of computer science processes using possible-world semantics
(Automated) verification of modeled processes using model checking methods and their applications in practice
Syntax and semantics of epistemic logics (such as belief sets and epistemic modal logic) and their relevance for computer science
Exemplary application of the topics learned: depending on the interests and professional background, various example applications can be chosen such as Formal Hardware Verification , Modeling Dynamic Processes , Concurrency , etc.
Sensible intensional / propositional logics and their applications in modern computer science applications
Relevance of logics in the applications of artificial intelligence

Teaching methods

Lecture in seminar style, with blackboard and projection
Exercise to accompany the lecture

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

oral examination
presentation

Requirements for the awarding of credit points

passed oral examination
successful presentation

Applicability of the module (in other degree programs)

Bachelor's degree in Business Informatics
Bachelor of Computer Science
Bachelor of Computer Science
Bachelor of Medical Informatics
Bachelor of Computer Science Dual
Bachelor of Medical Informatics Dual

Literature

Hughes und Cresswell A New Introduction To Modal Logic, Routledge Chapman & Hall,
Kropf Introduction to Formal Hardware Verification, Springer-Verlag Berlin and Heidelberg, 1999
Chagrov und Zakharyaschev Modal Logic, Oxford University Press, 1997
Gardenfors - Knowledge in Flux: Modeling the Dynamics of Epistemic States (Studies in Logic), College Publications, 2008
Bab - Epsilon_mu-Logik - Eine Theorie propositionaler Logiken, Shaker Verlag Aachen, 2007

Ausgewählte Aspekte der Informatik
WP

4 SWS

5 ECTS

Number
46904
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

In the course "Selected Aspects of Computer Science", content on a special topic of computer science is presented.
This course offers the opportunity to offer a course that is not offered on an annual basis. Lecturers from Germany and abroad and cooperation partners can be approached to present interesting aspects.
The topics offered specifically expand the range of courses in the field of practical computer science.
Both the content of the course and the forms of teaching and examination may vary from semester to semester.

Subject and methodological skills

Self-competence

Social competence:

- The students know the basics of the topic
- The students know the requirements, principles, architectures, methods, procedures and tools for the topic
- The students can work independently on tasks (case studies, project tasks, development tasks)
- Students develop their results independently or in teams and present them
- Practical work is done in teams.

In this course, 'Selected Aspects of Computer Science' are specifically presented.

This course is offered in coordination with the Dean of Studies, taking capacity aspects into account.

A module description - in accordance with the specifications in the module handbook - is created in advance for the specific course. The head of degree program uses this to check the suitability of the course to complement the curriculum. The module description is made available to the students from the beginning of the course.

Quality assurance is carried out by the head of degree program.

Teaching methods

Seminar-style teaching

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Applicability of the module (in other degree programs)

Bachelor of Computer Science Dual
Bachelor of Medical Informatics
Bachelor of Medical Informatics Dual
Bachelor of Software and Systems Engineering (dual)
Bachelor of Software and Systems Engineering (dual)
Bachelor's degree in Business Informatics

Literature

Die Literaturhinweise erfolgen Themen-spezifisch durch den jeweiligen Lehrenden.

Componentware
WP

4 SWS

5 ECTS

Number
46808
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

Introduction to component-based software development and application of what has been learned in practical examples based on EJB.

Technical and methodological competence:

Knowing and defining the concept of components
Understanding the challenges of distributed systems
Knowing solution approaches with and without middleware
Know typical problems in enterprise applications (transaction protection, security, access control, internationalization, scalability, availability, ...)
Modeling distributed systems with UML
Understanding the difference between specification and its realization
Understanding the EJB specification
Applying EJB knowledge with the glassfish application server
Develop an independent solution as part of a project

Interdisciplinary methodological competence:

Developing a project from any application domain

Social skills:

Systematically work on problems of medium to high complexity in a team
Develop an EJB solution in a cooperative and collaborative team
Document an EJB solution in a cooperative and collaborative team

General basics of component technology (motivation, definitions, goals,...)
Fundamental terms and challenges of enterprise applications (transaction protection, security, access control, internationalization, scalability, availability, ...)
Software architecture principles and concepts for defining software components and platforms
Concept of the application server
Stateless session beans
Stateful session beans
Singleton session beans
Message Driven Beans
Timer Services
Entity Manager and Persistent Entities
Transaction management
Characteristic features of component-based systems

Teaching methods

Lecture in seminar style, with blackboard and projection
Exercise to accompany the lecture
Solving practical exercises in individual or team work
Internship accompanying the lecture
project work accompanying the lecture with final presentation
Exercises or projects based on practical examples

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

Project work with oral examination
Presentation
Semester-accompanying study achievements (bonus points)

Requirements for the awarding of credit points

passed oral examination
successful project work
successful presentation

Applicability of the module (in other degree programs)

Bachelor of Business Informatics
Bachelor of Software and Systems Engineering (dual)
Bachelor's degree in Software and Systems Engineering (dual)
Bachelor of Computer Science
Bachelor of Computer Science
Bachelor's degree in Medical Informatics
Bachelor of Medical Informatics Dual
Bachelor of Computer Science

Literature

Oliver Ihns et. al.: EJB 3.1 professionell. Grundlagen- und Expertenwissen zu Enterprise JavaBeans 3.1 inkl. JPA 2.0, dpunkt.verlag GmbH, Auflage: 2., 2011
Jan Leßner, Werner Eberling: Enterprise JavaBeans 3.1: Das EJB-Praxisbuch für Ein- und Umsteiger, Carl Hanser Verlag GmbH & CO. KG; Auflage: 2, 2011
Clemens Szyperski, Dominik Gruntz and Stephan Murer: Component software. Beyond object-oriented computing, Pearson, 2nd Edition, 2002
CBSE-Proceedings: nth International Symposium on Component-Based Software Engineering

Computergraphik
WP

4 SWS

5 ECTS

Number
46809
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

Technical and methodological competence:

After successfully completing the module, students know the terminology of computer graphics and can use it correctly to describe graphics systems. They will know important mathematical concepts, algorithms and data structures of computer graphics and their use in common computer graphics systems.

You will be able to select suitable solutions for problems in the field of computer graphics and develop your own computer graphics applications using a standard programming interface (e.g. OpenGL).

Lecture

Introduction:
Visual information processing and its applications, hardware and software of graphical systems
2D graphics:
2D basic elements and basic algorithms, curves, transformations and clipping, raster conversion
3D graphics:
3D basic elements, curves and surfaces, body modeling, scene graph and transformations, projection, visibility and occlusion, shader programming, lighting and shading, textures, ray tracing

Internship

Graphics programming with OpenGL

Teaching methods

Lecture in seminar style, with blackboard writing and projection
Solving practical exercises in individual or team work
Processing programming tasks on the computer in individual or team work

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

written exam paper

Requirements for the awarding of credit points

passed written exam

Applicability of the module (in other degree programs)

Bachelor's degree in Software and Systems Engineering (dual)
Bachelor's degree in Software and Systems Engineering (dual)
Bachelor of Computer Science
Bachelor of Computer Science
Bachelor's degree in Medical Informatics
Bachelor of Computer Science Dual
Bachelor of Medical Informatics Dual
Bachelor of Computer Science

Literature

Nischwitz, A., Fischer M., Haberäcker P., Socher G.: Computergrafik : Band I des Standardwerks Computergrafik und Bildverarbeitung; Springer Vieweg; 4. Auflage; 2019
Marschner, S., Shirley, P.: Fundamentals of Computer Graphics, 4th. ed., CRC Press, 2016
Hughes J.F., van Dam A., McGuire M., Sklar D.F., Foley J., Feiner S.K., Akeley K.: Computer Graphics principles and practice, 3rd ed., Addison-Wesley, 2013
Kessenich, J.; Sellers, G.; Shreiner,D.: OpenGL Programming Guide, 9th ed., Addison-Wesley, 2017

Controlling
WP

4 SWS

5 ECTS

Number
46811
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

Students learn the difference between strategic and operational controlling and can assess the importance of strategic corporate planning as the basis for strategic controlling.

Technical and methodological competence:
Students learn about and apply operational controlling tools and techniques for annual profit generation. They will be able to determine sales, profit and capital return on investment. They can calculate the contribution margin and make decisions about price elasticity.
You will learn about and apply methods for strategic controlling to maintain the company. SWOT analysis, success factors and success objects, strategic business area analysis and strategic business units will be understood and categorized.

Interdisciplinary methodological competence:
Students learn about the use of ERP systems in controlling. They will be able to classify controlling in the structure of business software.

Social skills:
Group work strengthens social skills in team building and teaches consideration for others in discussions.

Classification of controlling in the company
The controller as a person
The controlling control loop
Revolving planning and the SWOT analysis
Strategic business units and strategic business areas
Success objectives and success factors
Controlling key figures, ROI, balanced scorecard
Break-even analysis, contribution margin accounting
Price elasticity

Teaching methods

Lecture in interaction with the students, with blackboard writing and projection

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

written exam paper

Requirements for the awarding of credit points

passed written exam

Applicability of the module (in other degree programs)

Bachelor of Business Informatics
Bachelor of Software and Systems Engineering (dual)
Bachelor's degree in Software and Systems Engineering (dual)
Bachelor of Computer Science
Bachelor of Computer Science
Bachelor's degree in Medical Informatics
Bachelor of Medical Informatics Dual
Bachelor of Computer Science

Literature

Ziegenbein, Klaus, Controlling, Kiehl Friedrich Verlag
Däumler, Klaus-Dieter, Grabe, Jürgen, Kostenrechnung 2, Deckungsbeitragsrechnung, nwb-Verlag
Reichmann, Thomas, Controlling mit Kennzahlen, Vahlen Verlag

Data Mining in Industrie u.Wirtschaft
WP

4 SWS

5 ECTS

Number
46843
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

Students master important methods and algorithms of modern data analysis for recognizing patterns and structures in large data sets. In particular, they are familiar with the three phases of pre-processing, analysis and evaluation of the data mining process. They will be able to select and apply suitable data analysis methods for specific applications in industry and Business Studies and use them to support decision-making.

Technical and methodological competence:

Students have a sound knowledge of the data analysis methods covered.

Social skills:

The students can analyze data sets from practice in teamwork using the methods of the course and present the results to the plenum.

