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06.07.2022 05:48:17
inf030 - Programming, Algorithms and Data Structures (Complete module description)
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Module label Programming, Algorithms and Data Structures
Module code inf030
Credit points 9.0 KP
Workload 270 h
Institute directory Department of Computing Science
Applicability of the module
  • Bachelor's Programme Business Informatics (Bachelor) > Basiscurriculum
  • Bachelor's Programme Computing Science (Bachelor) > Basismodule
  • Bachelor's Programme Economics and Business Administration (Bachelor) > Studienrichtung Wirtschaftsinformatik
  • Bachelor's Programme Mathematics (Bachelor) > Nebenfachmodule
  • Bachelor's Programme Sustainability Economics (Bachelor) > Wahlpflichtbereich
  • Dual-Subject Bachelor's Programme Computing Science (Bachelor) > Basismodule
Responsible persons
Lehrenden, Die im Modul (Authorized examiners)
Schönberg, Christian (Module responsibility)
Prerequisites
Skills to be acquired in this module

Programming is one of the basic activities of computer scientists and a prerequisite for many other courses in computer science studies. The aim of the module "Programming, Data Structures and Algorithms" is to learn the basic concepts of imperative, procedural and object-oriented programming using the Java programming language and to present known, efficient algorithms and data structures for various, frequently occurring problems.

After completing the module, the students should be able to independently develop imperative and simple object-oriented programmes based on Java for solving smaller problems and assess the efficiency of their programmes. They should also be able to apply important algorithms and select them based on their complexity.
 
**Professional competence**
The students:

- describe basic concepts of imperative programming with Java

- recognise imperative programming terminology and use the appropriate terms accurately in discussions

- recognise basic terminology of object-oriented programming

- describe what programs presented to them do

- independently develop programs to solve small problems

- systematically examine their own and other people's programmes for errors

- use modern programme development environments to develop and test programmes

- create algorithms with general design concepts (e.g. Greedy method, divide-and-conquer method)

- name algorithms and data structures for solving common problems and evaluate their applicability

- name problems of efficiency of algorithmic solutions of concrete problems and evaluate them

- make a well-founded choice of an algorithm and a data structure for solving a concrete problem

- apply the learned algorithms and data structures sensibly to given and concrete problems

**Methodogical competence**
The students:

- solve given problems from the point of view of imperative or object-oriented programming

- transfer practical experience in programme development to new tasks

**Social competence**
The students:

- communicate the structure and mode of operation of self-developed programmes to others

- present solutions to small tasks in front of groups

**Self-competence**
The students:

- organise themselves in finding algorithmic solutions to small and medium-sized problems in computer science

- incorporate the concepts of general programme design in their actions
Module contents

In the first part, general basic concepts of programming are introduced:

- Algorithm, programming languages, computer

- development tools, development phases

- compilers

- grammars

- logic

The second part deals with basic programming concepts:

- data types

- variables

- Expressions, statements

- control structures

- Methods, parameters

- recursion

- Reference data types, arrays

- Classes, objects

- Documentation

- Testing

 

The third part contains an introduction to data structures and algorithms as well as a discussion of their efficiency, i.e. the computational effort or memory requirements depending on the amount of data to be processed. The module introduces known, efficient algorithms and data structures for various, frequently occurring problems. These include in particular:

- Methods for searching for keys, as well as insertion and deletion in dynamic data sets, e.g. lists, trees, AVL trees or hash methods,

- Methods for searching for text patterns,

- Methods for sorting data by key values, e.g. QuickSort and HeapSort,

- Graph-based applications, e.g. for finding shortest paths in graphs.

 

The lecture part is supplemented by a comprehensive exercise part, in which in particular the taught programming contents are implemented in practical examples.
Reader's advisory

Essential:

Lecture Notes (made available either in printed form or via Stud.IP during the course of the lecture)

 

Good secondary literature:

Dietmar Ratz, Jens Scheffler, Detlev Seese, Jan Wiesenberger: Grundkurs Programmieren in Java, Carl Hanser Verlag.

Joachim Goll, Cornelia Heinisch: Java als erste Programmiersprache, Springer Vieweg Verlag

Ottmann, Widmayer: Algorithmen und Datenstrukturen. Spektrum Verlag, 5. Auflage, 2012

Segdewick, Wayne: Algorithms. Addison Wesley, 4th ed., 2011

Siege: Einführung in die Informatik. Shaker Verlag, 2013
Links

 

Language of instruction German
Duration (semesters) 1 Semester
Module frequency WiSe
Module capacity unlimited
Modullevel / module level BC (Basiscurriculum / Base curriculum)
Modulart / typ of module Pflicht / Mandatory
Lehr-/Lernform / Teaching/Learning method V+Ü
Vorkenntnisse / Previous knowledge
Course type Comment SWS Frequency Workload of compulsory attendance
Lecture
4 WiSe 56
Exercises
2 WiSe 28
Total time of attendance for the module 84 h
Examination Time of examination Type of examination
Final exam of module
At the End of the Semester
Portfolio / Klausur /mündliche Prüfung