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Informatics 2

Module name (EN):
Name of module in study programme. It should be precise and clear.
Informatics 2
Degree programme:
Study Programme with validity of corresponding study regulations containing this module.
Applied Informatics, Bachelor, SO 01.10.2026
Module code: PIB-INF2
SAP-Submodule-No.:
The exam administration creates a SAP-Submodule-No for every exam type in every module. The SAP-Submodule-No is equal for the same module in different study programs.
P221-0025
Hours per semester week / Teaching method:
The count of hours per week is a combination of lecture (V for German Vorlesung), exercise (U for Übung), practice (P) oder project (PA). For example a course of the form 2V+2U has 2 hours of lecture and 2 hours of exercise per week.
3V+1U (4 hours per week)
ECTS credits:
European Credit Transfer System. Points for successful completion of a course. Each ECTS point represents a workload of 30 hours.
5
Semester: 2
Mandatory course: yes
Language of instruction:
German
Assessment:
Written exam, Duration 120 min.

[updated 13.10.2024]
Applicability / Curricular relevance:
All study programs (with year of the version of study regulations) containing the course.

PIB-INF2 (P221-0025) Applied Informatics, Bachelor, ASPO 01.10.2022 , semester 2, mandatory course
PIB-INF2 (P221-0025) Applied Informatics, Bachelor, SO 01.10.2026 , semester 2, mandatory course
Workload:
Workload of student for successfully completing the course. Each ECTS credit represents 30 working hours. These are the combined effort of face-to-face time, post-processing the subject of the lecture, exercises and preparation for the exam.

The total workload is distributed on the semester (01.04.-30.09. during the summer term, 01.10.-31.03. during the winter term).
60 class hours (= 45 clock hours) over a 15-week period.
The total student study time is 150 hours (equivalent to 5 ECTS credits).
There are therefore 105 hours available for class preparation and follow-up work and exam preparation.
Recommended prerequisites (modules):
PIB-INF1 Informatics 1
PIB-MA1 Mathematics 1


[updated 11.12.2025]
Recommended as prerequisite for:
PIB-ATEC Automotive Engineering
PIB-BS Operating Systems
PIB-CBAU Compiler Construction
PIB-CVIS Computer Vision
PIB-DB Databases
PIB-EMOB Electromobility
PIB-ERSD Risk-Based Decision Making and Statistical Data Analysis
PIB-FFKC Error-Identification and Error-Correcting Codes
PIB-GKI Introduction to the Basics of Artificial Intelligence
PIB-IRET Information Retrieval
PIB-ISEC Information Security
PIB-KI
PIB-KISB Methods and Applications from the Field of Artificial Intelligence for Signal and Image Processing
PIB-MLRN Machine Learning
PIB-NUMS Numerical Software
PIB-PA Project work
PIB-PRA Work Experience Phase
PIB-SAI Applied Computer Science Seminar
PIB-SIDM Computer Science in the Media
PIB-SKOM


[updated 30.04.2026]
Module coordinator:
Prof. Dr. Klaus Berberich
Lecturer: Prof. Dr. Klaus Berberich

[updated 28.09.2016]
Learning outcomes:
After successfully completing this module, students will be familiar with basic problems on undirected and directed graphs, as well as character strings. They will be able to define and differentiate basic terms from the graph theory. Students will be aware of the relevance of graph problems (e. g. topological sorting and finding minimum spanning trees) for solving practical tasks (e. g. scheduling). They will be able to use efficient algorithms for solving basic problems on graphs and strings. For their description and analysis, students use the skills acquired in the “Informatics 1” module. Students will also be capable of formulating a given practical task as a problem and of solving it by applying the algorithms they have learned.

[updated 13.10.2024]
Module content:
1. Introduction
 
2. Searching and sorting
2.1 Breadth-first search
2.2 Depth-first search
2.3 Topological sorting
 
3. Shortest paths
3.1 Bellman-Ford algorithm
3.2 Dijkstra’s algorithm
3.3 Floyd-Warshall algorithm
 
4. Components and spanning trees
4.1 Determining connected components
4.2 Kruskal’s algorithm
4.3 Prim’s algorithm
 
5. Algorithms for character strings
5.1 Pattern matching
5.2 Longest common strings
5.3 Levenshtein distance
5.4 Pattern search in strings
 

[updated 13.10.2024]
Teaching methods/Media:
Slides, theoretical exercises.

[updated 24.02.2018]
Recommended or required reading:
Cormen Thomas H., Leiserson Charles E., Rivest Ronald L. und Stein Clifford: Algorithmen - Eine Einführung,
Oldenbourg , 2013
 
Gunther Saake und Kai-Uwe Sattler: Algorithmen und Datenstrukturen: Eine Einführung mit Java,
dpunkt.verlag, 2020
 
Sedgewick Robert, Wayne Kevin: Algorithmen und Datenstrukturen,
Pearson Studium, 2014

[updated 13.10.2024]
 
[Tue Jun 16 13:16:51 CEST 2026, CKEY=pi2, BKEY=pi3, CID=PIB-INF2, LANGUAGE=en, DATE=16.06.2026]