Phases of data mining
Data, relations and data preprocessing
Multiple regression
Cluster analysis
Classification methods
Association analysis
Outlier detection

Teaching methods

Lecture in interaction with the students, with blackboard writing and projection
Solving practical exercises in individual or team work
Processing programming tasks on the computer in individual or team work
Exercises or projects based on practical examples

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

Project work with oral examination
Examinations during the semester

Requirements for the awarding of credit points

passed oral examination
successful project work
successful mini-project (project-related work)

Applicability of the module (in other degree programs)

Bachelor of Medical Informatics
Bachelor of Computer Science
Bachelor of Computer Science
Bachelor of Medical Informatics Dual
Bachelor of Computer Science Dual
Bachelor of Business Informatics

Literature

Cleve, J., Lämmel, U. (2020), Data Mining, 3. Auflage, De Gruyter, Berlin/Boston
Runkler, A. (2015) Data Mining: Modelle und Algorithmen intelligenter Datenanalyse, 2. Auflage, Springer VS, Wiesbaden.
Hastie, T., Tibshirani, R., Friedmann, J. (2009), The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2. Auflage, Springer, New York

Datenbanken 2
WP

4 SWS

5 ECTS

Number
46812
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

Technical and methodological skills:

Develop EER models and transfer them to relational, object-relational and object-relational databases.
Apply methods of object-relational mapping.
Explain the 5-level model of a database management system.
Explain concepts of storage and access management.
Use examples to apply the methods of access optimization and transaction management.

Social skills:

Developing, creating, communicating and presenting learning content in teams

Implementation concepts

Memory management
Logical and physical access optimization
Transaction management
Distributed databases
Performance optimization and SQL tuning

Database models

Data modeling (EER model)
Limitations of the relational model
Object-relational database extension
Object-relational mapping frameworks

Teaching methods

seminar-style teaching with flipchart, smartboard or projection
Solving practical exercises in individual or team work
Internship to accompany the lecture
working on programming tasks on the computer in individual or team work
active, self-directed learning through Internet-supported tasks, sample solutions and accompanying materials
exercises or projects based on practical examples
The lecture is offered as a video
Inverted teaching (inverted classroom)

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

written examination paper
examinations during the semester

Requirements for the awarding of credit points

passed written exam

Applicability of the module (in other degree programs)

Bachelor of Business Informatics
Bachelor of Software and Systems Engineering (dual)
Bachelor's degree in Software and Systems Engineering (dual)
Bachelor of Computer Science
Bachelor of Computer Science
Bachelor's degree in Medical Informatics
Bachelor of Medical Informatics Dual
Bachelor of Computer Science Dual

Literature

R. Elmasri, S. Navathe, Grundlagen von Datenbanksystemen, 2009
A. Kemper, A. Eickler, Datenbanksysteme (Eine Einführung), 2015
G. Saake, K.-U. Sattler, A. Heuer, Datenbanken Implementierungstechniken, 2011
R. Niemiec, Oracle database 12c release 2 performance tuning tips & techniques, 2017
R. Panther, SQL-Anfragen optimieren, 2014

Digitale Bildverarbeitung
WP

4 SWS

5 ECTS

Number
46814
Language(s)
de
Duration (semester)
1
Contact time
45 h
Self-study
105 h

Learning outcomes/competences

The course deals with the development and analysis of systems that use digital image processing methods.

Technical and methodological competence:

After attending the course, students will be able to

list and explain the stages of digital image processing
recall and apply important mathematical and algorithmic concepts of digital image processing
solve image processing problems by combining the methods covered
develop simple image processing applications using the Matlab® programming system or the Java and ImageJ programming languages
know examples for the industrial application of digital image processing

Introduction to the Matlab® programming language and environment
Overview of image processing hardware and software
Image acquisition and discretization
Procedures for image restoration, image enhancement and geometric manipulation of images
Morphological image processing and the processing of color images
Discrete Fourier transform (1D and 2D) and applications
Methods for image segmentation, feature extraction and image analysis
Pattern recognition and image classification
Modern image features - interest points (SIFT)
Deep learning methods for image classification

Teaching methods

Solving practical exercises in individual or team work
Processing programming tasks on the computer in individual or team work

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

written examination paper or oral examination (according to the current examination schedule)

Requirements for the awarding of credit points

passed written examination or passed oral examination (according to current examination schedule)

Applicability of the module (in other degree programs)

Bachelor's degree in Software and Systems Engineering (dual)
Bachelor's degree in Software and Systems Engineering (dual)
Bachelor of Computer Science
Bachelor of Computer Science
Bachelor of Computer Science Dual
Bachelor of Computer Science

Literature

H. Bässmann, J. Kreyss: Bildverarbeitung AdOculos, Springer-Verlag, 2004
W. Burger, M. J. Burge: Digital Image Processing, Dritte Auflage, Springer-Verlag, 2015, elektronische Version im Intranet verfügbar
A. Nischwitz, M. Fischer, P. Haberäcker: Computergrafik und Bildverarbeitung, Vieweg+Teubner Verlag, 2007
R. C. Gonzalez, S. L. Eddins, R. E. Woods, Digital Image Processing, Vierte Auflage, Pearson, 2018
R. C. Gonzalez, S. L. Eddins, R. E. Woods, Digital Image Processing Using MATLAB, Prentice Hall, 2004

ERP 1 (Standardsoftware)
WP

4 SWS

5 ECTS

Number
46828
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

Providing basic knowledge about the importance and development of standard software and raising awareness of the associated problem areas. Theoretical knowledge about types of adaptations to standard software and their practical implementation on a specific ERP system. Consolidation and practical application of previously acquired specialist knowledge using practical examples.

Technical and methodological competence:

Distinguishing between standard and customized software
Naming the advantages and disadvantages of standard software.
Differentiate between the various customization options of standard software and evaluate the respective consequences.

Designing and implementing functional enhancements to standard software.

Social skills:

Evaluate the importance of communication, conflict and team skills in implementation and customization projects.

Professional field orientation:

Knowledge of the requirements of different job profiles in the ERP environment (esp. sales, consulting, project management, application development)

General principles (definition of terms, historical development, )
Standardization concept (classification and differentiation from in-house development, degree of coverage, )
Integration aspects (technical and organizational integration, examples and consequences, )
Business management components (financial accounting, HR, logistics, production, )
Selection process (market overview and breakdown, selection criteria, decision-making process, )
Implementation of an ERP system (project approach, implementation strategies, procedures)
Technical basics (system structure, hardware platforms and supported databases, )
Installation, maintenance and operation of an ERP solution
Customizations to standard software (types of customizations, their delimitation and consequences, )
Integrated development environments and programming languages
Inhouse developments (functional expansion of an ERP system in practical exercises based on a mini-project)

Teaching methods

Lecture in interaction with the students, with blackboard writing and projection
Solving practical exercises in individual or team work
Processing programming tasks on the computer in individual or team work

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

written written examination
study achievements during the semester (bonus points)

Requirements for the awarding of credit points

passed written exam

Applicability of the module (in other degree programs)

Bachelor's degree in Software and Systems Engineering (dual)
Bachelor's degree in Software and Systems Engineering (dual)
Bachelor of Computer Science
Bachelor's degree in Medical Informatics
Bachelor of Medical Informatics Dual
Bachelor of Computer Science
Bachelor of Computer Science Dual
Bachelor of Computer Science

Literature

Skript zur Vorlesung (Hesseler, M.)
Hesseler, M.; Görtz, M.; Basiswissen ERP-Systeme ; w3l-Verlag; Bochum; 2007;

Ergänzende Literaturempfehlungen (nicht zwingend erforderlich):
- Allweyer, T.; Geschäftsprozessmanagement ; w3l-Verlag; Bochum; 2005;
- Hesseler, M. und Rösel, C.; ERP-Übungsbuch: Entwicklung einer einfachen Fuhrpakrverwaltung in Microsoft Dynamics NAV ; Books on Demand; Norderstedt; 2010;
- Hesseler, M. und Görtz, M.; ERP-Systeme im Einsatz ; w3l-Verlag; Herdecke; 2009;
- Luszczak, A.; "Microsoft Dynamics NAV 2009 - Grundlagen", Microsoft Press Deutschland; Auflage: 1, Unterschleißheim, 2009

Effiziente Algorithmen und Datenstrukturen
WP

4 SWS

5 ECTS

Number
46889
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

Technical and methodological competence:

Be able to describe basic algorithmic methods
Be able to assess problems in terms of their modeling possibilities and algorithmic complexity.
Be able to describe and implement efficient algorithms and data structures for selected basic problems.

Basics
- O-notation
- Graphs
Graph algorithms
- Shortest paths
- Minimal spanning trees
- Flows in networks
- Matchings
- Tours
Algorithmic techniques
- Divide and Conquer
- Dynamic programming
- Greedy algorithms
Optimization problems
- Backtracking
- Branch-and-bound
- Approximation algorithms

Teaching methods

Lecture in interaction with the students, with blackboard writing and projection
Exercise accompanying the lecture
Solving practical exercises in individual or team work
Group work
Individual work
Presentation

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

written exam paper

Requirements for the awarding of credit points

passed written exam

Applicability of the module (in other degree programs)

Bachelor's degree in Software and Systems Engineering (dual)
Bachelor's degree in Software and Systems Engineering (dual)
Bachelor of Computer Science
Bachelor of Computer Science
Bachelor's degree in Medical Informatics
Bachelor of Medical Informatics Dual
Bachelor of Computer Science Dual
Bachelor of Computer Science

Literature

T. Cormen, C. Leiserson, R. Rivest, C. Stein: "Algorithmen - Eine Einführung", Oldenbourg, 4. Auflage, 2013
T. Ottmann, P. Widmayer: "Algorithmen und "Datenstrukturen", Spektrum Akademischer Verlag, 6. Auflage, 2017
G. Pomberger, H. Dobler: "Algorithmen und Datenstrukturen", Pearson Studium, 2008
R. Sedgewick, K. Wayne: "Algorithmen", Pearson Studium, 2014
R. Wanka: "Approximationsalgorithmen - Eine Einführung", Teubner, 2006
B. Vöcking, H. Alt, M. Dietzfelbinger, R. Reischuk, C. Scheideler, H. Vollmer, D. Wagner: "Taschenbuch der Algorithmen", Springer, 2008

