Bachelor-Studium Informatics
Wollen Sie zukünftige Lebens- und Arbeitsbereiche auf kreative Art und Weise mitgestalten? Interessieren Sie sich vielleicht auch für techniknahe Felder? Dann ist unserer Bachelor-Studiengang Informatics wie für Sie gemacht.
Denn eines ist sicher: Die Informatik prägt wie kein anderes Fach die Entwicklungen unserer Lebens- und Arbeitswelt der letzten Jahrzehnte und wird in Zukunft noch viel größere Bedeutung haben.
Der Studienbeitrag zzgl. 22,70 EUR ÖH-Beitrag gilt für EU- bzw. EWR-Staatsbürgerinnen und -Staatsbürger. Bitte beachten Sie, dass für Nicht-EU/EWR-Staatsbürgerinnen und -Staatsbürger eigene Studienbeiträge gelten.
Das Studium
Seit Herbst 2019 bietet die IMC FH Krems den englischsprachigen Bachelor-Studiengang Informatics an.
Informatik ist ein wesentlicher Innovationstreiber für Entwicklungen in vielen Lebens- und Arbeitsbereichen. Beispielsweise ermöglichen Computer die Modellierung und Vorhersage von ökonomischen, ökologischen und sozialen Entwicklungen, hilft die Bioinformatik neue Medikamente zu entwickeln oder werden mit maschinellem Lernen große Datenmengen sinnvoll lesbar und mittels Mustererkennung als wertvolle Ressource in unterschiedlichen Anwendungsfeldern nutzbar. Informatik bietet neue Möglichkeiten, ökonomische Mehrwerte zu schaffen, die Umwelt zu schützen und Menschenleben zu retten.
Die IMC Fachhochschule Krems richtet sich mit ihrem englischsprachigen Bachelor-Studiengang Informatics an Frauen und Männer, die sich für techniknahe Felder interessieren und kreativ zukünftige Arbeits- und Lebensbereiche mitgestalten möchten. Der Bachelor-Studiengang Informatics bietet einen Schwerpunkt im Bereich der Data Science und eine anwendungsnahe Vertiefung in den Wahlfächern „Business Process and Enterprise Technologies“ und „Bio Informatics“.
Ob in der Softwareentwicklung, der informationsgestützten Entscheidungsfindung oder dem IT-Consulting, Informatik-Absolventinnen und Absolventen finden ein breites Betätigungsfeld, sind national und international nachgefragt und zukunftsfit.
Die branchenunabhängige grundlegende Ausbildung ermöglicht den Einstieg in unterschiedliche Organisationen und Branchen ebenso wie die Qualifizierung für einen Master-Studiengang.
„In der Informatik geht es genauso wenig um Computer wie in der Astronomie um Teleskope.“ (Informatiker Edsger Wybe Dijkstra)
Informatics leicht erklärt
Als Informatikerin oder Informatiker beschäftigen Sie sich mit wissenschaftlichen und technischen Möglichkeiten, Informationen zu verarbeiten, in Wissen zu übersetzen und in Diensten verfügbar zu machen. Sie arbeiten als Software Developer, Data Scientist und IT Consultant oder entwickeln Interfaces für die Mensch-Computer-Interaktion.
Internet of Things, Industrie 4.0 und Social Media, die Vervielfachung von Speicherkapazitäten und die Steigerung cloudbasierter Rechenleistungen stehen stellvertretend für transformative informationsbasierte Technologien.
Erkenntnisse und Entwicklungen der Informatik sind wesentliche Innovationstreiber für Entwicklungen in anderen Bereichen. Team- und Anwendungsorientierung stehen heute im Vordergrund.
" Those who can imagine anything, can create the impossible. "
Informatik-Pioneer Alan Turing
Erfolgskonzept: Theorie + Praxis
Das Studium umfasst 3 Säulen:
- 1
1. Die Grundlagen
In den Semestern 1-4
In den ersten Semestern legen wir den Fokus auf die Grundlagen der angewandten Informatik. Dabei werden mit der theoretischen Informatik zentrale Problemstellungen der Informationsverarbeitung sowie statistische Methoden und Verfahren behandelt. Darauf aufbauend werden im Bereich der praktischen und technischen Informatik projektbezogen umsetzbare Lösungen entwickelt.
Einen Schwerpunkt legen wir auf dem Bereich des Software Engineering. Mit Werkzeugen und Methoden der Programmierung werden qualitätsvolle Software-Systeme entwickelt.
Einen weiteren Schwerpunkt bildet der Bereich der Data Science. Es wird ein Grundverständnis dafür geschaffen, wie Daten aus verschiedenen Quellen verfügbar gemacht und diese Daten analysiert werden können, um Schlussfolgerungen für konkrete Fragestellungen zu ziehen. Wir widmen uns branchenübergreifenden Modellen und Systemen der anwendungsbezogenen Generierung von Wissen aus Daten. Mit geeigneten Methoden der Visualisierung liefern wir Erkenntnisse für Wirtschaft und Wissenschaft.
Grundlegend werden in allen Anwendungsbereichen des Studiums Voraussetzungen des IT Rechts und der IT Security berücksichtigt. Weiters reflektierten und diskutieren wir kritisch die Auswirkungen der Datengenerierung, Datennutzung und der damit verbundenen Technologien für die Gesellschaft und das Individuum unter ethischen Gesichtspunkten.
Praxis von Anfang an: Projektarbeiten sind ein wichtiger Teil des Studiums. Schon im ersten Semester geht es los mit einem Web-Projekt. In Semester 2 und 3 widmen Sie sich einem Software-Projekt und in Semester 4 dem Data Science Capstone Projekt.
- 2
2. Der praktische Teil
Im 5. Semester
Das fünfte Semester steht ganz im Zeichen Ihres Praktikums. Es ist ein verpflichtender Teil des Studiums und dauert 22 Wochen. Sie haben die Wahl, wo sie es absolvieren: in einem Unternehmen, einer Organisation, einer Bildungs- oder Forschungsinstitution. Im Inland oder Ausland? Auch das liegt bei Ihnen. Mehr als die Hälfte unserer Studierenden nützt das Praktikum, um Erfahrungen in einem anderen Land zu sammeln. Das Praxissemester ist eine einzigartige Gelegenheit, um internationale Luft zu schnuppern, neue Methoden kennenzulernen und anderen Expertinnen und Experten über die Schulter zu schauen.
Das Team des IMC Career Centers und Ihre Lehrenden aus dem Studium helfen bei der Suche nach einem geeigneten Praktikumsplatz. Damit Sie dann während Ihres „Practical Training Semesters“ eines können: viel mitnehmen für Ihre berufliche Laufbahn.
- 3
3. Die Spezialisierung
Im 6. Semester
Zurück vom Praktikum, entscheiden Sie sich für eines der zwei Vertiefungsgebiete: Business Process and Enterprise Technologies oder Bioinformatics. So bieten wir Ihnen die Möglichkeit die Kerntätigkeitsfelder Software Development, Business Consulting und Data Science branchennahe zu vertiefen.
In der Spezialisierung Business Process and Enterprise Technologies arbeiten Sie an der Anpassung und Erweiterung von ERP Systemen (ERP = Enterprise Resources Planning) für Betriebe bzw. Organisationen. Hierbei wenden Sie bereits erlernte Methoden der Softwareentwicklung und grundlegende Schnittstellentechnologien zur Integration von Geschäftsanwendungen in ERP-Systemen an. Sie beschäftigen sich weiters mit der Transformation und Speicherung von Unternehmensdaten und Technologien des Data Warehousing. Die Implementierung wesentlicher Arbeitsschritte findet in einem praktischen ERP-Consulting Projekt statt.
In der Spezialisierung Bioinformatics beschäftigen Sie sich mit Methoden der Datenanalyse im Kontext der Bioinformatik. Sie erstellen und transformieren Rohdatensätze und analysieren und interpretieren diese mithilfe von Data-Science-Methoden. Weiters setzen Sie sich mit grundlegenden Konzepten des Visual Computing auseinander und wenden erlernte Data-Science-Techniken an, um biologische und medizinische Bilddaten zu analysieren. Die Implementierung wesentlicher Arbeitsschritte findet in einem praktischen Bioinformatik Projekt statt.
Studienplan
Was wird Sie im Studium genau erwarten? Der Studienplan gibt Ihnen eine Übersicht.
Klicken Sie auf die einzelnen Lehrveranstaltungen um nähere Informationen zu erhalten.
Tipp: Absolventinnen und Absolventen von österreichischen HTLs mit dem Schwerpunkt Informationstechnologie können sich viele Lehrveranstaltungen anrechnen lassen.
Course SWS ECTS Mathematics, Statistics and Theoretical Computer Science Mathematics I Mathematics I - Theory 2 3 Mathematics I - Theory
Module: Mathematics IRoot module: Mathematics, Statistics and Theoretical Computer ScienceSemester: 1 Course code: MATIT1VO Contact hours per week: 2 ECTS: 3Course Content:- Basic mathematical concepts (number theory, logic, sets and combinatorics)
- Graph theory & applications (directionality, degree, trees & forests, route problems & algorithms)
- Linear algebra & applications (vector spaces, matrices, endo-/homomorphism)
- Coding theory & applications (linear coding, cryptography)
- Introduction to R software for algebraic mathematics
Course outcome:Upon completion of the module, students are able to:
- formulate, calculate and correctly correlate classic computer science problems with their mathematical foundations,
- explain the relation of practical applications in computer science and their corresponding mathematical fields and theories,
- utilize a combination of manual solving and scientific computing applications to solve the problems and verify their solutions,
- explain their solutions to the given problems (on paper),
- use the R software to solve similar problems computationally.
Mathematics I - Exercise 2 3 Mathematics I - Exercise
Module: Mathematics IRoot module: Mathematics, Statistics and Theoretical Computer ScienceSemester: 1 Course code: MATIE1UE Contact hours per week: 2 ECTS: 3Course Content:Accompanying practical mathematical exercises to the lecture "Mathematics I - Theory"
Statistics and Probability in Computer Science Statistics and Probability in Computer Science - Theory 2 3 Statistics and Probability in Computer Science - Theory
Module: Statistics and Probability in Computer ScienceRoot module: Mathematics, Statistics and Theoretical Computer ScienceSemester: 1 Course code: SPCST1VO Contact hours per week: 2 ECTS: 3Course Content:- Combinatorics (permutations, enumeration)
- Stochastics
- Probability theory (probability spaces, random variables, distributions, standard deviation & variance, quantiles, independence)
- Joint & conditional probabilities, Bayes Theorem, law of large numbers
- Statistical testing of hypotheses (significance tests, confidence intervals)
- Descriptive statistics
- Applications in Data Science (statistical inference and predictions)
- Introduction to R software for statistics
Course outcome:Upon completion of the module, students are able to:
- explain the foundational concepts of mathematical statistics,
- perform calculations of probabilities, deviation and variance,
- utilize statistical tests of hypotheses, both on paper and with computational software (R), use the R software to solve similar problems computationally,
- relate these concepts to data science applications and the available electives,
- utilize a combination of manual solving and scientific computing applications to solve the problems and verify their solutions,
- explain their solutions to the given problems on paper.
