htw saar Piktogramm QR-encoded URL
Back to Main Page Choose Module Version:
emphasize objectives XML-Code


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.
Computer Science and Communication Systems, Bachelor, ASPO 01.10.2014
Module code: KI210
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.
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.
Semester: 2
Mandatory course: yes
Language of instruction:
Written exam

[updated 20.03.2007]
Applicability / Curricular relevance:
All study programs (with year of the version of study regulations) containing the course.

KI210 (P222-0017) Computer Science and Communication Systems, Bachelor, ASPO 01.10.2014 , semester 2, mandatory course
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):
KI100 Programming 1
KI110 Informatics 1
KI160 Mathematics 1

[updated 11.10.2017]
Recommended as prerequisite for:
KI300 Software Engineering 1
KI320 Computer Networks
KI420 Operating Systems
KI579 Simulation of Discrete Systems with AnyLogic
KI590 Work Experience Phase
KI675 Compiler Construction

[updated 22.01.2018]
Module coordinator:
Prof. Dr. Damian Weber
Prof. Dr. Damian Weber
Dipl.-Inform. Marion Bohr
Sarah Theobald, M.Sc.

[updated 11.10.2017]
Learning outcomes:
After completing this course, students will be able to use algorithms to solve graph problems. The solutions will involve the knowledge and methods learned in the module “Informatics 1”. Students will acquire the skills necessary to analyse algorithms.
They will also learn how to represent a real practical problem as graph problem and thus generate a solution to the original problem from the solution to the underlying graph problem.
In addition, the course will provide an intuitive introduction to important complexity classes as the basis for understanding the algorithmic solvability of problems. By analysing the resource consumption of algorithms, students will be able to decide whether there is an efficient, exact or heuristic method for solving a specific problem.

[updated 13.03.2007]
Module content:
1. Graphs
1.1......Data structures
1.3......Automata theory and formal languages
2. Problem-solving techniques
2.2......Dynamic programming
2.3......Greedy algorithms
3. Computability and complexity theory

[updated 06.05.2007]
Recommended or required reading:
CORMEN T., LEISERSON, C., RIVEST R., STEIN, C.: Introduction to Algorithms, Second Edition.

[updated 13.03.2007]
Module offered in:
SS 2017, SS 2016, SS 2015, SS 2014, SS 2013, ...
[Mon Jun 24 07:58:33 CEST 2024, CKEY=info2, BKEY=ki, CID=KI210, LANGUAGE=en, DATE=24.06.2024]