Entwicklung verteilter Anwendungen
WP

4 SWS

5 ECTS

Number
46890
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

Transfer of knowledge for the development of distributed applications

Technical and methodological competence:

Understanding the special requirements and challenges of developing distributed systems
Learning about the principles, architectures and mechanisms of distributed systems
Knowing the approaches to developing distributed systems
Converting current concepts into Java programs

Social skills:

Working in small teams
Results-oriented group work

Scenarios of distributed systems
Basics of distributed systems
Distributed data management
Communication in distributed systems
(request/reply, peer-to-peer, push)
Challenges of distributed systems
(heterogeneity, interoperability, configuration,...)
Quality of distributed systems
(transparency, security, reliability,...)
Architectures

Teaching methods

Lecture in interaction with the students, with blackboard writing and projection
Processing programming tasks on the computer in individual or team work

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

written written examination
study achievements during the semester (bonus points)

Requirements for the awarding of credit points

passed written exam

Applicability of the module (in other degree programs)

Bachelor's degree in Software and Systems Engineering (dual)
Bachelor's degree in Software and Systems Engineering (dual)
Bachelor of Computer Science
Bachelor of Computer Science
Bachelor's degree in Medical Informatics
Bachelor of Computer Science Dual
Bachelor of Medical Informatics Dual
Bachelor of Computer Science

Literature

Literaturhinweise

Bengel, Günther: Grundkurs Verteilte Systeme, 4. Auflage Springer Vieweg, 2014
Dustar, Schahram et. al.: Softwarearchitekturen für verteilte Systeme, Springer, 2003
Hohpe, Gregor, Woolf, Bobby: Enterprise Integration Patterns, Addison Wesley, 2004
Kopp, Markus, Wilhelms, Gerhard: Java Solutions

Hardware Engineering
WP

4 SWS

5 ECTS

Number
46878
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

Teaching the basics of hardware-related implementations within technical computer science. Theoretical knowledge, its application and transfer to structure-based (HW) and behavior-based (SW) solutions.

Technical competence:

The students should be able to explain Mealy- & Moore automata, building blocks of digital technology, VHDL language elements and basic HW technologies.
They will be able to explain procedures for the transition from logic to switching algebra, differentiate the relationship between design parameters (performance, area, power consumption, costs) and differentiate between switching algebra procedures.
The students can minimize switching functions, design switching systems, create simple VHDL programs, configure an FPGA device (Xilinx Spartan 3) and implement a VGA driver.

Social skills:

Work in the practical part (internship in the 2nd half of the semester) in the field of simulation of VHDL programs and FPGA programming in small groups strengthens communication skills and binding coordination between students

Formal basics
- Terms, classes, forms of representation (tabular, graphical, algebraic)
- Normal forms (KNF, DNF)
- Minimization (Quine/McCluskey, KV, Nelson, Petrick)
- Switching networks
- Sequential logic
- Switching mechanisms & automata
Components of digital technology, etc.
- Gates
- Flip-flops
- Multiplexers
- Registers
- Adder
- Counter
Syntax & semantics of the hardware description language VHDL
Simulation of hardware descriptions
Design of digital circuits, design of state machines
Hardware design in FPGA technology

Teaching methods

Lecture in interaction with the students, with blackboard writing and projection
Solving practical exercises in individual or team work
Processing programming tasks on the computer in individual or team work

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

written exam paper

Requirements for the awarding of credit points

passed written exam

Applicability of the module (in other degree programs)

Bachelor of Computer Science
Bachelor of Computer Science
Bachelor of Computer Science

Literature

Sikora, A, Drechsler, R. Software-Engineering und Hardware-Design, Eine
systematische Einführung, Hanser, 2002
Becker, B, Drechsler, R., Molitor, P. Technische Informatik, Eine Einführung,
Pearson Studium, 2005.
Reichardt, J., Schwarz, B., VHDL-Synthese, Entwurf digitaler Schaltungen und
Systeme, 3. Auflage, Oldenbourg, 2003.
Molitor, P, Ritter, J., VHDL, Eine Einführung, Pearson Studium, 2004.

IT-Servicemanagement
WP

4 SWS

5 ECTS

Number
46905
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

Transfer of basic knowledge regarding the importance and use of IT service management in the company. Theoretical knowledge of the five phases and their processes, roles and functions of the IT Infrastructure Library (ITIL) lifecycle model. Consolidation and practical application of previously acquired specialist knowledge using practical examples.

Technical and methodological competence:

Distinguishing between IT management and IT service management
Naming the reasons for and objectives of using ITIL
Differentiating the different phases of the ITIL lifecycle
Use case studies to deepen the knowledge gained and develop your own solutions in the ITIL environment
Design and implement your own ITIL implementation scenarios in exemplary case studies
Develop detailed processes based on the ITIL phases for specific practical tasks

Interdisciplinary methodological competence:

Selecting suitable communication structures for service and support processes/structures
Systematic prioritization of activities and projects
Knowing error cultures (human factor in stressful situations)
Evaluating classic conflicts between design and operational functions
Classification of DevOps and agile development in ITIL phases
Systematic use of IT KPIs to measure the achievement of objectives

Professional field orientation:

Knowledge of the requirements of different job profiles in the IT service management environment (service owner, service manager, process owner, process manager, etc.)
Applying IT processes in the context of IT service management
Knowing roles and responsibilities within IT service management
Selecting and using suitable models, concepts and tools

IT Management and Business Service Management (BSM) Basics
Business Process Modeling Notation Basics
IT service management (ITSM) basics
Concepts and methods of IT service management
ITIL basics and history
ITIL (IT Infrastructure Library) V3 2011
Service strategy (Service Strategy)
Service design (Service Design)
Service Transition (Service Transition)
Service Operation (Service Operation)
Continuous Service Improvement

Teaching methods

Lecture in seminar style, with blackboard writing and projection
Solving practical exercises in individual or team work
Case studies
Role-playing games
Exercises or projects based on practical examples

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

written exam paper

Requirements for the awarding of credit points

passed written exam

Applicability of the module (in other degree programs)

Bachelor of Business Informatics
Bachelor of Software and Systems Engineering (dual)
WXYZ
Bachelor of Computer Science
Bachelor of Computer Science
Bachelor's degree in Medical Informatics
Bachelor of Medical Informatics Dual
Bachelor of Computer Science

Literature

Axelos, ITIL® Service Continual Service Improvement; Edition2011; London TSO; 2013
Axelos, ITIL® Service Design, Edition 2011; London TSO; 2013
Axelos, ITIL® Service Operation; Edition 2011; London TSO; 2013
Axelos, ITIL® Service Strategy; Edition 2011; London TSO; 2013
Axelos, ITIL® Service Transition; Edition 2011; London TSO; 2013
Beims, M.; IT-Service Management mit ITIL®, ITIL® Edition 2011, ISO 20000:2011 und PRINCE2® in der Praxis; 3. Auflage; Dr. Carl Hanser Verlag; 2012
Buchsein, R., Victor, F. Günther, H., Machmeier, V.; IT-Management mit ITIL® V3: Strategien, Kennzahlen, Umsetzung; 2. Auflage; Vieweg; Wiesbaden; 2008
Olbrich, Al.; ITIL kompakt und verständlich; 4. Auflage; Vieweg; Wiesbaden; 2006
Victor, F., Günther, H.; Optimiertes IT-Management mit ITIL; 2. Auflage; Vieweg; Wiesbaden; 2005
Zarnekow, R., Fröschle, H.-P.; Wertorientiertes IT-Servicemanagement: HMD - Praxis der Wirtschaftsinformatik (Heft 264); dpunkt Verlag; Heidelberg; 2008.

Informations- und Business Performance Management
WP

4 SWS

5 ECTS

Number
46909
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

The course is based on business management methods and derives requirements for IT support from them. Based on the consideration of the conceptual level of analytical applications, the technical implementation of the concepts and their comparison with each other is carried out.

Technical and methodological competence (also interdisciplinary):

Knowing and classifying the terms strategic alignment, document management, balanced scorecard, key figure systems and predictive modeling
Recognize the core concepts of the information supply chain, multidimensional modelling, MOLAP, ROLAP, in-memory, data warehouse and data mining concepts
Basics of big data processing
Understanding and applying advanced business management methods such as planning and budgeting
Knowing and classifying life cycle models, reference models and modeling languages
Name and differentiate between information architectures

Professional field orientation:

Application and concrete use of the methods taught in a semester-accompanying project
Construction of reports and analysis models from raw data, the use of various life cycle models (Kimball, Inmon, CRISP) based on the implementation of a small business intelligence project in a team.

Social skills:

Group work strengthens personal social coordination and communication during the event
The project organization and management guided by the life phase models provides students with interdisciplinary methodological skills.

Overview and introduction
Chapter I
- Information and decision theory
- Information supply chain
- Business signals
- Operational and analytical applications
- Balanced scorecard
Chapter II
- Accounting, controlling, strategic planning
- Extraction, transformation, loading (ETL)
- Concept of the data warehouse
- Multidimensional modeling
Chapter III
- Predictive analytics, data mining methods and applications
Chapter IV
- Big data and document management
Chapter V
- Multidimensional business applications
- OLAP analysis
- Business planning
- Group consolidation
Chapter VI
- Case studies of analytical applications
Chapter VII
- Strategic Business and IT Alignment
- Lifecycle models for information management projects

Semester-accompanying group project:
Development of a reporting system for standard and OLAP reports based on tourism market research data using Microsoft SQL Business Intelligence Studio with the following sub-steps:

Understanding the question
Understanding the data
Processing the data
Modeling
Validation
Application

Teaching methods

Lecture in interaction with the students, with blackboard writing and projection
Exercise accompanying the lecture
Solving practical exercises in individual or team work
Internship accompanying the lecture
Group work
Concluding presentation

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

written examination paper 75%
semester-accompanying coursework 25%

Requirements for the awarding of credit points

passed written examination
successful presentation

Applicability of the module (in other degree programs)

Bachelor of Business Informatics
Bachelor of Software and Systems Engineering (dual)
Bachelor's degree in Software and Systems Engineering (dual)
Bachelor of Computer Science
Bachelor of Computer Science
Bachelor's degree in Medical Informatics
Bachelor of Medical Informatics Dual
Bachelor of Computer Science Dual