Statistics and Probability in Computer Science - Exercise 2 3 Statistics and Probability in Computer Science - Exercise
Module: Statistics and Probability in Computer ScienceRoot module: Mathematics, Statistics and Theoretical Computer ScienceSemester: 1 Course code: SPCSE1UE Contact hours per week: 2 ECTS: 3Course Content:Accompanying practical exercises to the lecture "Statistics and Probability in Computer Science - Theory"
Software Engineering and Data Modelling Web Technologies 4 6 Web Technologies
Module: Software Engineering and Data ModellingRoot module: Software Engineering and Data ModellingSemester: 1 Course code: WT1ILV Contact hours per week: 4 ECTS: 6Course Content:- Practical Web-Project
- Languages of the web (e.g. XHTML, HTML5, CSS, JavaScript)
- Standard libraries and tools (JQuery, Angular/React, SVG)
- Foundational concepts (responsive design, WAI/W3C/accessible design)
- Protocols (HTTP(S))
- Asynchronism (XMLHttpRequest. Ajax)
Course outcome:Upon completion of this course, students are able to:
- conceptualize, design, develop and deploy static and dynamic webpages using languages such as XHTML, HTML5, CSS, JavaScript,
- assess and apply principles of responsive and accessible design and development to web applications in a project.
Programming I 4 6 Programming I
Module: Software Engineering and Data ModellingRoot module: Software Engineering and Data ModellingSemester: 1 Course code: PROGI1ILV Contact hours per week: 4 ECTS: 6Course Content:- Introduction to programming and programming languages
- Programming with Python
- Foundational concepts (variables, data types, operators, loops, branches, simple data structures, subroutines)
- Input/Output (incl. input validation)
- Iteration vs. Recursion
- Development operations in Python (modules and packages, virtual environments, libraries)
Course outcome:Upon completion of this course, students are able to:
- explain basic concepts of programming,
- write simple programs in Python including input/output of data,
- set up and maintain a development environment in Python.
Computer Science and Society Introduction: Applied Informatics 1 1 Introduction: Applied Informatics
Module: Computer Science and SocietyRoot module: Computer Science and SocietySemester: 1 Course code: IAI1VO Contact hours per week: 1 ECTS: 1Course Content:- Introduction of the electives as continuation of the fundamentals of computer science
- Examples of applied informatics in the different fields of application
- Outlook towards the planned project work relating to the electives
Course outcome:Upon completion of this course, students are able to:
- to discuss the SW development framework for programming and data analysis for an exemplary field (analysis, problem definition, solution design, implementation),
- understand the different domains in sufficient detail to be able to explain and select their elective path preference.
General Business Administration 2 3 General Business Administration
Module: Computer Science and SocietyRoot module: Computer Science and SocietySemester: 1 Course code: GBUS1VO Contact hours per week: 2 ECTS: 3Course Content:Basics of Business Administration and overview on and principles of:
- Human Resources
- Finance
- Marketing
- Operations
Course outcome:Upon completion of this course, students are able to:
- explain basic business terms,
- identify and describe the structure, functioning and complexity of an organization and the dependencies of its parts,
- describe the fundamentals of doing business according to the classical different functions (Marketing, Accounting, Finance, HR, Operations),
- distinguish between strategic, and operative decisions.
Social Skills Intercultural Competences 1 2 Intercultural Competences
Module: Social SkillsRoot module: Social SkillsSemester: 1 Course code: IC1WK Contact hours per week: 1 ECTS: 2Course Content:- Definition, elements and characteristics of culture
- National cultures and subcultures
- Contradictory views of culture
- Intercultural abilities and skills (cognitive, emotional and social components)
- Companies and cultural diversity, and intercultural experiences
Course outcome:Upon completion of this course, students are able to:
- discuss problems arising in international projects or companies as a result of cultural differences between individuals and groups, and draw up approaches for resolving such problems,
- identify influences on communication and management, taking cultural circumstances into account, and describe the most important intercultural-management models,
- Critically reflect the cultural heterogeneity of their group.
Course SWS ECTS Mathematics, Statistics and Theoretical Computer Science Mathematics II 2 3 Mathematics II
Module: Mathematics, Statistics and Theoretical Computer ScienceRoot module: Mathematics, Statistics and Theoretical Computer ScienceSemester: 2 Course code: MATII2ILV Contact hours per week: 2 ECTS: 3Course Content:- Basic concepts of mathematical analysis (sequences, series)
- Elementary functions & applications (limits, zero sets, continuity)
- Differential / integral calculus, differential equations
- Applications in Data Science (gradient descent)
Course outcome:Upon completion of this course, students are able to:
- describe foundational concepts of mathematical analysis,
- solve problems from the domains of differential and integral calculus, both on paper and with computational software (R),
- relate the mathematical concepts to data science applications and the available electives.
Theoretical Computer Science and Logic 2 3 Theoretical Computer Science and Logic
Module: Mathematics, Statistics and Theoretical Computer ScienceRoot module: Mathematics, Statistics and Theoretical Computer ScienceSemester: 2 Course code: TCSL2ILV Contact hours per week: 2 ECTS: 3Course Content:- Propositional logic (concepts, syntax & semantics)
- Finite-state machines (concepts, representations)
- Formal language theory (regular/context free grammars, regular expressions)
- Fundamentals of first order logic (concepts, syntax & semantics: alphabets, symbols, formation rules)
- Petri nets and applications
Course outcome:Upon completion of this course, students are able to:
- demonstrate their knowledge and understanding of foundational theoretical computer science concepts,
- relate theoretical concepts and their paradigms to their applications in data science and the electives.
Algorithms and Data Structures I 2 3 Algorithms and Data Structures I
Module: Mathematics, Statistics and Theoretical Computer ScienceRoot module: Mathematics, Statistics and Theoretical Computer ScienceSemester: 2 Course code: ADSI2ILV Contact hours per week: 2 ECTS: 3Course Content:- Descriptive analysis of algorithms (runtime complexity, notation)
- Algorithmic paradigms (greedy, divide and conquer, branch and bound)
- Sorting and searching (binary/balanced search trees, hashing, insertion sort, selection sort, merge sort, quicksort, bubble sort)
Course outcome:Upon completion of this course, students are able to:
- explain foundational algorithmic concepts such as runtime complexity and notations,
- implement algorithmic paradigms for common software development tasks,
- evaluate algorithmic implementations based on their performance and applicability to the problem at hand.
Computer Systems Database Systems Database Systems - Theory 2 2 Database Systems - Theory
Module: Database SystemsRoot module: Computer SystemsSemester: 2 Course code: DBST2VO Contact hours per week: 2 ECTS: 2Course Content:- Semantic data modelling in relational contexts (EER diagrams, conceptual schemata)
- Foundations of relational database management systems (RDBMS)
- Relational query languages (SQL, SQL extensions)
- Transaction and error handling
- Non-Relational database concepts and applications (NoSQL: semi-structured data, schema-less data models, graph databases)
- Database systems for big data analysis
- In-memory and high–performance key-value-stores (Redis, SAP Hana)
Course outcome:Upon completion of the module, students are able to:
- explain basic relational and non-relational database concepts,
- relate common database paradigms to applications in Data Science,
- semantically create data models based on real-world examples and visualize them via EER diagrams,
- install and administrate simple relational and other database systems (including virtualized instances),
- perform simple CRUD operations and basic queries in SQL as well as query key-value stores.
Database Systems - Exercise 2 3 Database Systems - Exercise
Module: Database SystemsRoot module: Computer SystemsSemester: 2 Course code: DBSE2UE Contact hours per week: 2 ECTS: 3Course Content:- Accompanying practical exercises to the lecture "Database Systems - Theory"
- Introduction to database administration for relational and other databases
- Exercises focusing on querying databases (joins, subqueries, generic where clauses)
Technical Foundations of Computer Science 2 2 Technical Foundations of Computer Science
Module: Computer SystemsRoot module: Computer SystemsSemester: 2 Course code: TFCS2VO Contact hours per week: 2 ECTS: 2Course Content:- Binary numbers
- Information and coding theory
- Boolean algebra
- Logic circuits (adders, encoding, multiplexing)
- Foundations of computer hardware (CPU, BUS, memory, storage, mobile device technologies)
Course outcome:Upon completion of this course, students are able to:
- explain the foundational concepts of information and coding theory,
- perform basic binary calculations and Boolean algebra,
- identify logic circuits and explain their use.
Networking Technologies and Management Systems I 2 2 Networking Technologies and Management Systems I
Module: Computer SystemsRoot module: Computer SystemsSemester: 2 Course code: NTMGTI2ILV Contact hours per week: 2 ECTS: 2Course Content:- Foundational concepts of network technologies (architectures, topologies, OSI-model, network addressing, routing, switching, NAT, subnets)
- Network protocols (ARP, TCP/IP – IPv4/6, DNS, UDP, ICMP)
- Transfer security concepts (firewalls, end-to-end encryption, public key encryption, ciphers, certificates, SSH/TLS)
- Network management (SNMP)
Course outcome:Upon completion of this course, students are able to:
- explain foundational concepts in wired computer networks and technologies,
- identify key issues in network security and their remedies,
- describe basic network protocols and layers.
Software Engineering and Data Modelling Programming II 4 6 Programming II
Module: Software Engineering and Data ModellingRoot module: Software Engineering and Data ModellingSemester: 2 Course code: PROGII2ILV Contact hours per week: 4 ECTS: 6Course Content:- Advanced data abstraction concepts (objects, classes, instances, inheritance)
- Recursive data structures (lists, dictionaries, list comprehension)
- Basic design patterns (singleton, façade, decorators, context managers)
- Database access (ORMs, active record and data mapper)
- Exception handling
- Automated software testing (unit tests, fixtures, coverage)
- Pythonic programming (PEP8 style guide, code documentation)
- Basic backend development for web applications (Django)
Course outcome:Upon completion of this course, students are able to:
- implement complex software projects in Python,
- utilize advanced data abstraction concepts in Python,
- follow basic paradigms of error handling, software testing and pattern utilization.
Design Methodology in Human Computer Interaction 2 3 Design Methodology in Human Computer Interaction
Module: Software Engineering and Data ModellingRoot module: Software Engineering and Data ModellingSemester: 2 Course code: DMHCI2ILV Contact hours per week: 2 ECTS: 3Course Content:- Practical Software-Project I (customer meeting, project concept)
- Introduction to user interface design
- HCI-Design paradigms (participatory design, user-centered design)
- Design tools and methodologies (prototyping, scenarios, mock-ups, user stories, technology probes)
- Foundations of User Modelling
Course outcome:Upon completion of this course, students are able to:
- design and adapt interfaces, products and applications for, and in cooperation with end-users,
- apply design ideation and iterative user testing methodologies in software projects,
- relate paradigms and methodologies in HCI-Design to the curricular electives and their application.
Computer Science and Society Reflections on Computer Science, Society and Ethics 1 1 Reflections on Computer Science, Society and Ethics
Module: Computer Science and SocietyRoot module: Computer Science and SocietySemester: 2 Course code: RCSSE2TU Contact hours per week: 1 ECTS: 1Course Content:- subject areas related to the curriculum of the current semester are reviewed, critically analysed and discussed from ethical, cultural and sociological viewpoints by means of lectures and contributions from students
Course outcome:Upon completion of this course, students are able to:
- critically reflect on and discuss ethical, social and cultural aspects of information technology as framed by interdisciplinary overlaps,
- manage and moderate a critical discussion of ethical questions connected with informatics, data and related responsibilities, and formulate possible courses of action based on this discussion.
