Course

INF2 - Computer Science 2

PDF Course Catalog Deutsche Version: INF2

Version: 5 | Last Change: 29.09.2019 16:57 | Draft: 0 | Status: vom verantwortlichen Dozent freigegeben

Long name Computer Science 2
Approving CModule INF2_BaMT
Responsible
Prof. Dr.-Ing. Arnulph Fuhrmann
Professor Fakultät IME
Level Bachelor
Semester in the year summer semester
Duration Semester
Hours in self-study 90
ECTS 6
Professors
Prof. Dr.-Ing. Arnulph Fuhrmann
Professor Fakultät IME
Requirements Computer Science 1
Language German
Separate final exam Yes
Literature
G. Saake, K. Sattler: Algorithmen und Datenstrukturen, dpunkt.verlag, 6. Auflage, 2020
R. Sedgewick, K. Wayne: Introduction to Programming in Java, Addison Wesley, 2017
W. Küchlin, A. Weber: Einführung in die Informatik - Objektorientiert mit Java, Springer, 2005
Final exam
Details
Students must demonstrate the following competences in a written examination:
- Development of short programmes to solve problems described in colloquial language (K.4, K.9)
- Development of short programs to solve abstractly described problems (K.2)
- Application of programming language and more abstract constructs to solve application problems (K.8)
- Reading, understanding and, if necessary, correction of given program fragments (K.4, K.10)
- Evaluation of statements with regard to their correctness (K.11)
Minimum standard
At least 50% of the total number of points.
Exam Type
Students must demonstrate the following competences in a written examination:
- Development of short programmes to solve problems described in colloquial language (K.4, K.9)
- Development of short programs to solve abstractly described problems (K.2)
- Application of programming language and more abstract constructs to solve application problems (K.8)
- Reading, understanding and, if necessary, correction of given program fragments (K.4, K.10)
- Evaluation of statements with regard to their correctness (K.11)

Learning goals
Knowledge
Advanced methods of object orientation
polymorphism
Abstract Classes
interfaces
modelling
Generic Programming
Dynamic data structures
concatenated lists
stacks
cues
hash tables
trees
algorithms
intricacy
O notation
expenditure of time
storage effort
performance measurement
General strategies for designing algorithms
brute force
greedy
divide-and-conquer
backtracking
sorting methods
Selection Sort
Insertion Sort
Merge Sort
search procedure
Linear search
Binary Search
Skills
Creating object-oriented programs in Java
Designing object-oriented models for a given problem
Using class diagrams
Convert to software
dynamic data structures
Using dynamic data structures in Java
Designing dynamic data structures
Implement dynamic data structures in Java
Determining the complexity of algorithms
Solving a problem using suitable algorithms
Selecting algorithms
Designing algorithms
Implementing Algorithms in Java
Expenditure classroom teaching
Type Attendance (h/Wk.)
Lecture 3
Exercises (whole course) 0
Exercises (shared course) 2
Tutorial (voluntary) 2
Special literature
keine/none
Special requirements
none
Accompanying material
electronic lecture slides for the lecture
electronic exercise collection
Separate exam
Exam Type
solving exercises within limited functional / methodical scope
Details
Independent solving of self-learning tasks on the topics of the lecture in the form of the development of more complex programs to solve problems described in colloquial or abstract language (K.4, K.5, K.9, K.2).
Minimum standard
More than 80% of all exercises submitted. A task is deemed to have been completed if it has been solved predominantly and independently.

Impressum
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