Literature

Bashiri, I., Engels, C., Heinzelmann, M., Strategic Alignment, Springer, 2010.
Cameron, S., SQL Server 2008 Analysis Services Step by Step, Microsoft Press, 2009, ISBN-10: 0-7356-2620-0.
CRISP-DM, 1.0 step-by-step data mining guide, CRISP-DM consortium, 1999, (abgerufen am 25.11.2010) http://www.crisp-dm.org/download.htm.
Engels, C., Basiswissen Business Intelligence, W3L Verlag, Witten 2009.
Heinrich, Lutz J.: Informationsmanagement. Seit 1985 im Oldenbourg Wissenschaftsverlag, München / Wien, 8. Aufl. 2005, 9. Aufl. 2009 (1. bis 3. und ab 8. Aufl. mit Ko-Autor), ISBN 3-486-57772-7.
Jiawei Han, M.Kamber, Data Mining: Concepts and Techniques, http://www.cs.sfu.ca/~han/bk/.
Robert S. Kaplan, David P. Norton: Balanced Scorecard. Strategien erfolgreich umsetzen. Stuttgart 1997, ISBN 3-7910-1203-7.
Kemper et.al., Business Intelligence, Vieweg, 3. Auflage, 2010, ISBN 978-3-8348-0719-9.
Kimball, R. et. al., The Kimball Group Reader, Wiley, 2010.
Kimball, R., Caserta J., The Data Warehouse ETL Toolkit, Wiley, 2004.
Krcmar, H.: Informationsmanagement. 6. Auflage, Springer, Berlin et al., 2015, ISBN 978-3-662-45862-4
Misner, S., SQL Server 2008 Reporting Services Step by Step, Microsoft Press, 2009, ISBN-10: 0-7356-2647-2.
Mitchell, T., Machine Learning, McGraw Hill, 1997.
Scheuch, R., Gansor, T., Ziller, C: Master Data Management: Strategie, Organisation, Architektur, dpunkt.verlag, 2012.
Plattner, H., Zeier, A.: In-Memory Data Management: An Inflection Point for Enterprise Applications, Springer, Berlin, 2011.

Informationssicherheit
WP

4 SWS

5 ECTS

Number
46813
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

The students are able to

define, differentiate and explain basic information security terminology
understand the central importance of standardization in information security and map it methodically.

Terminology
- IT security, information security, difference between security and safety
- Asset
- Protection target (CIA and authentication)
- Vulnerability, vulnerability, threat, attack, attacker types
- Risk
- Security measure
Security guidelines, human factor, security awareness
Legal framework, European General Data Protection Regulation
Standards and best practices
- ISO/IEC 27000 series
- Common Criteria
- IT baseline protection
- OWASP
Applied cryptography
- Symmetric encryption (basics, AES, block modes, padding, pitfalls)
- Hash functions (types of attack, SHA-2 family, SHA-3 family), MAC
- Asymmetric cryptography (basics, DH, RSA, ECC, padding, pitfalls, digital shelf marks, certificates)
Access control
- Basics (DAC, MAC, RBAC, Deny by Default, Least Privilege)
- Advanced models (ABAC, ReBAC), modeling
Authentication
- Basics of authentication (types, MFA, entropy)
- Password-based authentication (Linux password databases, types of attacks, Salt, Argon2, NIST 800-63B)
Basics of software development and information security
- Best practices (OWASP Top 10, SAMM, ASVS, Testing Guide)

Teaching methods

Lecture in interaction with the students, with blackboard writing and projection
Solving practical exercises in individual or team work

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

written exam paper

Requirements for the awarding of credit points

passed written exam

Applicability of the module (in other degree programs)

Bachelor of Business Informatics
Bachelor of Software and Systems Engineering (dual)
Bachelor of Computer Science
Bachelor of Computer Science
Bachelor's degree in Medical Informatics
Bachelor of Medical Informatics Dual
Bachelor of Computer Science Dual
Bachelor of Computer Science Dual

Literature

R. Anderson: Security Engineering: A Guide to Building Dependable Distributed Systems, 3. Auflage, John Wiley & Sons Inc., 2020
C. Eckert: IT Sicherheit (Konzepte, Verfahren, Protokolle), 11. Auflage, De Gruyter Oldenbourg, 2023
ISO/IEC 27000: Information technology Security techniques Information security management systems Overview and vocabulary, 2018
K. Schmeh: Kryptografie Verfahren - Protokolle - Infrastrukturen, 6. Auflage, dpunkt.verlag, 2016

Kooperative Systeme
WP

4 SWS

5 ECTS

Number
46912
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

Technical and methodological competence:

Students know the basics of social groups and how they are supported by technical systems
The students are able to select, adapt and introduce a specific system for group work in a company
The importance and impact of IT support for group work in companies is known

Interdisciplinary methodological competence:

The concepts of group work learned can be used across disciplines
Students can assess the importance of cooperative systems for the IT landscape of a company

Social competence:

The seminar accompanying performance is carried out as group work and thus promotes social competence
This is supported by the application of the concepts learned in this course on the topic of groups

Theoretical foundations: social groups, communication, cooperation, coordination, knowledge management
Technical implementation of cooperative systems: classifications and components
Current examples from CSCW, CSCL, knowledge management, Web 2.0, social networks
Cooperative systems for companies: Importance, selection, customization, implementation, impact

Teaching methods

Seminar-style teaching with flipchart, smartboard or projection

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

Homework
Presentation
Semester-accompanying coursework (bonus points)

Requirements for the awarding of credit points

successful term paper
successful presentation

Applicability of the module (in other degree programs)

Bachelor of Business Informatics
Bachelor of Software and Systems Engineering (dual)
Bachelor's degree in Software and Systems Engineering (dual)
Bachelor of Computer Science
Bachelor of Computer Science
Bachelor's degree in Medical Informatics
Bachelor of Medical Informatics Dual
Bachelor of Computer Science

Literature

Back, A.; Gronau, N.; Tochtermann, K. (2012): Web 2.0 und Social Media in der Unternehmenspraxis: Grundlagen, Anwendungen und Methoden mit zahlreichen Fallstudien.München: Oldenbourg, 3. Auflage.
Gross, T.; Koch, M. (2007): Computer Supported Cooperative Work. München: Oldenbourg.
Haake, J. M.; Schwabe, G.; Wessner, M. (Hrsg.) (2012): CSCL-Kompendium. München: Oldenbourg Verlag, 2. Auflage.
Koch, M.; Richter, A. (2008): Enterprise 2.0: Planung, Einführung und erfolgreicher Einsatz von Social Software in Unternehmen. München: Oldenbourg.
Schwabe, G.; Streitz, N.; Unland, R. (2001): CSCW-Kompendium: Lehr- und Handbuch Zum Computerunterstützten Kooperativen Arbeiten.Heidelberg: Springer.

Künstliche Intelligenz
WP

4 SWS

5 ECTS

Number
46834
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

Fundamental knowledge of concepts and methods of artificial intelligence (AI) and of applications of knowledge-based methods in "intelligent systems". Basic understanding of the possible applications of these methods. Sensitivity for practice-relevant questions.

Technical and methodological competence:

Capturing and presenting typical AI software architectures
Understanding and explaining the paradigms of symbolic and sub-symbolic approaches to AI.
In-depth explanation and demonstration of heuristic methods of symbolic AI: search, constraints, rule processing. Basic understanding of uncertainty and fuzziness in the context of knowledge-based applications.
Develop the ability to apply these methods in the context of simple problems.
Understanding and applicability of basic formal logic modeling techniques in the field of AI.

Social skills:

Development of verbal skills and communication skills in a team by working out solutions in small groups

Basic concepts of artificial intelligence and formal knowledge processing
Intelligent agents
State spaces and heuristic search, alpha-beta search, constraint propagation
Production control systems
Uncertain knowledge (probabilism), vague knowledge (fuzzy methods)
Simple neural networks
Formal logic modeling in the field of artificial intelligence (e.g. predicate logic)

Teaching methods

Lecture in interaction with the students, with blackboard writing and projection
Exercise accompanying the lecture
immediate feedback and success monitoring

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

written written examination
study achievements during the semester (bonus points)

Requirements for the awarding of credit points

passed written exam

Applicability of the module (in other degree programs)

Bachelor's degree in Software and Systems Engineering (dual)
Bachelor of Computer Science Dual
Bachelor of Computer Science
Bachelor of Computer Science
Bachelor's degree in Medical Informatics
Bachelor of Medical Informatics Dual
Bachelor of Business Informatics
Bachelor of Computer Science Dual

Literature

Ingo Boersch, Jochen Heinsohn, Rolf Socher; Wissensverarbeitung. Eine Einführung in die Künstliche Intelligenz für Informatiker und Ingenieure ; 2. Auflage; Spektrum Akademischer Verlag; München; 2007.
Stuart Russel, Peter Norvig: Künstliche Intelligenz. Ein moderner Ansatz ; 3. aktualisierte Auflage; Pearson; München; 2012.

Mobile App Engineering
WP

4 SWS

5 ECTS

Number
46847
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

Technical and methodological competence:

Know, understand and assess the technical software challenges involved in developing mobile apps
Know and be able to apply processes, activities, methods, techniques, languages and tools for mobile app-specific requirements engineering
Know and be able to apply processes, activities, methods, techniques, languages and tools for designing mobile apps
Know and be able to apply processes, activities, methods, techniques, languages and tools for designing the interaction options and screen pages of a mobile app
Know and be able to apply processes, activities, methods, techniques, languages and tools for implementing mobile apps
Know and be able to apply processes, activities, methods, techniques, languages and tools for testing mobile apps
Know and be able to apply processes, activities, methods, techniques, languages and tools for going live with mobile apps
Know and be able to apply processes and activities, roles and responsibilities in the field of mobile app engineering

Self-competence:

Development and creation of mobile app-specific development and results documents
Independent development of a mobile app across all development phases: from requirements to go-live
Presentation of the developed and achieved results

Social skills:

Teamwork in groups of four in the internship over an entire semester

Professional field orientation:

Practical implementation of mobile app-specific processes and activities
Practical application of mobile app-specific methods, techniques, languages and tools

The aim and content of the course is to teach suitable methods, concepts, techniques, languages and tools to professionally conceptualize, design, develop, test and commission mobile business apps from a software engineering perspective. The entire life cycle of a mobile app is considered, including:

User-oriented collection and specification of the functional and non-functional requirements for a mobile app
GUI prototyping with low- and high-fidelity prototypes
UX/UI design,
Specification of the interaction design and the individual screen pages,
Implementation of mobile apps,
Testing of mobile apps
Processes and activities for the go-live of a mobile app

The phases and activities to be carried out are described and illustrated in a practical way using suitable methods, techniques, languages and tools based on a large industrial mobile app development project.