Social Skills Creative Thinking 2 2 Creative Thinking
Module: Social SkillsRoot module: Social SkillsSemester: 2 Course code: CT2WK Contact hours per week: 2 ECTS: 2Course Content:- Design thinking methods
- Creativity and problem-solving techniques and methods:
- Brainstorming, Mind mapping, customer journey mapping, personas, empathy cards and mock-ups
- Lateral thinking, Divergent and convergent thinking, Disney Method
Course outcome:Upon completion of this course, students are able to:
- address specific questions/problems using various creative techniques,
- describe the creative process and present the solution process,
- develop a systematic approach to dealing with complex problems in line with user requirements and needs, and outline its application.
Course SWS ECTS Mathematics, Statistics and Theoretical Computer Science Advanced Statistical Methods for Data Science 2 4 Advanced Statistical Methods for Data Science
Module: Mathematics, Statistics and Theoretical Computer ScienceRoot module: Mathematics, Statistics and Theoretical Computer ScienceSemester: 3 Course code: ASMDS3ILV Contact hours per week: 2 ECTS: 4Algorithms and Data Structures II 2 3 Algorithms and Data Structures II
Module: Mathematics, Statistics and Theoretical Computer ScienceRoot module: Mathematics, Statistics and Theoretical Computer ScienceSemester: 3 Course code: ADSII3ILV Contact hours per week: 2 ECTS: 3Course Content:- Advanced theoretical aspects of algorithms (P vs. NP, NP-completeness)
- Advanced algorithmic paradigms (prune and search, parametrized complexity, kernelization)
- Algorithmic approximation, heuristics (TSP, evolutionary algorithms)
- Applications in Data Science (runtime optimization for large datasets)
Course outcome:Upon completion of this course, students are able to:
- explain advanced algorithmic concepts such as NP-hardness,
- describe advanced algorithmic paradigms,
- judge algorithmic implementations based on their performance and applicability to the problem at hand,
- relate algorithms and their paradigms to their application in data science and the electives.
Computer Systems Networking Technologies and Management Systems II 2 3 Networking Technologies and Management Systems II
Module: Computer SystemsRoot module: Computer SystemsSemester: 3 Course code: NTMGTII3ILV Contact hours per week: 2 ECTS: 3Course Content:- Wireless network transmission technologies and specifications (eg. GSM/LTE/3G/4G/5G, IEEE 802.11, Bluetooth, NB-IoT, mesh networks)
- Quality of Service (QoS), fault tolerance
- Introduction to unix commandline tools for systems and network adminstration
- Virtualisation technologies (Docker, Linux Containers)
Course outcome:Upon completion of this course, students are able to:
- explain foundational concepts in mobile / wireless computer networks and technologies,
- identify key issues in network performance (QoS) and their remedies,
- troubleshoot computer network issues.
Operating Systems 2 3 Operating Systems
Module: Computer SystemsRoot module: Computer SystemsSemester: 3 Course code: OS3ILV Contact hours per week: 2 ECTS: 3Course Content:- History and basic components of operating systems
- OS architectures, abstractions
- Processes and threads (process states and management, multithreading)
- Memory management (de-/allocation, relocation, segmentation, paging, virtual memory management, page replacement, protection and sharing)
- Input-output and disk management (devices and device characteristics, I/O operations, drivers, buffering, disks, file systems, file system organization)
- OS networking concepts
- OS security (threats, security measures, access control, authentication, disk encryption)
- OS virtualization
- OS considerations for big data analysis (Windows/Unix comparisons, memory management for data science)
Course outcome:Upon completion of this course, students are able to:
- explain fundamental concepts of operating systems,
- develop applications with regards to operating system considerations and limitations,
- evaluate different operating system choices regarding their suitability for data science applications.
Software Engineering and Data Modelling Software Engineering and Project Management 4 6 Software Engineering and Project Management
Module: Software Engineering and Data ModellingRoot module: Software Engineering and Data ModellingSemester: 3 Course code: SWEPM3ILV Contact hours per week: 4 ECTS: 6Course Content:- Practical Software-Project II (technical implementation)
- Requirements analysis and engineering
- Software development process modelling & model comparison
- Scrum (focusing on values, introducing practices, roles & responsibilities)
- Working in iterations with quick to rapid feedback
- Version control with Git
- QA with unit, integration and functional tests
- Automation with CI/CD
- Preparation of IPMA certification
Course outcome:Upon completion of this course, students are able to:
- explain and assess different project management methodologies,
- apply project management in in-class work in managed and self-organised software development teams in software projects.
Computer Science and Society Reflections on Critical Algorithm Studies Reflections on Computer Science, Society and Ethics 1 1 Reflections on Computer Science, Society and Ethics
Module: Reflections on Critical Algorithm StudiesRoot module: Computer Science and SocietySemester: 3 Course code: RCSSEE3TU Contact hours per week: 1 ECTS: 1Course Content:- subject areas related to the curriculum of the current semester are reviewed, critically analysed and discussed from ethical, cultural and sociological viewpoints by means of lectures and contributions from students
Course outcome:Upon completion of this course, students are able to:
- critically reflect on and discuss ethical, social and cultural aspects of information technology as framed by interdisciplinary overlaps,
- manage and moderate a critical discussion of ethical questions connected with informatics, data and related responsibilities, and formulate possible courses of action based on this discussion.
Critical Algorithm Studies 2 2 Critical Algorithm Studies
Module: Reflections on Critical Algorithm StudiesRoot module: Computer Science and SocietySemester: 3 Course code: CAS3SE Contact hours per week: 2 ECTS: 2Course Content:- Critical reflection and analysis of algorithmic systems
- Algorithmic bias and discrimination
- Algorithmic transparency and accountability
- Computer Science Culture (impact, influences and re-production)
- Critical Data Studies
- Auditing algorithms
Course outcome:Upon completion of this course, students are able to:
- critically reflect on ethical challenges related to the design, production, implementation and impact of algorithmic systems,
- identify problematic aspects of algorithmic decision making, machine learning and data science,
- formulate strategies to combat inequalities perpetuated by algorithmic systems.
Process Management 2 3 Process Management
Module: Computer Science and SocietyRoot module: Computer Science and SocietySemester: 3 Course code: PSM3ILV Contact hours per week: 2 ECTS: 3Course Content:- Definition of processes (management, business, support)
- Corporate value chain model
- Business process management lifecycle
- Business process mapping, re-engineering
- Modelling business processes using UML and corresponding tools
- Business Process Automation (SOA Reference Architecture)
- Introduction to popular business process management software suites
Course outcome:Upon completion of this course, students are able to:
- discover and model business processes using elicitation techniques and modelling language and tools,
- identify bottlenecks and problems in business processes,
- improve, optimize and automate business processes,
- re-engineer business processes from scratch.
Computer Science and Law 2 3 Computer Science and Law
Module: Computer Science and SocietyRoot module: Computer Science and SocietySemester: 3 Course code: CSL3VO Contact hours per week: 2 ECTS: 3Course Content:- Legal basics (e.g. states, national law, international law, EU laws, regulations)
- Foundational challenges of technology law (geographical applicability, structural challenges)
- Contract & liability law (EU General Data Protection Regulation)
- Copyright law (basic concepts, intellectual property, open source laws & licenses)
Course outcome:Upon completion of this course, students are able to:
- explain basic legal terms and challenges related to information technologies and law,
- discuss practical, data-related matters linked to corporate and organisational settings from a legal perspective,
- identify possible steps and draw up recommendations for action.
Research and Scientific Working Scientific Skills and Writing 2 2 Scientific Skills and Writing
Module: Research and Scientific WorkingRoot module: Research and Scientific WorkingSemester: 3 Course code: SSW3PS Contact hours per week: 2 ECTS: 2Course Content:- Fundamentals of academic research (academic quality criteria, everyday and scientific knowledge, types of academic statement, types of academic paper, criteria for evaluating academic research)
- Formulating arguments in academic papers
- Literature research, evaluation and appraisal
- Process of compiling an academic paper
Course outcome:- apply the principles of academic research in the preparation of a seminar paper and address research questions using scientific literature.
Course SWS ECTS Computer Systems Distributed Systems Distributed Systems - Theory 2 3 Distributed Systems - Theory
Module: Distributed SystemsRoot module: Computer SystemsSemester: 4 Course code: DST4VO Contact hours per week: 2 ECTS: 3Course Content:- Distributed processes and communication technologies (sockets, RPC/RMI)
- Principles of naming and discovery
- Fault tolerance, process resilience, consistency and replication
- Synchronization (clocks, fundamental algorithms for synchronization)
- Security in distributed systems
- Distributed Applications (peer-to-peer networking, SaaS, cloud computing, distributed scientific computing, Google App Engine, Amazon EC2, Apache Hadoop)
Course outcome:Upon completion of the module, students are able to:
- describe foundational concepts and challenges of distributed systems,
- evaluate software paradigms and strategies for distributed applications,
- assess the suitability of cloud computing services for given distributed applications,
- conceptualize, design and implement distributed software applications,
- integrate and deploy a distributed application with a cloud computing platform (Google App Engine, Amazon EC2, Apache Hadoop),
- evaluate and improve distributed solutions in regards to security and performance.
Distributed Systems - Exercise 2 3 Distributed Systems - Exercise
Module: Distributed SystemsRoot module: Computer SystemsSemester: 4 Course code: DSE4UE Contact hours per week: 2 ECTS: 3Course Content:- Accompanying practical exercises to the lecture "Distributed Systems - Theory"
- Practical programming exercises for distributed applications and environments
IT Security Risk Management 2 3 Risk Management
Module: IT SecurityRoot module: IT SecuritySemester: 4 Course code: ITRM4VO Contact hours per week: 2 ECTS: 3Course Content:- Definition of Risks
- Risk assessment methodologies
- Quality assurance
- Risk management and compliance
Course outcome:Upon completion of this course, students are able to:
- identify key characteristics of software development projects and describe their relation to risk assessment,
- perform basic risk assessment for software development tasks and projects.
Cybersecurity and Data Protection 3 4 Cybersecurity and Data Protection
Module: IT SecurityRoot module: IT SecuritySemester: 4 Course code: CSDP4VO Contact hours per week: 3 ECTS: 4Course Content:- Security risks & threats (risk analysis, attack vectors and methodologies)
- Security domains
- Operating system and network security
- Organizational and operational security
- Security in software projects and application development
- Access control paradigms (authentication, authorization)
- Security enhancing technologies and countermeasures (cryptography, public/private key encryption, firewall systems)
- Security audits and penetration testing
- Information security guidelines, governance & protocols
Course outcome:Upon completion of this course, students are able to:
- explain common security risks, threats and countermeasures,
- perform risk assessment for software projects,
- apply countermeasures to improve domain security.
Data Science and Emerging Technologies From Data Capturing to Analysis and Interpretation Data Mining, Acquisition and Preparation 2 3 Data Mining, Acquisition and Preparation
Module: From Data Capturing to Analysis and InterpretationRoot module: Data Science and Emerging TechnologiesSemester: 4 Course code: DMAP4ILV Contact hours per week: 2 ECTS: 3Course Content:- Data acquisition methods
- Survey techniques and crowdsourcing
- Scraping
- Distributed sensor networks
- Selective data acquisition
- Public domain datasets
- Multi-origin data sources and data merging
- Data preparation
- Data requirements specifications and modelling
- Explorative data analysis (EDA)
- Data integrity and quality estimation
- Feature engineering
Course outcome:Upon completion of this course, students are able to:
- define data requirements based on an application problem statement,
- apply different data acquisition methods,
- explore and prepare collected datasets using EDA, quality estimations, feature engineering and text analysis methods.