In the practical part of the course, selected requirements, conception, design, development and testing activities are carried out in teamwork in order to develop a mobile app independently.

Teaching methods

Lecture in interaction with the students, with blackboard writing and projection
Exercise accompanying the lecture
Solving practical exercises in individual or team work
Internship accompanying the lecture
Processing programming tasks on the computer in individual or team work
Concluding presentation

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

written written examination
study achievements during the semester (bonus points)

Requirements for the awarding of credit points

passed written exam

Applicability of the module (in other degree programs)

Bachelor's degree in Business Informatics
Bachelor of Computer Science
Bachelor of Computer Science
Bachelor of Medical Informatics
Bachelor of Computer Science Dual
Bachelor of Medical Informatics Dual
Bachelor of Computer Science

Literature

Vollmer, G. (2017): Mobile App Engineering, Heidelberg: dpunkt-Verlag.

Modellbasierte Softwareentwicklung
WP

4 SWS

5 ECTS

Number
46897
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

Technical and methodological competence:

After completing the course, students will be able to

Create models of software systems and technical systems
create software automatically with the help of models.
Construct transformations and simple code generators
Select suitable technologies for modeling and generation

Basics: model concept, model building, perspectives and levels of abstraction
Modeling in software engineering and technical systems
Metamodeling, four-level meta-modeling architecture, linguistic vs. ontological metamodels
Domain-specific languages
- textual
- graphical
Architecture, target platform, transformation and code generation
Model-driven software development
- with Eclipse Modeling Framework/Ecore
- with Xtext, Xpand and Xtend, more recent developments
- with UML and related technologies: UML, Object Constraint Language (OCL), Query View Transformation Language (QVT)
- with MPS (JetBrains)
Reference to related topics: e.g. product lines, quality assurance/testing
Case studies from the areas of desktop, mobile and embedded systems (e.g. mbeddr)

Teaching methods

Lecture in seminar style, with blackboard writing and projection

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

Project work with oral examination

Requirements for the awarding of credit points

Successful project work

Applicability of the module (in other degree programs)

Bachelor's degree in Software and Systems Engineering (dual)
Bachelor's degree in Software and Systems Engineering (dual)
Bachelor of Computer Science
Bachelor of Computer Science
Bachelor's degree in Medical Informatics
Bachelor of Computer Science Dual

Literature

Völter: "DSL Engineering", dslbook.org, 2013
Völter: "Generic Tools, Specific Languages", 2014
Steinberg: EMF: Eclipse Modeling Framework (2nd Edition), Addison-Wesley, 2008
Gronback: Eclipse Modeling Project A Domain-specific Language (DSL) Toolkit , Addison-Wesley, 2009
Stahl, Völter, Efftinge, Haase: Modellgetriebene Softwareentwicklung , dpunkt.verlag, 2. Auflage, 2007
Gruhn, Pieper, Röttgers: MDA , Springer, 2006
Markus Völter, DSL Engineering: Designing, Implementing and Using Domain-Specific Languages, dslbook.org, 2013

Moderne Datenbanken
WP

4 SWS

5 ECTS

Number
46892
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

Expert knowledge:

Know and use NoSQL database models and demonstrate possible applications
Know and explain materialized and virtual information integration.
Know and explain distributed database architectures for big data applications.
Evaluate big data applications taking into account ethical, social and Business Studies aspects.

Social competence:

Developing, communicating and presenting non-relational database applications in small groups
Collaboratively creating and comparing non-relational database applications with relational solutions

Professional field orientation:

Know the requirements of different job profiles in the database environment (database administrator. Database developer, application developer, data protection officer)

Distributed databases and big data applications
Architectures for data streaming applications
NoSQL database models
Selected algorithms (e.g. map-reduce algorithm)
Current applications

Teaching methods

Seminar-style teaching with flipchart, smartboard or projection
Processing programming tasks on the computer in individual or team work
Project work accompanying the lecture with a final presentation
Group work
active, self-directed learning through internet-supported tasks, sample solutions and accompanying materials
homework to accompany the course
the lecture is offered as a video
Inverted teaching (inverted classroom)
Concluding presentation

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

written exam paper
presentation
examinations during the semester

Requirements for the awarding of credit points

passed written examination
successful presentation
successful mini-project (project-related work)

Applicability of the module (in other degree programs)

Bachelor's degree in Software and Systems Engineering (dual)
Bachelor's degree in Software and Systems Engineering (dual)
Bachelor of Computer Science
Bachelor of Computer Science
Bachelor's degree in Medical Informatics
Bachelor of Medical Informatics Dual
Bachelor of Computer Science Dual
Bachelor of Computer Science

Literature

S. Edlich, A. Friedland, J. Hampe, B. Brauer, NoSQL Einstieg in die Welt nichtrelationaler Web 2.0 Datenbanken, Hanser Verlag 2010
M. Kleppmann, Designing data-intensive applications, O'Reilly Media (2017)
A. Bifet, Machine learning for data stream, MIT-Press (2017)
B. Ellis, Real-time analytics, Wiley & Sons (2014)
Aktuelle Fachliteratur

Multimedia
WP

4 SWS

5 ECTS

Number
43082
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

The students should be able to work on the creation of IT-supported media products. This includes both classic media-based multimedia products, such as DVDs, as well as web-based offerings. For this purpose, the necessary basics for an understanding of today's common media technologies are taught. This ranges from developing your own filters for image processing to raising awareness of the special legal framework conditions when using media in software products.

Technical and methodological skills:

SW-technical implementation of basic image processing algorithms
Naming important media file formats and their properties
Creating the Huffman coding for a given message source
Calculating the entropy of a message source
Conversion between color models
SW-technical implementation of basic graphic algorithms, such as floodfill

Social skills:

Working on the exercises in small groups of 2-4 students
Programming in pairs

Professional field orientation:

Providing basic knowledge for IT media projects

1. basics

History
Information technology
Information theory
Compression & coding

2. graphics & font

Perception
Color models
Graphic formats
Typography
Font formats & character sets

3. audio

Basics
Language
Data formats

4. video & animation

Basics
Analog & digital technology
Real-time graphics

5. interdisciplinarity

Media engineering
Development processes
Ethics of digital media
Law in media informatics

6. further content

In consultation with the students, one to three of the following topics will be covered. The list will be expanded as required

Virtual & augmented reality

Mobile & wearable computing

Video editing

Audio editing

Streaming

Teaching methods

Lecture in interaction with the students, with blackboard writing and projection
Solving practical exercises in individual or team work

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

written written examination
Project work with oral examination
study achievements during the semester (bonus points)

Requirements for the awarding of credit points

passed written examination
passed oral examination
successful project work

Applicability of the module (in other degree programs)

Bachelor's degree in Software and Systems Engineering (dual)
Bachelor's degree in Software and Systems Engineering (dual)
Bachelor of Computer Science
Bachelor of Computer Science
Bachelor of Computer Science

Literature

Literaturhinweise werden in der Veranstaltung bekanntgegeben.

Die im jeweiligen Semester eingesetzte Prüfungsform (z.B. mündliche Prüfung) wird zu Beginn der Veranstaltung bekanntgegeben. Dies gilt ebenfalls für eine möglicherweise genutzte Bonuspunkteregelung.

Numerische Algorithmen
WP

4 SWS

5 ECTS

Number
46840
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

Teaching the fundamentals, techniques and algorithms of numerical and applied mathematics, insofar as they are relevant to the successful study of computer science. Students should be familiar with the specified course content and be able to make informed decisions about which technique to use to solve which problem. Furthermore, they should be introduced to the efficient implementation of the algorithms presented with the help of Matlab and be able to develop these further independently.

Technical and methodological skills:

Calculation of numerical representations
Analysis of numerical errors
Numerical calculation of fixed points, zeros and roots
Numerical calculation of derivatives and integrals
Numerical solution of linear systems of equations
Numerical solution of eigenvalue and eigenvector problems
Calculation of approximating and interpolating polynomials and splines
Calculation of approximating and interpolating surfaces

Number representations and error analysis
LR decomposition
QR decomposition (Givens and Householder)
Cholesky decomposition
Banach's fixed point theorem
Newton method
Heron method
Secantal method
Descent method
Divided-difference method
Trapezoidal and Simpson's rule
Norms and sequences in multidimensions
Total step, single step and SOR methods
Von Mises-Geiringer method
Polynomial interpolation and approximation
Spline interpolation and approximation
Trigonometric interpolation and DFT
Bilinear interpolation
Multidimensional polynomial approximation

Teaching methods

Lecture in interaction with the students, with blackboard writing and projection
Solving practical exercises in individual or team work
Active, self-directed learning through tasks, sample solutions and accompanying materials

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

written exam paper

Requirements for the awarding of credit points

passed written exam

Applicability of the module (in other degree programs)

Bachelor of Computer Science
Bachelor of Computer Science
Bachelor's degree in Medical Informatics
Bachelor of Medical Informatics Dual
Bachelor of Computer Science

Literature

R. Schröder: Numerische Algorithmen, Skript zur Vorlesung.

Ergänzend:

G, Bärwolf, Numerik für Ingenieure, Physiker und Informatiker, Springer-Verlag, Berlin-Heidelberg-New York, 2017, dritte Auflage
G. Farin, Curves and Surfaces for CAGD, Academic Press, San Diego, 2002, fünfte Auflage.
M. Hermann, Numerische Mathematik, de Gruyter-Oldenbourg, 2011, dritte Auflage
T. Huckle, S. Schneider, Numerik für Informatiker, Springer-Verlag, Berlin-Heidelberg-New York, 2006, zweite Auflage.
B. Lenze, Basiswissen Angewandte Mathematik, W3L-Verlag, Dortmund, 2014, erster Nachdruck.
H. Prautzsch, W. Boehm, M. Paluszny, Bezier and B-Spline Techniques, Springer-Verlag, Berlin-Heidelberg-New York, 2010, erster Nachdruck.
R. Schaback, H. Wendland, Numerische Mathematik, Springer-Verlag, Berlin-Heidelberg-New York, 2005, fünfte Auflage.
J. Werner, Numerische Mathematik 1 und 2, Vieweg, Wiesbaden, 1992

Operations Research
WP

4 SWS

5 ECTS

Number
46841
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

Acquisition of basic knowledge to describe concrete problems with the help of linear models and knowledge of methods to determine and evaluate model solutions.

Technical and methodological competence:

Assessment of model approaches (validation)
Creating and evaluating admissible initial solutions using various solution algorithms
Developing optimal solutions from admissible initial solutions
Recognize and use correlations between start and end tableau (sensitivity analysis, ...)
Specifying special restrictions to derive integer solutions
Characterization of simplex solutions
Solving special OR problems (transport problems, ...)

Interdisciplinary methodological competence:

Describing decision problems using OR models to uncover relevant structural features
Determining approximate solutions for practical problems by linear modeling of restrictions
Developing solution approaches for business planning problems (subsection, production program, process planning)

Mathematical foundations of linear optimization
Graphical solutions
Algebraic determination of admissible corner points
Simplex algorithm
Problems with non-admissible initial solution (dual simplex algorithm, M-method, 2-phase method, 3-phase method)
Sensitivity analyses
Duality theory
Integer optimization
Special optimization methods (transport problems, ...)

Teaching methods

Lecture in interaction with the students, with blackboard writing and projection
Solving practical exercises in individual or team work

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

written exam paper

Requirements for the awarding of credit points

passed written exam

Applicability of the module (in other degree programs)

Bachelor of Business Informatics
Bachelor of Software and Systems Engineering (dual)
Bachelor of Computer Science
Bachelor of Computer Science

Literature

Neumann,K., Morlock, M.: Operations Research. Hanser, München
Rietmann, P.: Operations Research (Vorlesungsskript, 2018)
Rietmann, P.: Aufgaben und Lösungen, 2018
Rietmann, P.: OR-Formelsammlung, 2018

Rechnerarchitekturen
WP

4 SWS

5 ECTS

Number
46845
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

Technical and methodological competence:

knows the various basic architectures for digital computer architectures
can identify and classify the individual architecture elements
can analyze application scenarios and select suitable architecture features
knows the entire range from the structure level (RTL) to the instruction set level (ISA) and can apply these
can understand and apply architecture manuals and instruction set manuals of current computer architectures
Optimization options for computer architectures (e.g. caching, jump prediction) are understood and can be assessed
knows paradigms such as parallel processing and special areas such as architectures for embedded systems through exemplary insights
can assess and select microcontrollers with regard to their area of application and program them close to the hardware in assembler and C
can use a development environment (using the Keil uVision environment as an example)
can analyze current computer architectures and evaluate and discuss them against the background of their knowledge

Structure and function of the Turing machine as an introductory example of a very rudimentary computer architecture => identification of the basic components arithmetic unit/control unit/memory/instruction set
Structure and function of the integer Java virtual machine according to Tanenbaum
Instruction set (ISA) and microcode, optimization of microcode, explanation of the specifics of ISA in Java byte code, CISC, RISC
Analysis and optimization of the processing pipeline, instruction fetch unit, jump prediction, speculative execution, out-of-order execution
Analysis of memory architecture, caching, memory types (SDRAM, graphics DRAM, SRAM, flash) and architectures
Comparative analysis of Intel Core and Intel Netburst architecture with regard to the above-mentioned topics
Parallel computer architectures, including cache coherence (especially MESI), VLIW
Examples of special computers (mobile processors, data flow computers)
Architectures for embedded systems (including ARM, introduction of DMA and interrupt units)
Atmel AVR as an example for microcontrollers, architecture, ISA, assembler and C programming

Teaching methods

Lecture in interaction with the students, with blackboard writing and projection
Solving practical exercises in individual or team work
Processing programming tasks on the computer in individual or team work

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

written exam paper

Requirements for the awarding of credit points

passed written exam

Applicability of the module (in other degree programs)

Bachelor of Medical Informatics
Bachelor of Computer Science
Bachelor of Computer Science
Bachelor of Medical Informatics Dual
Bachelor of Computer Science

Literature

Tanenbaum, A.: Computerarchitektur, 5. Auflage, Pearson, 2006
Yiu, J.: The Definitive Guide to the ARM Cortex M0, Newnes, Elsevier, 2011
Martin, T.: The Designer's Guide to the Cortex-M Processor Family, Newnes, Elsevier, 2013
Brinkschulte, U.; Ungerer, T.: Mikrocontroller und Mikroprozessoren, 3. Auflage, Springer, 2010

Robotik
WP

4 SWS

5 ECTS

Number
46855
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

Technical and methodological competence:

After completing the lecture, students will be able to

Understand and apply methods and concepts of robotics
design and implement stationary and mobile robotics applications
set up kinematic equations for mobile and stationary robots
select components for robotics applications
configure and program mobile and stationary robots

Objectives and areas of application of robotics
Design of stationary and mobile robots
Kinematics of stationary robots
Applications of stationary robots
Subsystems of robots (joints, drives, actuators and sensors)
Kinematics of mobile wheel-driven robots
Self-localization and navigation of mobile robots

Teaching methods

Lecture in interaction with the students, with blackboard writing and projection
Exercise accompanying the lecture
Solving practical exercises in individual or team work
Internship accompanying the lecture

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

written exam paper

Requirements for the awarding of credit points

passed written exam

Applicability of the module (in other degree programs)

Bachelor of Computer Science
Bachelor of Computer Science
Bachelor of Computer Science

Literature

Corke, Peter: Robotics, Vision and Control: Fundamental Algorithms in MATLAB, second edition, Springer, 2017
Weber, Wolfgang: Industrieroboter: Methoden der Steuerung und Regelung, Carl Hanser Verlag, 3. Auflage, 2017
Siegwart, Roland; Nourbakhsh, Illah R.: Introduction to Autonomous Mobile Robots, MIT Press, 2nd Edition, 2011
Hesse, Stefan; Malisa, Viktorio (Hrsg.): Taschenbuch Robotik - Montage - Handhabung, Carl Hanser Verlag, 2010
Hertzberg, Joachim; Lingemann, Kai; Nüchter, Andreas: Mobile Roboter - Eine Einführung aus Sicht der Informatik, Springer Vieweg Verlag, 2012

Seminar - Methodik
WP

2 SWS

2 ECTS

Number
451811
Language(s)
de
Duration (semester)
1
Contact time
30 h
Self-study
45 h

Learning outcomes/competences

The skills acquired depend on the chosen methodological focus of the seminars. After attending the course, students will be able to:

Technical and methodological competence:

apply the methodological skills corresponding to the focus of the seminar in their studies and work

Interdisciplinary methodological skills:

apply the methods learned during the course to an interdisciplinary topic and present it to fellow students in an understandable way

Self-competence:

independently able to structure, develop and create scientific texts and presentations and to present these results
independently able to research and evaluate technical-scientific content

Social skills:

Working in groups and interacting within groups
Presenting and defending content in groups

As an alternative to this seminar, students can take a "Studium Generale" course, which expands their methodological skills

The seminars include topics that expand students' interdisciplinary scientific and methodological skills. The topics are offered each semester with new, up-to-date content by all professors and are offered to students in the university's electronic information service (web) (https://fh.do/inf/seminare). Examples of courses are Presentation techniques, introduction to scientific work, planning and conducting data surveys.

Alternatively, a methodologically oriented course can be taken in the "Studium Generale" in the scope of 2 SWS. The list of selectable courses can be found in the university's electronic information service (https://fh.do/inf/generale).

Teaching methods

Seminar

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

Presentation

Requirements for the awarding of credit points

Regular participation in at least 2/3 of the attendance dates

Applicability of the module (in other degree programs)

Bachelor's degree in Business Informatics
Bachelor of Computer Science
Bachelor of Medical Informatics

Literature

Literatur muss vom Studierenden selbst ermittelt werden.

Übergreifend:

Balzert, H.; Schröder, M. und Schäfer, C.; Wissenschaftliches Arbeiten; W3l; Witten; 2. Aufl.; 2011

Begründung zur Notwendigkeit der Teilnahmepflicht:

Es handelt sich um eine zu Exkursionen, Sprachkursen, Praktika und praktische Übungen vergleichbare Lehrveranstaltung mit in der Regel maximal 20 Teilnehmern. Durch eine regelmäßige Teilnahme werden die Fach- und Methodenkompetenzen der Studierenden in der Einübung des wissenschaftlichen Diskurses in Gruppenarbeit mit anderen Studierenden und im Dialog mit dem Dozenten erarbeitet und gefestigt. Eine Reflektion der Kompetenzen und damit der Lernziele ist selbstständig nicht ausreichend möglich. Nur ein geringer Anteil der Veranstaltung bezieht sich auf die selbstständige Einarbeitung in die fachlichen Inhalte und die Vorbereitung auf den wissenschaftlichen Diskurs, der größere Anteil bezieht sich auf die gemeinschaftliche Erarbeitung und Reflektion der Kompetenzen, sodass eine regelmäßige Teilnahme an mindestens 2/3 der Präsenzterminen für das Erreichen der Lernziele gegeben ist.

Serielle Bussysteme
WP

4 SWS

5 ECTS

Number
46896
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

Technical and methodological competence:

Knowledge and principles of the structure and use of serial bus systems, especially in the embedded world.