Machine Learning, Artificial Intelligence and Big Data Analytics 3 4 Machine Learning, Artificial Intelligence and Big Data Analytics
Module: From Data Capturing to Analysis and InterpretationRoot module: Data Science and Emerging TechnologiesSemester: 4 Course code: MLAIBD4ILV Contact hours per week: 3 ECTS: 4Course Content:- Machine Learning paradigms and techniques
- Supervised learning (classification, regression)
- Unsupervised learning (clustering, association)
- Semi-supervised learning (deep learning & neural networks, advanced dimensionality reduction methods, reinforcement learning, meta learning, ensemble learning)
- Distributed data processing technologies / cluster environments (Microsoft AzureML, Apache Hadoop & Spark)
- Case studies of ML applications
- Image classification
- Recommender systems
- Purchase pattern analysis
Course outcome:Upon completion of this course, students are able to:
- explain supervised and unsupervised machine learning methods,
- implement machine learning projects with current and emerging distributed platforms and environments,
- assess the suitability of different machine learning, AI and big data analytics techniques for given problem statements.
Data Visualization, Presentation and Real-time Integration of Digital Products 2 3 Data Visualization, Presentation and Real-time Integration of Digital Products
Module: From Data Capturing to Analysis and InterpretationRoot module: Data Science and Emerging TechnologiesSemester: 4 Course code: DVIS4ILV Contact hours per week: 2 ECTS: 3Course Content:- Foundational concepts of data visualization (human cognition & perception, color theory, morphology)
- Visualization as a means to exploration, confirmation and presentation
- Visualization tools and techniques (plots, charts, graphs, diagrams, alignment, scaling, order)
- Interactive visualization design (visual data exploration)
- Real-Time visualizations
- Visualization software libraries and tools (Tableau, Highcharts)
Course outcome:Upon completion of this course, students are able to:
- describe foundational concepts of data visualization, their application domains and use cases,
- visualize a variety of datasets for data science and machine learning applications,
- design and implement interactive / real-time visualizations.
Data Science Capstone Project 3 4 Data Science Capstone Project
Module: From Data Capturing to Analysis and InterpretationRoot module: Data Science and Emerging TechnologiesSemester: 4 Course code: DSCP4WK Contact hours per week: 3 ECTS: 4Course Content:- Conceptualize. and implement a data science project
- Define and evaluate measures of success
- Present the project outcomes to peers
Course outcome:Upon completion of this course, students are able to:
- apply learned techniques, technologies and methodologies in a practical context,
- document progress and identify obstacles throughout the implementation process,
- evaluate a project’s success based on self-determined criteria,
- present the project outcomes to their peers.
Computer Science and Society Reflections on Computer Science, Society and Ethics 1 1 Reflections on Computer Science, Society and Ethics
Module: Computer Science and SocietyRoot module: Computer Science and SocietySemester: 4 Course code: RCSSE4TU Contact hours per week: 1 ECTS: 1Course Content:- subject areas related to the curriculum of the current semester are reviewed, critically analysed and discussed from ethical, cultural and sociological viewpoints by means of lectures and contributions from students
Course outcome:Upon completion of this course, students are able to:
- critically reflect on and discuss ethical, social and cultural aspects of information technology as framed by interdisciplinary overlaps,
- manage and moderate a critical discussion of ethical questions connected with informatics, data and related responsibilities, and formulate possible courses of action based on this discussion.
Research and Scientific Working Bachelor Exposé Preparation 1 2 Bachelor Exposé Preparation
Module: Research and Scientific WorkingRoot module: Research and Scientific WorkingSemester: 4 Course code: BP4PS Contact hours per week: 1 ECTS: 2Course Content:- Approaches to and possible applications for research methods
- Preparing a proposal for an academic paper in engineering sciences
Course outcome:Upon completion of this course, students are able to:
- independently apply the principles of academic research in the preparation of an extended proposal and the subsequent bachelor paper. The course builds on the content of Scientific Skills and Writing, with a focus on practical application.
Course SWS ECTS Practical Training Semester Practical Training Semester (22 weeks à 30 hours) 0 28 Practical Training Semester (22 weeks à 30 hours)
Module: Practical Training SemesterRoot module: Practical Training SemesterSemester: 5 Course code: PTS5BOPR Contact hours per week: 0 ECTS: 28Course Content:- Practical application of theory in the professional field
Practical Training Coaching Seminar 1 2 Practical Training Coaching Seminar
Module: Practical Training SemesterRoot module: Practical Training SemesterSemester: 5 Course code: PTCS5SE Contact hours per week: 1 ECTS: 2Course Content:- Supervision during the practical training through coordinator
- Preparing progress reports
- Preparing final reports
- Critical reflection on the practical training
Course SWS ECTS Data Science and Emerging Technologies Current Trends and Emerging Technologies 2 2 Current Trends and Emerging Technologies
Module: Data Science and Emerging TechnologiesRoot module: Data Science and Emerging TechnologiesSemester: 6 Course code: CTET6TU Contact hours per week: 2 ECTS: 2Course Content:- State-of-the-art outlook in emerging technology and new fields of application
- Examples of current trends in computer science: such as
- Blockchain applications and cryptocurrencies
- Social media analysis
- Autonomous computing
- Augmented Analytics
- Digital Ethics and Privacy
Course outcome:Upon completion of this course, students are able to:
- explain, analyze and critically discuss the technological trends that inform applications of computer and data science,
- discuss how companies and organizations can gain important insights and which new fields of applications can evolve with the help of new technologies and what opportunities and risks are involved.
Computer Science and Society Reflections on Computer Science, Society and Ethics 1 1 Reflections on Computer Science, Society and Ethics
Module: Computer Science and SocietyRoot module: Computer Science and SocietySemester: 6 Course code: RCSSE6TU Contact hours per week: 1 ECTS: 1Course Content:- subject areas related to the curriculum of the current semester are reviewed, critically analysed and discussed from ethical, cultural and sociological viewpoints by means of lectures and contributions from students
Course outcome:Upon completion of this course, students are able to:
- critically reflect on and discuss ethical, social and cultural aspects of information technology as framed by interdisciplinary overlaps,
- manage and moderate a critical discussion of ethical questions connected with informatics, data and related responsibilities, and formulate possible courses of action based on this discussion.
Elective 1: Business Process and Enterprise Technologies ERP-Consulting Customizing 3 6 Customizing
Module: ERP-ConsultingRoot module: Elective 1: Business Process and Enterprise TechnologiesSemester: 6 Course code: CST6ILV Contact hours per week: 3 ECTS: 6Course Content:- Practical project work in ERP-Consulting
- Adaptation and extension of existing modules, applications and implementations of an ERP system in JavaScript for a company / organization
- Review of Enterprise Architecture (EA) and Integration (EAI)
Course outcome:Upon completion of this course, students are able to:
- to conceptualize, design, implement and evaluate business processses within SAP in a practical project and explain their project to peers.
Data Transformation and Data Warehousing 3 3 Data Transformation and Data Warehousing
Module: ERP-ConsultingRoot module: Elective 1: Business Process and Enterprise TechnologiesSemester: 6 Course code: DTDW6ILV Contact hours per week: 3 ECTS: 3Course Content:- Practical project work in ERP-Consulting
- Data standardization and clearing
- Data mining for business applications
- Data transformation and storage technologies (ETL/extract-transform-load, schema on read/write, OLAP, OLTP)
- Enterprise Data Hubs (EDH) & Data Lakes (Hadoop)
Course outcome:Upon completion of this course, students are able to:
- explain the concepts, challenges and technologies related to the transformation and storage of enterprise data,
- assess data warehousing technologies and approaches,
- implement data extraction, transformation and clearing processes with ERP systems in a practical project.
Integrated Value Flows 2 3 Integrated Value Flows
Module: Elective 1: Business Process and Enterprise TechnologiesRoot module: Elective 1: Business Process and Enterprise TechnologiesSemester: 6 Course code: IVF6ILV Contact hours per week: 2 ECTS: 3Course Content:Based on general business administration and operational processes
- Value added and processes in ERP systems (purchasing, financial and cost accounting, production, distribution, logistics, cash management, taxes)
- Value chain / supply chain modelling and management
- Supply chain operations reference model (SCOR)
- Optional SAP Certification
Course outcome:Upon completion of this course, students are able to:
- relate general concepts related to value flows of ERP to their implementation in SAP,
- describe the value flows in ERP systems and within the supply chain in SAP,
- use SAP main modules (material management, finance, costs),
- evaluate and optimize value flows by implementing SAP general ledger in a real life example.
Business Application Integration 3 4 Business Application Integration
Module: Elective 1: Business Process and Enterprise TechnologiesRoot module: Elective 1: Business Process and Enterprise TechnologiesSemester: 6 Course code: BAI6VO Contact hours per week: 3 ECTS: 4Course Content:- Business application modelling
- Initiating and carrying out business processes
- Expense distribution & costing sheets review
- Information silos vs. integrated enterprise applications
- Integrating different applications (CRM, ERP, SCM, HR, BI, IoT and Customer Insights) using APIs and Middleware
- Mediation and federation patterns, topologies
- Adapters/connectors
- Optional SAP Certification
Course outcome:Upon completion of this course, students are able to:
- explain the concepts, challenges and technologies related to the integration of enterprise applications,
- utilize software development patterns and basic interfacing technologies to integrate business applications within ERP systems,
- collect and assess key performance indicators for given interfacing implementations.
Elective 2: Bio Informatics Image Processing and Visual Computing in Biology and Medicine Image Processing and Visual Computing in Biology and Medicine - Theory 2 2 Image Processing and Visual Computing in Biology and Medicine - Theory
Module: Image Processing and Visual Computing in Biology and MedicineRoot module: Elective 2: Bio InformaticsSemester: 6 Course code: S2_IPBMT6VO Contact hours per week: 2 ECTS: 2Course Content:- Introduction to visual computing
- Foundations of computer graphics & vision
- Digital image processing (image metrics, formats, sampling, filtering in spatial and frequency domains, compression)
- Foundations of augmented and virtual reality
- Imaging techniques in Biology and Medicine
- Image segmentation (active contours, level-set)
- Model-based processing of anatomical data
- Texture analysis
- Machine learning in neuroimaging (analysis, classification)
Course outcome:Upon completion of this course, students are able to:
- explain foundational concepts of visual computing,
- apply imaging techniques to visual datasets and utilize data science approaches to analyse them,
- relate the learned techniques and methodologies to practical problems in Bioinformatics.
- perform visual data preparation and processing in the domains of Biology and Medicine,
- apply data science techniques to analyse medical image data.
Image Processing and Visual Computing in Biology and Medicine - Exercise 1 2 Image Processing and Visual Computing in Biology and Medicine - Exercise
Module: Image Processing and Visual Computing in Biology and MedicineRoot module: Elective 2: Bio InformaticsSemester: 6 Course code: S2_IPBME6UE Contact hours per week: 1 ECTS: 2Course Content:- Accompanying practical exercises to the lecture “Image Processing and Visual Computing in Biology and Medicine - Theory”
- Practical exercises in medical image processing and analysis
Biological Foundations of Bio Informatics 2 3 Biological Foundations of Bio Informatics
Module: Elective 2: Bio InformaticsRoot module: Elective 2: Bio InformaticsSemester: 6 Course code: BFBI6VO Contact hours per week: 2 ECTS: 3Course Content:- Basics of general and organic chemistry
- Nucleic acids and proteins
- Genes and genomes
- Basics of cell biochemistry and bioenergetics
- Experimental techniques which generate big data for bioinformatics analysis: DNA microarrays, DNA sequencing, RNA sequencing, proteomics, metabolomics
Course outcome:Upon completion of this course, students are able to:
- explain the structure and function of bioinformatics-relevant biomolecules,
- explain the bioinformatics-relevant topics related to genes and genomes,
- discuss the crucial technologies for generating bioinformatics-relevant data,
- explain foundational concepts of physics, biology and chemistry.