Selection of bus systems taking into account the application, determination of

Data volume
Reaction time
Cabling effort
Interference influence

Know and apply the structure and possible applications of various bus systems: I2C bus, SPI bus, CAN bus, LIN bus, Flex-Ray; measurement technology in the use of bus systems

Presentation and development of the topics:

physical layer
Bus access method
Reaction time consideration
µController connection
Performance consideration

of bus systems

Teaching methods

Lecture in interaction with the students, with blackboard writing and projection
Solving practical exercises in individual or team work
Processing programming tasks on the computer in individual or team work

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

written exam paper

Requirements for the awarding of credit points

passed written exam

Applicability of the module (in other degree programs)

Bachelor's degree in computer science

Literature

Andrew S. Tanenbaum: Computernetze, Springer-Verlag, 1999
CAN-Spezifikation, Version 2.0, Robert Bosch GmbH, 1991
LIN Specification Package, Revision 2.1, November 24, 2006
THE I2C-BUS SPECIFICATION VERSION 2.1, JANUARY 2000, NXP
Introduction to Serial Peripheral Interface, By D. Kalinsky and Roee Kalinsky, Embedded Systems Design, 02/01/02

Softwaretechnik C (Softwaremanagement)
WP

4 SWS

5 ECTS

Number
45261
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

Technical and methodological competence:

Be able to assess and evaluate the complexity of software projects
- Analyzing the background and causes of project failures
Know software development procedure and process models and be able to select them for specific contexts
- Waterfall and spiral model, prototyping, V-model XT, Rational Unified Process, agile models (Scrum)
Know and be able to apply processes and activities, roles and responsibilities in the area of software management

Interdisciplinary methodological competence:

Be able to organize and manage software projects
- Project planning, effort estimation, effort and cost controlling
Know product management
Know and be able to apply process analysis, measurement and evaluation
- Improvement of process quality (CMMI, GQM)

Self-competence:

Development and creation of software management-specific result documents
Independent creation and presentation of selected software management topics and content

Social skills:

Teamwork in groups of four over an entire semester

Professional field orientation:

Practical application and implementation of software management-specific processes and activities

Procedure and process models of software engineering (waterfall, concurrent and spiral model, V-Modell XT, Rational Unifed Process, Scrum)
Know and be able to apply processes and activities, concepts and methods of requirements management
Know and be able to apply risk management processes and activities, concepts and methods
Know and be able to apply project management (planning and control) processes and activities, concepts and methods
Know and be able to apply quality management processes and activities, concepts and methods
Know and be able to apply configuration management processes and activities, concepts and methods
Know and be able to apply product management processes and activities, concepts and methods
Know and be able to apply release management processes and activities, concepts and methods
Know and be able to apply processes and activities, concepts and methods of process improvement
Know and be able to apply framework models for process improvement

Teaching methods

Lecture in interaction with the students, with blackboard writing and projection
Exercise accompanying the lecture
Solving practical exercises in individual or team work
Internship accompanying the lecture
Group work
Exercises or projects based on practical examples
immediate feedback and performance review

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

written exam paper

Requirements for the awarding of credit points

passed written exam

Applicability of the module (in other degree programs)

Bachelor's degree in Software and Systems Engineering (dual)
Bachelor's degree in Software and Systems Engineering (dual)
Bachelor's degree in Business Informatics
Bachelor of Computer Science
Bachelor of Computer Science
Bachelor's degree in Medical Informatics
Bachelor of Computer Science Dual
Bachelor of Computer Science Dual
Bachelor of Medical Informatics Dual
Bachelor of Computer Science

Literature

Balzert, H. (2008): Lehrbuch der Softwaretechnik: Softwaremanagement, 2. Auflage, Heidelberg: Spektrum Akademischer Verlag.
Balzert, H. (2009): Basiskonzepte und Requirements Engineering, 3. Auflage, Heidelberg: Spektrum Akademischer Verlag.
Ludewig, J., Lichter, H. (2013): Software Engineering Grundlagen, Menschen, Prozesse, Techniken, 3. korrigierte Auflage, Heidelberg: dpunkt-Verlag.
Pichler, R. (2009): Scrum - Agiles Projektmanagement erfolgreich einsetzen, Heidelberg: dpunkt-Verlag.
Pohl, K.; Rupp, C. (2015): Basiswissen Requirements Engineering, 4. überarbeitete Auflage, Heidelberg: dpunkt-Verlag.
Sommerville, I. (2018): Software Engineering, 10. aktualisierte Auflage, München: Pearson.
Spitzcok, N.; Vollmer, G., Weber-Schäfer, U. (2014): Pragmatisches IT-Projektmanagement, 2. aktualisierte und überarbeitete Auflage, Heidelberg: dpunkt-Verlag.
Vollmer, G. (2017): Mobile App Engineering, Heidelberg: dpunkt-Verlag.
Vollmer, G. (WS 2019/2020): Unterlagen zur Lehrveranstaltung "Softwaretechnik C - Softwaremanagement".
Winkelhofer, G. (2005): Management- und Projekt-Methoden, 3. Auflage, Berlin, Heidelberg: Springer.

Softwaretechnik D (Qualitätssicherung und Wartung)
WP

4 SWS

5 ECTS

Number
46264
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

Teaching the knowledge required to achieve a defined level of quality in software development. The analytical and constructive measures for quality assurance are known and can be applied in a targeted manner. Methodical approach to software maintenance.

Technical and methodological competence:

Differentiating between analytical and constructive measures for quality assurance
Naming typical sources of error
Selecting suitable tools in the context of constructive software engineering
Selecting suitable metrics for quality measurement
Knowing different integration strategies
Recognizing the influence of automation on quality
Systematically derive test cases
Performing manual test procedures
Applying analytical test procedures
Naming risks, problems and principles of maintenance
Organizing software maintenance

Interdisciplinary methodological competence:

Operationalizing the concept of quality via quality models
Understanding that testing is a necessary but not sufficient measure to ensure quality
Conducting target group-oriented presentations

Professional field orientation:

Creating a quality manual
Selecting and using suitable tools (constructive software engineering)

Quality models
Sources of error
Constructive measures
Manual test methods
Tools
Black box test
White box test
Metrics
Static code analysis
Test management
Automation (software infrastructure)
Load test
Maintenance and care

Teaching methods

Lecture in interaction with the students, with blackboard writing and projection
Solving practical exercises in individual or team work

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

written exam paper

Requirements for the awarding of credit points

passed written exam

Applicability of the module (in other degree programs)

Bachelor's degree in Software and Systems Engineering (dual)
Bachelor's degree in Software and Systems Engineering (dual)
Bachelor's degree in Business Informatics
Bachelor of Computer Science
Bachelor of Computer Science
Bachelor's degree in Medical Informatics
Bachelor of Computer Science Dual
Bachelor of Medical Informatics Dual
Bachelor of Computer Science

Literature

Balzert, H.; "Lehrbuch der Softwaretechnik, Softwaremanagement", Spektrum Akademischer Verlag, Heidelberg, 2008
Binder, R.V.; "Testing Object-Oriented Systems", Addison-Wesley, Boston, 2000
Hoffmann, D.W.; "Software-Qualität", Springer Vieweg, Berlin, 2013
Liggesmeyer, P.; "Software-Qualität", Spektrum Akademischer Verlag, Heidelberg, 2009
Ludewig, J.; Lichter, H.; "Software Engineering", dpunkt.verlag, Heidelberg, 2010
Spillner, A.; Linz, T.; "Basiswissen Softwaretest", dpunkt.verlag, Heidelberg, 2012
Sneed, H.M.; Seidl, R.; Baumgartner, M.; "Software in Zahlen", Hanser, München, 2010

Systemprogrammierung
WP

4 SWS

5 ECTS

Number
46849
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

Technical and methodological competence:

Knowledge:

Fundamental concepts of operating systems
Functionality of linkers and loaders
Principles for debugging user programs
Concepts of the Java VM and dynamic memory management

Application:

Concurrent programming under Java
Using the methods of the Java Runtime, Thread and ClassLoader classes
Using synchronous and asynchronous communication

Selected topics from the field of operating systems (linkers and loaders, runtime environment, memory management, mutual exclusion, deadlocks, concurrent programming, scanners, parsers)
Selected topics from the field of distributed systems (synchronous and asynchronous communication, clock synchronization)

Teaching methods

Lecture in interaction with the students, with blackboard writing and projection
Solving practical exercises in individual or team work

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

written exam paper

Requirements for the awarding of credit points

passed written exam

Applicability of the module (in other degree programs)

Bachelor's degree in Software and Systems Engineering (dual)
Bachelor's degree in Software and Systems Engineering (dual)
Bachelor of Computer Science
Bachelor of Computer Science
Bachelor of Medical Informatics Dual
Bachelor of Computer Science

Literature

A. Silberschatz, P. Galvin: Operating System Concepts, John Whiley & Sons, 2008 (8th Edition)
Andrew S. Tanenbaum: Computernetzwerke, Pearson Studium, München 2003
Andrew S. Tanenbaum: Moderne Betriebssysteme, Pearson Studium, München 2009

Virtualisierung und Cloud Computing
WP

4 SWS

5 ECTS

Number
46810
Language(s)
en
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

Providing basic knowledge in the field of virtualization and cloud computing. Theoretical knowledge of architectures and technologies in this area and awareness of their strengths and weaknesses in various areas of application. Consolidation of specialist knowledge using practical laboratory tasks with currently relevant cloud services and technology platforms.

Technical and methodological expertise:

Learning the relevant technical terms in the field of virtualization and cloud computing
Classification and evaluation of the various concepts and architectures
Installation and configuration of simple virtual systems with different technologies
Conception and practical setup of simple cloud services with open-source and commercial resource management systems
Overview of traditional and new areas of application for virtualization and cloud computing
Overview of current research topics and evaluation of scientific publications

Virtualization of CPU, memory and network components
Container technology
Current virtualization and container platforms
Resource management and orchestration
Current resource management and orchestration platforms
Cloud computing service models (IaaS, PaaS etc.)
New areas of application for virtualization and cloud computing (edge computing, NFV etc.)
Open source development processes and communities

Teaching methods

Lecture in interaction with the students, with blackboard writing and projection
Processing programming tasks on the computer in individual or team work
Project work accompanying the lecture with final presentation

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

written written examination
study achievements during the semester (bonus points)

Requirements for the awarding of credit points

passed written exam

Applicability of the module (in other degree programs)

Bachelor's degree in Software and Systems Engineering (dual)
Bachelor's degree in Software and Systems Engineering (dual)
Bachelor of Computer Science
Bachelor of Computer Science
Bachelor's degree in Medical Informatics
Bachelor of Medical Informatics Dual
Bachelor of Computer Science Dual
Bachelor of Computer Science Dual

Literature

Thomas Erl, Zaigham Mahmood, Ricardo Puttini; Cloud Computing; Prentice Hall; 2013
K. Chandrasekaran; Essentials of Cloud Computing; CRC Press; 2015

Web-Technologien
WP

4 SWS

5 ECTS

Number
46898
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h

Learning outcomes/competences

This module provides students with an overview of the most important technologies used today to create web applications. After completing the course, they will have mastered the central principles and concepts on which modern web architectures are based.

Technical and methodological competence:

Completers of the module will be able to name the central basic principles of the WWW and classify them in the context of web applications
They acquire the professional competence to differentiate between client-side and server-side web development techniques. They can also name and use important client- and server-side technologies for the creation of web applications.

Interdisciplinary methodological competence:

The participants have mastered the analysis of a comprehensive requirement and can break it down into sub-requirements. They have experience of implementing partial requirements over several weeks as part of an overall project in a team.

Social skills:

The participants develop and implement solutions cooperatively in a team
They are also able to explain and discuss their ideas and solutions.

Professional field orientation:

Students acquire knowledge of typical tasks in web development and the application of specific web technologies.

The lecture covers the following topics:

Detailed knowledge of the structure of websites with HTML and CSS
Server-side technologies for the development of web applications (e.g. with Java, JavaScript)
Basic knowledge of web architectures based on the MVC pattern
Introduction to web services (e.g. REST)
Client-side technologies for the development of web applications (e.g. JavaScript)
Fundamental concepts and techniques in the browser (e.g. DOM, AJAX)
Basic knowledge of responsive web design

Teaching methods

Lecture in interaction with the students, with blackboard writing and projection
Exercise accompanying the lecture
Solving practical exercises in individual or team work
Internship accompanying the lecture
Processing programming tasks on the computer in individual or team work
Group work
Active, self-directed learning through internet-supported tasks, sample solutions and accompanying materials
Inverted teaching (inverted classroom)
E-learning
Blended learning
Just-in-time teaching
Use of learning games
Screencasts
Project-oriented internship in teamwork

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

written written examination
study achievements during the semester (bonus points)

Requirements for the awarding of credit points

passed written exam

Applicability of the module (in other degree programs)

Bachelor of Business Informatics
Bachelor of Software and Systems Engineering (dual)
Bachelor of Computer Science
Bachelor of Computer Science
Bachelor's degree in Medical Informatics
Bachelor's degree in Medical Informatics
Bachelor of Medical Informatics Dual
Bachelor of Computer Science Dual
Bachelor of Medical Informatics Dual

Literature

Wolf J.; HTML5 und CSS3: Das umfassende Handbuch; Rheinwerk Computing; 4. Auflage; 2021
Bühler P., Schlaich P., Sinner D.; HTML5 und CSS3: Semantik - Design- Responsive Layouts; Springer Vieweg; 2017
Simpson K.; Buchreihe "You Don't Know JS" (6 Bände); O'Reilly; 2015
Haverbeke M.; JavaScript: richtig gut programmieren lernen; dpunkt.verlag; 2020, 2. Auflage
Springer S.; Node.js: Das umfassende Handbuch; Rheinwerk Computing; 4. Auflage, 2021
Tilkov S., Eigenbrodt M., Schreier S., Wolf O.; REST und HTTP; dpunkt.verlag; 3. Auflage; 2015
Balzert H.; Lehrbuch der Softwaretechnik. Entwurf, Implementierung, Installation und Betrieb. Spektrum Akademischer Verlag; 3. Auflage; 2011
Tanenbaum A.; Computernetzwerke; Pearson Studium; 3. Auflage; 2000

6. Semester of study

Projektarbeit
PF

0 SWS

15 ECTS

Number
46193
Language(s)
de
Duration (semester)
1
Contact time
3 h
Self-study
147 h

Learning outcomes/competences

Through the project work, students learn the following skills, which prepare them for writing their later thesis and qualify them for starting their career:

Technical and methodological competence

Solving IT-specific problems, if possible in a business context, by creating a software/hardware solution in an engineering manner (i.e. specifying requirements, weighing up and evaluating alternative solutions, modeling systems and ensuring quality) while taking limited resources into account.

Interdisciplinary methodological competence

Conducting the work as a project (i.e. setting objectives and planning projects, pre- and post-calculation of the time required), as well as
Production of the written paper using scientific working methods (including literature research, correct citation).

Self-competence

Assessment of own work results

Social skills

Ability to work in a team with developers and (as far as possible) users, especially: to present work results, to lead and moderate meetings and to resolve conflicts.

Professional field orientation

Working on practically relevant tasks

For further details see process description PB-PAAA (Annex IV).

The content of a project is assessed according to effort and complexity, originality and independence, scientific working technique and methodical approach, practical implementation, style and external form.

Students have the right to suggest a project topic. The project should preferably be carried out outside the university (further details are regulated by the VA-PAAA-EXT procedural instructions). Group work is desired. The specific knowledge directly required in the projects will be taught in block courses if necessary.
Regular project meetings give students the opportunity to acquire the above-mentioned teamwork skills by practicing them. In particular, quality assurance is trained through the presentation of results from analysis, design and implementation.

Teaching methods

Project work
Concluding presentation

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

Project work with oral examination

Requirements for the awarding of credit points

Successful project work

Applicability of the module (in other degree programs)

Bachelor's degree in Medical Informatics
Bachelor of Medical Informatics Dual
Bachelor of Computer Science

Literature

Muss von den Studierenden selbst in Bezug zum gewählten Thema der Projektarbeit ermittelt werden.

Übergreifend:

- Wissenschaftliches Arbeiten - Wissenschaft, Quellen, Artefakte, Organisation, Präsentation - Helmut Balzert, Christian Schäfer, Marion Schröder - W3L, 2. Aufl., 2011

Seminar - Inhalt
PF

2 SWS

2 ECTS

Number
45182
Language(s)
de
Duration (semester)
1
Contact time
30 h
Self-study
45 h

Learning outcomes/competences

The skills acquired depend on the chosen focus of the seminars. After attending the course, students will be able to:

Technical and methodological skills:

apply the content-related skills corresponding to the focus of the seminar in their studies and profession
use scientific methods to prepare a presentation on the main topic. They can research, evaluate, structure, document and present
write a scientific term paper

Self-competence:

independently able to structure, develop and create scientific texts and presentations and to present these results
independently able to research and evaluate technical-scientific content

Social skills:

Working in groups and interacting within groups
Presenting and defending content in groups

Professional field orientation:

to develop content corresponding to the occupational field

The seminars include topics that expand students' specialist academic skills. Students prepare a presentation on a selected special topic in business administration, computer science and/or business informatics and present the content. The topics are offered each semester with new, up-to-date content by all professors and lecturers and are offered to students in the university's electronic information service (web) (https://fh.do/inf/seminare). Examples of courses are Modern Supply Chain Management for Information Logistics, Business Simulation and Social Networks. The professional orientation of the seminars is strengthened by the use of lecturers from Business Studies with special qualifications in the subjects.

Teaching methods

Seminar

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

Presentation

Requirements for the awarding of credit points

successful presentation
regular participation in at least 2/3 of the attendance dates

Applicability of the module (in other degree programs)

Bachelor's degree in Business Informatics
Bachelor of Computer Science
Bachelor of Medical Informatics

Literature

Literatur muss vom Studierenden selbst ermittelt werden.

Übergreifend:

Balzert, H.; Schröder, M. und Schäfer, C.; Wissenschaftliches Arbeiten; W3l; Witten; 2. Aufl.; 2011

Thesis mit Kolloquium
PF

0 SWS

15 ECTS

Number
103
Duration (semester)
1

Study plan

BWL

Algorithmen und Datenstrukturen

Datenbanken 1

Automatisierungstechnik

IT-Recht

Projektarbeit

Einführung in die Programmierung

Lern- u. Arbeitstechniken

Elektronik

Embedded Systems

Informatik und Gesellschaft

Seminar - Inhalt

Mathematik für Informatik 1

Mathematik für Informatik 2

Mathematik für Informatik 4

Kommunikations- und Rechnernetze

Studium Generale

Thesis mit Kolloquium

Rechnerstrukturen und Betriebssysteme 1

Mathematik für Informatik 3

Physik

Softwaretechnik 2

Compulsory elective modules (38)

Theoretische Informatik

Programmierkurs 1

Programmierkurs 2 TI

Systems Engineering

Rechnerstrukturen und Betriebssysteme 2

Softwaretechnik 1

Studium Generale

Technisches Englisch

Compulsory elective modules 1. Semester

Compulsory elective modules 2. Semester

Compulsory elective modules 3. Semester

Compulsory elective modules 4. Semester

Compulsory elective modules 5. Semester

Adaptive Systeme

Anerkannte Wahlpflichtprüfungsleistung

Anerkannte Wahlpflichtprüfungsleistung

Anerkannte Wahlpflichtprüfungsleistung

Anerkannte Wahlpflichtprüfungsleistung

Anerkannte Wahlpflichtprüfungsleistung

Angewandte Logiken

Ausgewählte Aspekte der Informatik

Componentware

Computergraphik

Controlling

Data Mining in Industrie u.Wirtschaft

Datenbanken 2

Digitale Bildverarbeitung

ERP 1 (Standardsoftware)

Effiziente Algorithmen und Datenstrukturen

Entwicklung verteilter Anwendungen

Hardware Engineering

IT-Servicemanagement

Informations- und Business Performance Management

Informationssicherheit

Kooperative Systeme

Künstliche Intelligenz

Mobile App Engineering

Modellbasierte Softwareentwicklung

Moderne Datenbanken

Multimedia

Numerische Algorithmen

Operations Research

Rechnerarchitekturen

Robotik

Seminar - Methodik

Serielle Bussysteme

Softwaretechnik C (Softwaremanagement)

Softwaretechnik D (Qualitätssicherung und Wartung)

Systemprogrammierung

Virtualisierung und Cloud Computing

Web-Technologien

Compulsory elective modules 6. Semester

Module overview

1. Semester of study

BWLPF 4 SWS 5 ECTS

Learning outcomes/competences

BWL
PF

4 SWS

5 ECTS

Einführung in die Programmierung
PF

10 SWS

10 ECTS

Mathematik für Informatik 1
PF

4 SWS

5 ECTS

Rechnerstrukturen und Betriebssysteme 1
PF

4 SWS

5 ECTS

Theoretische Informatik
PF

4 SWS

5 ECTS

Algorithmen und Datenstrukturen
PF

4 SWS

5 ECTS

Lern- u. Arbeitstechniken
PF

2 SWS

2 ECTS

Mathematik für Informatik 2
PF

4 SWS

5 ECTS