Algorithms and Tools in Bio Informatics 2 3 Algorithms and Tools in Bio Informatics
Module: Elective 2: Bio InformaticsRoot module: Elective 2: Bio InformaticsSemester: 6 Course code: ATBI6ILV Contact hours per week: 2 ECTS: 3Course Content:- Algorithms and data structures in Bioinformatics:
- Sequence alignment algorithms
- Data structures in bioinformatics
- Suffix trees
- Gene expression profiling
- Gene prediction
- Data, tools and technologies in Bioinformatics:
- Standard data sets and –sources
- Introduction to software tools for bioinformatics
- Gene Prediction: ORF Finder, GeneScan
- Gene Expression Databases: GEO, ArrayExpress
Course outcome:Upon completion of this course, students are able to:
- describe foundational problems in Bioinformatics and relate them to their respective algorithmic techniques,
- select, curate and utilize standard datasets and resources,
- apply machine learning methods, tools and algorithms in the context of bio-informatics.
Big Data for Bioanalytics and Medicine 4 6 Big Data for Bioanalytics and Medicine
Module: Elective 2: Bio InformaticsRoot module: Elective 2: Bio InformaticsSemester: 6 Course code: BDBM6ILV Contact hours per week: 4 ECTS: 6Course Content:- Practical project work in Bio-Informatics
- Implement big data analysis projects based on provided raw data
- From data curation and preparation to analysis, interpretation and visualization
- Themes / topics:
- Next-Generation Sequencing Analysis
- RNA Sequencing Analysis
- Microarray / DNA Chip Analysis
- Analysis of Proteomics Data
- Personalized / predictive biomarkers
Course outcome:Upon completion of this course, students are able to:
- prepare and transform raw datasets from the domain of bioinformatics,
- analyse and interpret bioinformatics data through data science methods,
- visualize the results of data analysis to support interpretation,
- apply the learned work steps in a project and
- present the project results.
Research and Scientific Working Bachelor Seminar and Bachelor Paper 1 8 Bachelor Seminar and Bachelor Paper
Module: Research and Scientific WorkingRoot module: Research and Scientific WorkingSemester: 6 Course code: BPA6BASE Contact hours per week: 1 ECTS: 8Course Content:- Writing the bachelor paper, including project planning
- Topic-focused literature research
- Applying content-related and formal academic requirements
- Preparing the bachelor paper on the basis of the proposal
Course outcome:Upon completion of this course, students are able to:
- independently write an academic paper, in accordance with content-related and formal academic requirements
Bachelor Exam 0 2 Bachelor Exam
Module: Research and Scientific WorkingRoot module: Research and Scientific WorkingSemester: 6 Course code: BEX6AP Contact hours per week: 0 ECTS: 2Course Content:- Presentation of bachelor paper (and project )
- Oral examination on the bachelor paper (in accordance with section 16 Fachhochschul-Studiengesetz [University of Applied Sciences Studies Act]), and
- the links to related subjects on the curriculum (in accordance with section 16 University of Applied Sciences Studies Act)
Course outcome:In the bachelor exam, students demonstrate their ability to:- present their bachelor paper and the question they addressed in a manner appropriate to the target audience, and defend the paper before an expert committee,
- outline the significance of the findings for professional practice and research, and present supporting arguments and answer follow-up questions on degree-programme subjects and the links between them, and justify their answers
Social Skills Communication and Presentation Skills 1 1 Communication and Presentation Skills
Module: Social SkillsRoot module: Social SkillsSemester: 6 Course code: CPS6WK Contact hours per week: 1 ECTS: 1Course Content:- Verbal and non-verbal communication
- Seven phases of presentations
- Effective use of audio-visual media
- Handling difficult situations
- Storytelling
Course outcome:Upon completion of this course, students are able to:
- give a presentation for a particular target group, using a range of methods and media.
Besonderheiten
Warum sollten Sie sich für das Bachelor-Studium Informatics in Krems entscheiden?
Diese Branche macht die Zukunft
Informatik ist eine Disziplin, die wächst. Sie wird unser Leben noch stärker beeinflussen als sie das bereits jetzt tut. Denken wir an Wirtschaft, Umwelt oder Gesundheit – Informatik prägt alle Bereiche. Als Informatikerin oder Informatiker können Sie diese Entwicklung mitgestalten.
Da geht es nicht nur um technische, sondern auch um ethische und soziale Fragen. Denn Informatik beeinflusst das Arbeiten und Leben von Menschen. Vielleicht mehr als jede andere Branche.
Beste Karrierechancen
Eine Ausbildung in der Informatik legt den Grundstein für Ihre berufliche Laufbahn, nicht nur für einen Job. Nach dem Studium stehen Ihnen viele Möglichkeiten offen: Sie können in die Software Entwicklung gehen, sich auf informationsbasiertes Decision-Making spezialisieren oder auf IT-Consulting.
Sie sehen: Absolventinnen und Absolventen werden in vielen Bereichen sehr gefragt sein. Sowohl in Österreich als auch international. Darauf bereitet Sie auch die Unterrichtssprache Englisch vor.
Teil eines Teams sein
Das Tätigkeitsprofil von Informatikerinnen und Informatiker hat sich entwickelt, ebenso wie die Anforderungen an Hochschulabsolventinnen und -absolventen: Team- und Anwendungsorientierung stehen heute im Vordergrund. IT-Entwicklung orientiert sich heute oft an so genannten agilen Methoden - Entwicklerinnen und Entwickler arbeiten dabei stark eigenverantwortlich und oft in selbst-organisierenden Teams. Im Studiengang Informatics lernen Sie im Team Aufgaben zu lösen und neue Wege zu finden, um Information zu speichern, zu teilen und zu nützen. Weil Teamplayer die Zukunft gestalten.
Newsletter & Infomaterial
Zusätzliche Informationen gefällig? Abonnieren Sie Ihren personalisierten Newsletter oder bestellen Sie Broschüren über unsere Studiengänge direkt zu sich nach Hause.
Jetzt zusätzliche Informationen anfordernKompetenzbereiche
Nach Abschluss des Bachelor-Studiums Informatics verfügen Sie neben fundierten fachlichen und wissenschaftlichen Fähigkeiten auch über eine hohe praktische Kompetenz.
Sie lernen technische Werkzeuge und Software-Anwendungen zu entwickeln, darunter Algorithmen der künstlichen Intelligenz. Eine wesentliche Kompetenz ist auch der Umgang mit großen heterogenen Datenmengen, Stichwort Data Science. Absolventinnen und Absolventen können Daten in Echtzeit organisieren und daraus Informationen generieren und visualisieren.
Sie agieren Nutzerinnen- bzw. Nutzer-orientiert und denken über die Grenzen Ihres Fachgebiets hinaus. Das macht Sie besonders gefragt, wenn es um die Entwicklung von interdisziplinären Anwendungen geht (zum Beispiel biologische und wirtschaftliche Themenfelder).
Im Studium lernen Sie, berufsbezogene Forschungsfragen eigenständig zu bearbeiten. Dazu zählen der Umgang mit wissenschaftlicher Literatur, die Wahl von wissenschaftlichen Methoden, das Generieren von Ableitungen sowie das Formulieren und Begründen von Lösungen.
Kreative Teamplayer, fachlich kompetent und verantwortungsbewusst. Das sind genau die Absolventinnen und Absolventen, die wir uns wünschen – und die unsere Gesellschaft in Zeiten der automatisierten Datengenerierung dringend braucht. Denn es geht auch um ethische und gesellschaftliche Fragen, wenn wir von Informatik sprechen.
Karrierewege nach dem Bachelor-Studium Informatics
Als Informatikerin bzw. Informatiker sind viele Spezialisierungen und Tätigkeitfelder möglich.
Die Vorlesungssprache ist Englisch. Das bereitet Sie ideal auf Ihren Berufsalltag vor – egal, ob Sie eine nationale oder internationale Karriere anstreben. Interne Kommunikation, Kontakt mit Geschäftspartnerinnen und Geschäftspartner, sowie Kundinnen und Kunden – das alles findet heute in vielen Unternehmen und Organisationen auf Englisch statt.
Mit Ihrem Studium legen Sie nicht nur die fachliche, sondern auch die sprachliche Basis für einen gelungenen Einstieg ins Berufsleben bzw. einer Höherqualifizierung, wenn Sie bereits Berufserfahrung haben.
- Mögliche Arbeitsfelder
- Software Entwicklung: Frontend, Backend, Web für Kundinnen und Kunden sowie In-house
- Data Science: Datenerhebung, -säuberung, -analyse, und -interpretation für Kundinnen und Kunden sowie In-house
- IT Consulting: Beratung von Kundinnen und Kunden sowie Anpassung von Software-Lösungen
- Business Intelligence Engineering: Weiterentwicklung und Betrieb von ERP/DWH/BI-Systemen für und in Unternehmen
Es gibt viele Gründe, warum wir auf unsere Hochschule stolz sind. Finden Sie heraus, was uns besonders macht.
Was Krems besonders lebenswert macht? Lernen Sie Krems als Studierenden-Stadt kennen.
Von Studiumsorganisation bis Praktikums- und Berufsberatung. Informieren Sie sich über das Plus an Services.
Brauchen Sie Hilfe bei der Entscheidung fürs Studium? Unsere Studienberatung berät Sie gerne in einem persönlichen Gespräch.
Im Fokus: Informatics
Klicken Sie sich durch die Videos des Studiengangs.
Lernen Sie unsere Fachhochschule von einer ganz neuen und persönlichen Seite virtuell kennen.
Unser Team
Lernen Sie das Kern-Team des Bachelor-Studiengangs Informatics kennen.
Prof.(FH) Dipl. Ing. Dr. techn. Deepak Dhungana
Institutsleitung Digitalisierung und Informatik / Studiengangsleitung Informatics
Institut Digitalisierung und Informatik
- Software Engineering, Requirements Engineering, Software Architecture, Systems design- analysis and validation
- Adaptability and Flexiblilty in Systems design, Configuration and Re-configuration of systems, Product Line Engineering
- Data-driven Systems, Business Analytics and Monitoring, Industry 4.0
- InformaticsBachelor of Science in Engineering / Vollzeit
-
Kursplanung in modularen Schulsystemen
Department of Science & Technology
-
BRfit für Künstliche Intelligenz
Department of Business
-
Studie zum Schutz von Geschäftsgeheimnissen im Kontext der Data Economy
Department of Business
-
Museumspädagogik und Augmented Reality: Anerkennung von Museen als Bildungsräume
Projektleitung, Department of Science & Technology
-
UniLab - Von der Universität zum Arbeitsmarkt im 21. Jahrhundert: ein Schritt vorwärts in der Vermittlung von Praktikumsplätzen
Projektleitung, Department of Science & Technology
-
Digital Innovation Hub OST (DIHOST)
Department of Science & Technology
-
FLEXCRASH - Flexible und hybride Herstellung von grünem Aluminium zur Herstellung maßgeschneiderter adaptiver crashtoleranter Strukturen
Department of Science & Technology
Dhungana, D., Haselböck, A., Ruiz-Torrubiano, R., Wallner, S. (2022): Variability of safety risks in production environments. In Alexander Felfernig et. al. (Hrsg.), SPLC '22: Proceedings of the 26th ACM International Systems and Software Product Line Conference (178-187). Graz, Austria: Association for Computing Machinery.
Doi: https://doi.org/10.1145/3546932.3547074Bal, J., Dhungana, D., Karagiorgos, S., Mageirias, S., Pitnik, C., Vlachopoulos, D. (2021): MONA PROJECT: INTEGRATING MODERN TECHNOLOGIES IN MUSEUM EDUCATION. In Bal, J., Dhungana, D., Karagiorgos, S., Mageirias, S., Pitnik, C., Vlachopoulos, D. (Hrsg.), ICERI2021 Proceedings (8064-8070). -: Iated.
Doi: https://doi.org/10.21125/iceri.2021.1823Dhungana, D., Haselböck, A., Schmidbauer, C., Taupe, R., Wallner, S., (2021): Enabling Resilient Production Through Adaptive Human-Machine Task Sharing. In Andersen AL. et al. (Hrsg.), Towards Sustainable Customization: Bridging Smart Products and Manufacturing Systems. Cham: Springer.
Doi: https://doi.org/10.1007/978-3-030-90700-6_22Dhungana, D., Haselböck, A., Meixner, S., Schall, D., Schmid, J., Trabesinger, S., Wallner, S. (2021): Multi-factory production planning using edge computing and IIoT platforms. Journal of Systems and Software, 182(0164-1212).
Doi: https://doi.org/10.1016/j.jss.2021.111083Pfiel, S., Lovasz-Bukvova, H., Tiefenbacher, F., Hopp, M., Schuster, R., Reiner, M., Dhungana, D. (2021): Virtual Reality Applications for Experiential Tourism - Curator Application for Museum Visitors. In Yilmaz, M., Clarke, P., Messnarz, R., Reiner, M. (Hrsg.), Systems, Software and Services Process Improvement (716ff). Krems: Springer.
Doi: https://doi.org/10.1007/978-3-030-85521-5_49Hage R., Lovasz-Bukvova, H., Hopp, M., Hölzl, M., Kormann-Hainzl G., Reiner, M., Dhungana, D. (2021): Agile Approach for E-Learning in Digital-Leadership Training for Small and Medium Enterprises. In Softic, S.K., Read, T. (Hrsg.), Proceedings of the EDEN Annual Conference: Lessons Learned from the Pandemic. Madrid: EDEN.
Grünbacher, P., Seidl, C., Dhungana, D., Lovasz-Bukvova, H. (Hrsg.). (2021): VaMoS'21: 15th International Working Conference on Variability Modelling of Software-Intensive Systems, Virtual Event / Krems, Austria, February 9-11, 2021. Krems: ACM.
Doi: https://doi.org/10.1145/3442391Dhungana, D., Haelböck, A., Wallner, S. (2020): Generation of Multi-factory Production Plans: Enabling Collaborative Lot-size-one Production. In - (Hrsg.), Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2020 (529-536). Portoroz, Slovenia: IEEE.
Doi: https://doi.org/10.1109/SEAA51224.2020.00088Dhungana, D. (2018): Customer Co-Creation in Smart Production Ecosystems - Opportunities and Challenges for MDE. In Hammoudi, S., Ferreira Pires, L., Selic, B. (Hrsg.), Proceedings of the 6th International Conference on Model-Driven Engineering and Software Development - Volume 1: IndTrackMODELSWARD (625-631). Funchal, Madeira, Portugal: SciTePress.
Doi: https://doi.org/10.5220/0006731206250631Dhungana, D., Falkner, A., Haselböck, A., Taupe, R. (2017): Enabling Integrated Product and Factory Configuration in Smart Production Ecosystems. In - (Hrsg.), 43rd Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2017, Vienna, Austria, August 30 - Sept. 1, 2017 (266-273). Vienna, Austria: IEEE Computer Society.
Doi: https://doi.org/10.1109/SEAA.2017.26Dhungana, D., Engelbrecht, G., Parreira, J., Schuster, A., Tobler, R., Valerio, D. (2016): Data-driven ecosystems in smart cities: A living example from Seestadt Aspern. In - (Hrsg.), 3rd IEEE World Forum on Internet of Things, WF-IoT 2016, Reston, VA, USA, December 12-14, 2016 (82-87). Reston, VA, USA: IEEE Computer Society.
Doi: https://doi.org/10.1109/WF-IoT.2016.7845434Dhungana, D., Engelbrecht, G., Parreira, J., Schuster, A., Valerio, D. (2015): Aspern smart ICT: Data analytics and privacy challenges in a smart city. In - (Hrsg.), 2nd IEEE World Forum on Internet of Things, WF-IoT 2015, Milan, Italy, December 14-16, 2015 (447-452). Milan, Italy: IEEE Computer Society.
Doi: https://doi.org/10.1109/WF-IoT.2015.7389096Dhungana, D., Falkner, A., Haselböck, A., Schreiner, H. (2015): Smart factory product lines: a configuration perspective on smart production ecosystems. In Schmidt, D. (Hrsg.), Proceedings of the 19th International Conference on Software Product Line, SPLC 2015, Nashville, TN, USA, July 20-24, 2015 (201-210). Nashville, TN, USA: ACM.
Doi: https://doi.org/10.1145/2791060.2791066Galindo, J., Dhungana, D., Rabiser, R., Benavides, D., Botterweck, G., Grünbacher, P. (2015): Supporting distributed product configuration by integrating heterogeneous variability modeling approaches. Inf. Softw. Technol., 62: 78-100.
Doi: https://doi.org/10.1016/j.infsof.2015.02.002Parreira, J., Dhungana, D., Engelbrecht, G. (2015): The Role of RDF Stream Processing in an Smart City ICT Infrastructure - The Aspern Smart City Use Case. In Gandon, F., Gueret, C., Villata, S., Breslin, J., Faron-Zucker, C., Zimmermann, A. (Hrsg.), The Semantic Web: ESWC 2015 Satellite Events - ESWC 2015 Satellite Events Portorovz, Slovenia, May 31 - June 4, 2015, Revised Selected Papers (343-352). Portorovz, Slovenia: Springer.
Doi: https://doi.org/10.1007/978-3-319-25639-9\_47Gnesi, S., Heymans, P., Rubin, J., Czarnecki, K., Dhungana, D., Fantechi, A. (Hrsg.). (2014): Proceedings of 18th International Software Product Line Conference, SPLC 14. New York, USA: ACM.
Doi: https://doi.org/10.1145/2648511Rabiser, R., Vierhauser, M., Grünbacher, P., Dhungana, D., Schreiner, H., Lehofer, M. (2014): Supporting Multiplicity and Hierarchy in Model-Based Configuration: Experiences and Lessons Learned. In Dingel, J., Schulte, W., Ramos, I., Abrahao, S., Insfran, E. (Hrsg.), Model-Driven Engineering Languages and Systems - 17th International Conference, MODELS 2014, Valencia, Spain, September 28 - October 3, 2014. Proceedings (320-336). Valencia, Spain: Springer.
Doi: https://doi.org/10.1007/978-3-319-11653-2\_20Dhungana, D., Schreiner, H., Lehofer, M., Vierhauser, M., Rabiser, R., Grünbacher, P. (2014): Modeling multiplicity and hierarchy in product line architectures: extending a decision-oriented approach. In Liu, A., Klein, J., Tang, A. (Hrsg.), Proceedings of the WICSA 2014 Companion Volume, Sydney, NSW, Australia, April 7-11, 2014 (11:1-11:6). Sydney, NSW, Australia: ACM.
Doi: https://doi.org/10.1145/2578128.2578236Dhungana, D., Hoo Tang, C., Weidenbach, C., Wischnewski, P. (2013): Automated Verification of Interactive Rule-Based Configuration Systems (Additional Material). CoRR, abs/1309.0065.
Doi: https://doi.org/10.1109/ASE.2013.6693112Dhungana, D., Hoo Tang, C., Weidenbach, C., Wischnewski, P. (2013): Automated verification of interactive rule-based configuration systems. In Denney, E., Bultan, T., Zeller, A. (Hrsg.), 2013 28th IEEE/ACM International Conference on Automated Software Engineering, ASE 2013, Silicon Valley, CA, USA, November 11-15, 2013 (551-561). Silicon Valley, CA, USA: IEEE.
Doi: https://doi.org/10.1109/ASE.2013.6693112Dhungana, D., Falkner, A., Haselböck, A. (2013): Generation of conjoint domain models for system-of-systems. In Järvi, J., Kästner, C. (Hrsg.), Generative Programming: Concepts and Experiences, GPCE13, Indianapolis, IN, USA - October 27 - 28, 2013 (159-168). Indianapolis, IN, USA: ACM.
Doi: https://doi.org/10.1145/2517208.2517224Botterweck, G., Dhungana, D., Noda, N., Rabiser, R., Washizaki, H. (2013): Joint Workshop of the 5th International Workshop on Model-Driven Approaches in Software Product Line Engineering and the 4th Workshop on Scalable Modeling Techniques for Software Product Lines (MAPLE/SCALE 2013). In Kishi, T., Jarzabek, S., Gnesi, S. (Hrsg.), 17th International Software Product Line Conference, SPLC 2013, Tokyo, Japan - August 26 - 30, 2013 (268). Tokyo, Japan: ACM.
Doi: https://doi.org/10.1145/2491627.2499881Dhungana, D., Seichter, D., Botterweck, G., Rabiser, R., Grünbacher, P., Benavides, D., Galindo, J. (2013): Integrating heterogeneous variability modeling approaches with invar. In Gnesi, S., Collet, P., Schmid, K. (Hrsg.), The Seventh International Workshop on Variability Modelling of Software-intensive Systems, VaMoS 13, Pisa , Italy, January 23 - 25, 2013 (8:1-8:5). Pisa, Italy: ACM.
Doi: https://doi.org/10.1145/2430502.2430514Pleuss, A., Botterweck, G., Dhungana, D., Polzer, A., Kowalewski, S. (2012): Model-driven support for product line evolution on feature level. J. Syst. Softw., 85(10): 2261-2274.
Doi: https://doi.org/10.1016/j.jss.2011.08.008Nöbauer, N., Seyff, N., Groher, I., Dhungana, D. (2012): A Lightweight Approach for Product Line Scoping. In Cortellessa, V., Muccini, H., Demirörs, O. (Hrsg.), 38th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2012, Cesme, Izmir, Turkey, September 5-8, 2012 (105-108). Cesme, Izmir, Turkey: IEEE Computer Society.
Doi: https://doi.org/10.1109/SEAA.2012.81Botterweck, G., Dhungana, D., Rabiser, R. (2012): Fourth International Workshop on Model-driven Approaches in Software Product Line Engineering (MAPLE 2012). In Eduardo Santana de Almeida and Christa Schwanninger and David Benavides (Hrsg.), 16th International Software Product Line Conference, SPLC 12, Salvador, Brazil - September 2-7, 2012, Volume 1 (288-289). Salvador, Brazil: ACM.
Doi: https://doi.org/10.1145/2362536.2362577Pleuss, A., Hauptmann, B., Dhungana, D., Botterweck, G. (2012): User interface engineering for software product lines: the dilemma between automation and usability. In Diniz Junqueira Barbosa, S., Creissac Campos, J., Kazman, R., Palanque, P., Harrison, M., Reeves, S. (Hrsg.), ACM SIGCHI Symposium on Engineering Interactive Computing Systems, EICS12, Copenhagen, Denmark - June 25 - 28, 2012 (25-34). Copenhagen, Denmark: ACM.
Doi: https://doi.org/10.1145/2305484.2305491Nöbauer, M., Seyff, N., Dhungana, D., Stoiber, R. (2012): Managing variability of ERP ecosystems: research issues and solution ideas from Microsoft Dynamics AX. In Eisenecker, U., Apel, S., Gnesi, S. (Hrsg.), Sixth International Workshop on Variability Modelling of Software-Intensive Systems, Leipzig, Germany, January 25-27, 2012. Proceedings (21-26). Leipzig, Germany: ACM.
Doi: https://doi.org/10.1145/2110147.2110150Danar Sunindyo, W., Moser, T., Winkler, D., Dhungana, D. (2012): Improving Open Source Software Process Quality Based on Defect Data Mining. In Biffl, S., Winkler, D., Bergsmann, J. (Hrsg.), Software Quality. Process Automation in Software Development - 4th International Conference, SWQD 2012, Vienna, Austria, January 17-19, 2012. Proceedings (84-102). Vienna, Austria: Springer.
Doi: https://doi.org/10.1007/978-3-642-27213-4\_7Beecham, S., Noll, J., Richardson, I., Dhungana, D. (2011): A Decision Support System for Global Software Development. In - (Hrsg.), 6th IEEE International Conference on Global Software Engineering, ICGSE 2011, Workshop Proceedings, Helsinki, Finland, August 15-18, 2011 (48-53). Helsinki, Finland: IEEE Computer Society.
Doi: https://doi.org/10.1109/ICGSE-W.2011.20Dhungana, D., Falkner, A., Haselböck, A. (2011): Configuration of Cardinality-Based Feature Models Using Generative Constraint Satisfaction. In - (Hrsg.), 37th EUROMICRO Conference on Software Engineering and Advanced Applications, SEAA 2011, Oulu, Finland, August 30 - September 2, 2011 (100-103). Oulu, Finland: IEEE Computer Society.
Doi: https://doi.org/10.1109/SEAA.2011.24Dhungana, D., Seichter, D., Botterweck, G., Rabiser, R., Grünbacher, P., Benavides, D., Galindo, J. (2011): Configuration of Multi Product Lines by Bridging Heterogeneous Variability Modeling Approaches. In Santana de Almeida, E., Kishi, T., Schwanninger, C., John, I., Schmid, K. (Hrsg.), Software Product Lines - 15th International Conference, SPLC 2011, Munich, Germany, August 22-26, 2011 (120-129). Munich, Germany: IEEE Computer Society.
Doi: https://doi.org/10.1109/SPLC.2011.22Botterweck, G., Noda, N., Dhungana, D., Rabiser, R., Babar, M., Cohen, S., Kang, C., Kishi, T. (2011): Joint Workshop of the Third International Workshop on Model-Driven Approaches in Software Product Line Engineering and the Third Workshop on Scalable Modeling Techniques for Software Product Lines (MAPLE/SCALE 2011). In Santana de Almeida, E., Kishi, T., Schwanninger, C., John, I., Schmid, K. (Hrsg.), Software Product Lines - 15th International Conference, SPLC 2011, Munich, Germany, August 22-26, 2011 (340). Munich, Germany: IEEE Computer Society.
Doi: https://doi.org/10.1109/SPLC.2011.42Franch, X., Grünbacher, P., Oriol, M., Burgstaller, B., Dhungana, D., Lopez, L., Marco, J., Pimentel, J. (2011): Goal-Driven Adaptation of Service-Based Systems from Runtime Monitoring Data. In - (Hrsg.), Workshop Proceedings of the 35th Annual IEEE International Computer Software and Applications Conference, COMPSAC Workshops 2011, Munich, Germany, 18-22 July 2011 (458-463). Munich, Germany: IEEE Computer Society.
Doi: https://doi.org/10.1109/COMPSACW.2011.83Mordinyi, R., Moser, T., Biffl, S., Dhungana, D. (2011): Flexible Support for Adaptable Software and Systems Engineering Processes. In - (Hrsg.), Proceedings of the 23rd International Conference on Software Engineering & Knowledge Engineering (SEKE2011), Eden Roc Renaissance, Miami Beach, USA, July 7-9, 2011 (608-612). Miami Beach, USA: Knowledge Systems Institute Graduate School.
Dhungana, D., Seyff, N., Graf, F. (2011): Research Preview: Supporting End-User Requirements Elicitation Using Product Line Variability Models. In Berry, D., Franch, X. (Hrsg.), Requirements Engineering: Foundation for Software Quality - 17th International Working Conference, REFSQ 2011, Essen, Germany, March 28-30, 2011. Proceedings (66-71). Essen, Germany: Springer.
Doi: https://doi.org/10.1007/978-3-642-19858-8\_8Dhungana, D., Grünbacher, P., Rabiser, R. (2011): The DOPLER meta-tool for decision-oriented variability modeling: a multiple case study. Autom. Softw. Eng., 18(1): 77-114.
Doi: https://doi.org/10.1007/s10515-010-0076-6Thiel, S., Rabiser, R., Dhungana, D., Cawley, C. (2010): 3rd International Workshop on Visualisation in Software Product Line Engineering (VISPLE 2010). In Bosch, J., Lee, J. (Hrsg.), Software Product Lines: Going Beyond - 14th International Conference, SPLC 2010, Jeju Island, South Korea, September 13-17, 2010. Proceedings (527). Jeju Island, South Korea: Springer.
Doi: https://doi.org/10.1007/978-3-642-15579-6\_65Dhungana, D., Rabiser, R., Seyff, N., Botterweck, G. (Hrsg.). (2010): Proceedings of the 1st International Workshop on Automated Configuration and Tailoring of Applications. Antwerp, Belgium: CEUR-WS.org.
Dhungana, D., Groher, I., Rabiser, R., Thiel, S. (2010): 2nd International Workshop on Model-Driven Approaches in Software Product Line Engineering (MAPLE 2010). In Bosch, J., Lee, J. (Hrsg.), Software Product Lines: Going Beyond - 14th International Conference, SPLC 2010, Jeju Island, South Korea, September 13-17, 2010. Proceedings (525). Jeju Island, South Korea: Springer.
Doi: https://doi.org/10.1007/978-3-642-15579-6\_63Dhungana, D., Groher, I., Schludermann, E., Biffl, S. (2010): Software ecosystems vs. natural ecosystems: learning from the ingenious mind of nature. In Gorton, I., Cuesta, C., Babar, M. (Hrsg.), Software Architecture, 4th European Conference, ECSA 2010, Copenhagen, Denmark, August 23-26, 2010. Companion Volume (96-102). Copenhagen, Denmark: ACM.
Doi: https://doi.org/10.1145/1842752.1842777Seichter, D., Dhungana, D., Pleuss, A., Hauptmann, B. (2010): Knowledge management in software ecosystems: software artefacts as first-class citizens. In Gorton, I., Cuesta, C., Babar, M. (Hrsg.), Software Architecture, 4th European Conference, ECSA 2010, Copenhagen, Denmark, August 23-26, 2010. Companion Volume (119-126). Copenhagen, Denmark: ACM.
Doi: https://doi.org/10.1145/1842752.1842780Heider, W., Froschauer, R., Grünbacher, P., Rabiser, R., Dhungana, D. (2010): Simulating evolution in model-based product line engineering. Inf. Softw. Technol., 52(7): 758-769.
Doi: https://doi.org/10.1016/j.infsof.2010.03.007Dhungana, D., Grünbacher, P., Rabiser, R., Neumayer, T. (2010): Structuring the modeling space and supporting evolution in software product line engineering. J. Syst. Softw., 83(7): 1108-1122.
Doi: https://doi.org/10.1016/j.jss.2010.02.018Botterweck, G., Pleuss, A., Dhungana, D., Polzer, A., Kowalewski, S. (2010): EvoFM: feature-driven planning of product-line evolution. In Rubin, J., Botterweck, G., Mezini, M., Maman, I., Pleuss, A. (Hrsg.), Proceedings of the 2010 ICSE Workshop on Product Line Approaches in Software Engineering, PLEASE 2010, Cape Town, South Africa, May 2, 2010 (24-31). Cape Town, South Africa: ACM.
Doi: https://doi.org/10.1145/1808937.1808941Rabiser, R., Grünbacher, P., Dhungana, D. (2010): Requirements for product derivation support: Results from a systematic literature review and an expert survey. Inf. Softw. Technol., 52(3): 324-346.
Doi: https://doi.org/10.1016/j.infsof.2009.11.001Dhungana, D., Heymans, P., Rabiser, R. (2010): A Formal Semantics for Decision-oriented Variability Modeling with DOPLER. In Benavides, D., Batory, D., Grünbacher, P. (Hrsg.), Fourth International Workshop on Variability Modelling of Software-Intensive Systems, Linz, Austria, January 27-29, 2010. Proceedings (29-35). Linz, Austria: Universität Duisburg-Essen.
Pleuss, A., Botterweck, G., Dhungana, D. (2010): Integrating Automated Product Derivation and Individual User Interface Design. In Benavides, D., Batory, D., Grünbacher, P. (Hrsg.), Fourth International Workshop on Variability Modelling of Software-Intensive Systems, Linz, Austria, January 27-29, 2010. Proceedings (69-76). Linz, Austria: Universität Duisburg-Essen.
Vierhauser, M., Dhungana, D., Heider, W., Rabiser, R., Egyed, A. (2010): Tool Support for Incremental Consistency Checking on Variability Models. In Benavides, D., Batory, D., Grünbacher, P. (Hrsg.), Fourth International Workshop on Variability Modelling of Software-Intensive Systems, Linz, Austria, January 27-29, 2010. Proceedings (171-174). Linz, Austria: Universität Duisburg-Essen.
Rabiser, R., Dhungana, D., Heider, W., Grünbacher, P. (2009): Flexibility and End-User Support in Model-Based Product Line Tools. In - (Hrsg.), 35th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2009, Patras, Greece, August 27-29, 2009, Proceedings (508-511). Patras, Greece: IEEE Computer Society.
Doi: https://doi.org/10.1109/SEAA.2009.13Grünbacher, P., Rabiser, R., Dhungana, D., Lehofer, M. (2009): Model-Based Customization and Deployment of Eclipse-Based Tools: Industrial Experiences. In - (Hrsg.), ASE 2009, 24th IEEE/ACM International Conference on Automated Software Engineering, Auckland, New Zealand, November 16-20, 2009 (247-256). Auckland, New Zealand: IEEE Computer Society.
Doi: https://doi.org/10.1109/ASE.2009.11Heider, W., Rabiser, R., Dhungana, D., Grünbacher, P. (2009): Tracking Evolution in Model-based Product Lines. In Botterweck, G., Groher, I., Polzer, A., Schwanninger, C., Thiel, S., Voelter, M. (Hrsg.), Proceedings of the 1st International Workshop on Model-driven Approaches in Software Product Line Engineering (MAPLE 2009), collocated with the 13th International Software Product Line Conference (SPLC 2009), San Francisco, USA, August 24, 2009. San Francisco, USA: CEUR-WS.org.
Dhungana, D., Groher, I. (2009): Genetics as a role model for software variability management. In - (Hrsg.), 31st International Conference on Software Engineering, ICSE 2009, May 16-24, 2009, Vancouver, Canada, Companion Volume (239-242). Vancouver, Canada: IEEE.
Doi: https://doi.org/10.1109/ICSE-COMPANION.2009.5070991Grünbacher, P., Rabiser, R., Dhungana, D., Lehofer, M. (2009): Structuring the Product Line Modeling Space: Strategies and Examples. In Benavides, D., Metzger, A., Eisenecker, U. (Hrsg.), Third International Workshop on Variability Modelling of Software-Intensive Systems, Seville, Spain, January 28-30, 2009. Proceedings (77-82). Seville, Spain: Universität Duisburg-Essen.
Wolfinger, R., Reiter, S., Dhungana, D., Grünbacher, P., Prähofer, H. (2008): Supporting Runtime System Adaptation through Product Line Engineering and Plug-in Techniques. In - (Hrsg.), Seventh International Conference on Composition-Based Software Systems (ICCBSS 2008), February, 25-29, 2008, Madrid, Spain, Proceedings (21-30). Madrid, Spain: IEEE Computer Society.
Doi: https://doi.org/10.1109/ICCBSS.2008.30Grünbacher, P., Rabiser, R., Dhungana, D. (2008): Product Line Tools are Product Lines Too: Lessons Learned from Developing a Tool Suite. In - (Hrsg.), 23rd IEEE/ACM International Conference on Automated Software Engineering (ASE 2008), 15-19 September 2008, LAquila, Italy (351-354). LAquila, Italy: IEEE Computer Society.
Doi: https://doi.org/10.1109/ASE.2008.46Froschauer, R., Dhungana, D., Grünbacher, P. (2008): Managing the Life-cycle of Industrial Automation Systems with Product Line Variability Models. In - (Hrsg.), 34th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2008, September 3-5, 2008, Parma, Italy (35-42). Parma, Italy: IEEE Computer Society.
Doi: https://doi.org/10.1109/SEAA.2008.21Dhungana, D., Neumayer, T., Grünbacher, P., Rabiser, R. (2008): Supporting Evolution in Model-Based Product Line Engineering. In - (Hrsg.), Software Product Lines, 12th International Conference, SPLC 2008, Limerick, Ireland, September 8-12, 2008, Proceedings (319-328). Limerick, Ireland: IEEE Computer Society.
Doi: https://doi.org/10.1109/SPLC.2008.26Dhungana, D., Neumayer, T., Grünbacher, P., Rabiser, R. (2008): Supporting the Evolution of Product Line Architectures with Variability Model Fragments. In - (Hrsg.), Seventh Working IEEE / IFIP Conference on Software Architecture (WICSA 2008), 18-22 February 2008, Vancouver, BC, Canada (327-330). Vancouver, BC, Canada: IEEE Computer Society.
Doi: https://doi.org/10.1109/WICSA.2008.23Froschauer, R., Dhungana, D., Grünbacher, P. (2008): Runtime Adaptation of IEC 61499 Applications Using Domain-specific Variability Models. In Thiel, S., Pohl, K. (Hrsg.), Software Product Lines, 12th International Conference, SPLC 2008, Limerick, Ireland, September 8-12, 2008, Proceedings. Second Volume (Workshops) (39-44). Limerick, Ireland: Lero Int. Science Centre, University of Limerick, Ireland.
Dhungana, D., Grünbacher, P. (2008): Understanding Decision-Oriented Variability Modelling. In Thiel, S., Pohl, K. (Hrsg.), Software Product Lines, 12th International Conference, SPLC 2008, Limerick, Ireland, September 8-12, 2008, Proceedings. Second Volume (Workshops) (233-242). Limerick, Ireland: Lero Int. Science Centre, University of Limerick, Ireland.
Clotet, R., Dhungana, D., Franch, X., Grünbacher, P., Lopez, L., Marco, J., Seyff, N. (2008): Dealing with Changes in Service-Oriented Computing Through Integrated Goal and Variability Modelling. In Heymans, P., Kang, K., Metzger, A., Pohl, K. (Hrsg.), Second International Workshop on Variability Modelling of Software-Intensive Systems, Universität Duisburg-Essen, Germany, January 16-18, 2008, Proceedings (43-52). Duisburg-Essen, Germany: ICB.
Doi: https://doi.org/10.17185/duepublico/47116Rabiser, R., Dhungana, D., Grünbacher, P., Burgstaller, B (2008): Value-Based Elicitation of Product Line Variability: An Experience Report. In Heymans, P., Kang, K., Metzger, A., Pohl, K. (Hrsg.), Second International Workshop on Variability Modelling of Software-Intensive Systems, Universität Duisburg-Essen, Germany, January 16-18, 2008, Proceedings (73-79). Duisburg-Essen, Germany: ICB.
Doi: https://doi.org/10.17185/duepublico/47116Sinz, C., Haag, A., Narodytska, N., Walsh, T., Gelle, E., Sabin, M., Junker, U., OSullivan, B., Rabiser, R., Dhungana, D., Grünbacher, P., Lehner, K., Federspiel, C., Naus, D. (2007): Configuration. IEEE Intelligent Systems, 22(1): 78-90.
Doi: https://doi.org/10.1109/MIS.2007.6Rabiser, R., Dhungana, D., Grünbacher, P., Lehner, K., Federspiel, C. (2007): Involving Non-Technicians in Product Derivation and Requirements Engineering: A Tool Suite for Product Line Engineering. In - (Hrsg.), 15th IEEE International Requirements Engineering Conference, RE 2007, October 15-19th, 2007, New Delhi, India (367-368). New Delhi, India: IEEE Computer Society.
Doi: https://doi.org/10.1109/RE.2007.26Rabiser, R., Grünbacher, P., Dhungana, D. (2007): Supporting Product Derivation by Adapting and Augmenting Variability Models. In - (Hrsg.), Software Product Lines, 11th International Conference, SPLC 2007, Kyoto, Japan, September 10-14, 2007, Proceedings (141-150). Kyoto, Japan: IEEE Computer Society.
Doi: https://doi.org/10.1109/SPLINE.2007.22Dhungana, D., Rabiser, R., Grünbacher, P. (2007): Decision-Oriented Modeling of Product Line Architectures. In - (Hrsg.), Sixth Working IEEE / IFIP Conference on Software Architecture (WICSA 2007), 6-9 January 2005, Mumbai, Maharashtra, India (22). Mumbai, Maharashtra, India: IEEE Computer Society.
Doi: https://doi.org/10.1109/WICSA.2007.21Rabiser, R., Dhungana, D. (2007): Integrated Support for Product Configuration and Requirements Engineering in Product Derivation. In - (Hrsg.), 33rd EUROMICRO Conference on Software Engineering and Advanced Applications (EUROMICRO-SEAA 2007), August 28-31, 2007, Lübeck, Germany (219-228). Lübeck, Germany: IEEE Computer Society.
Doi: https://doi.org/10.1109/EUROMICRO.2007.36Dhungana, D., Rabiser, R., Grünbacher, P., Neumayer, T. (2007): Integrated tool support for software product line engineering. In Stirewalt, R., Egyed, A., Fischer, B. (Hrsg.), 22nd IEEE/ACM International Conference on Automated Software Engineering (ASE 2007), November 5-9, 2007, Atlanta, Georgia, USA (533-534). Atlanta, Georgia, USA: ACM.
Doi: https://doi.org/10.1145/1321631.1321730Dhungana, D., Grünbacher, P., Rabiser, R. (2007): Domain-specific Adaptations of Product Line Variability Modeling. In Ralyte, J., Brinkkemper, S., Henderson-Sellers, B. (Hrsg.), Situational Method Engineering: Fundamentals and Experiences, Proceedings of the IFIP WG 8.1 Working Conference, 12-14 September 2007, Geneva, Switzerland (238-251). Geneva, Switzerland: Springer.
Doi: https://doi.org/10.1007/978-0-387-73947-2\_19Rabiser, R., Dhungana, D., Grünbacher, P. (2007): Tool Support for Product Derivation in Large-Scale Product Lines: A Wizard-based Approach. In - (Hrsg.), Software Product Lines, 11th International Conference, SPLC 2007, Kyoto, Japan, September 10-14, 2007, Proceedings. Second Volume (Workshops) (119-124). Kyoto, Japan: Kindai Kagaku Sha Co. Ltd., Tokyo, Japan.
Dhungana, D., Rabiser, R., Grünbacher, P., Lehner, K., Federspiel, C. (2007): DOPLER: An Adaptable Tool Suite for Product Line Engineering. In - (Hrsg.), Software Product Lines, 11th International Conference, SPLC 2007, Kyoto, Japan, September 10-14, 2007, Proceedings. Second Volume (Workshops) (151-152). Kyoto, Japan: Kindai Kagaku Sha Co. Ltd., Tokyo, Japan.
Doi: https://doi.org/10.1007/s10515-010-0076-6Dhungana, D., Grünbacher, P., Rabiser, R. (2007): DecisionKing: A Flexible and Extensible Tool for Integrated Variability Modeling. In Pohl, K., Heymans, P., Kang, K., Metzger, A. (Hrsg.), First International Workshop on Variability Modelling of Software-Intensive Systems, VaMoS 2007, Limerick, Ireland, January 16-18, 2007. Proceedings (119-127). Limerick, Ireland: -.
Dhungana, D., Rabiser, R., Grünbacher, P., Prähofer, H., Federspiel, Ch., Lehner, K. (2006): Architectural Knowledge in Product Line Engineering: An Industrial Case Study. In - (Hrsg.), 32nd EUROMICRO Conference on Software Engineering and Advanced Applications (EUROMICRO-SEAA 2006), August 29 - September 1, 2006, Cavtat/Dubrovnik, Croatia (186-197). Cavtat, Croatia: IEEE Computer Society.
Doi: https://doi.org/10.1109/EUROMICRO.2006.21Dhungana, D. (2006): Integrated Variability Modeling of Features and Architecture in Software Product Line Engineering. In - (Hrsg.), 21st IEEE/ACM International Conference on Automated Software Engineering (ASE 2006), 18-22 September 2006, Tokyo, Japan (327-330). Tokyo, Japan: IEEE Computer Society.
Doi: https://doi.org/10.1109/ASE.2006.42Wolfinger, R., Dhungana, D., Prähofer, H., Mössenböck, H. (2006): A Component Plug-In Architecture for the .NET Platform. In Lightfoot, D., Szyperski, C. (Hrsg.), Modular Programming Languages, 7th Joint Modular Languages Conference, JMLC 2006, Oxford, UK, September 13-15, 2006, Proceedings (287-305). Berlin Heidelberg: Springer.
Doi: https://doi.org/10.1007/11860990\_18
Prof.(FH) Dipl. Ing. Dr. techn. Deepak DhunganaInstitutsleitung Digitalisierung und Informatik / Studiengangsleitung InformaticsInstitutsleitung Digitalisierung und Informatik / Studiengangsleitung Informatics
Prof.(FH) Dipl. Ing. Dr. techn. Deepak Dhungana
Kernkompetenzen
- Software Engineering, Requirements Engineering, Software Architecture, Systems design- analysis and validation
- Adaptability and Flexiblilty in Systems design, Configuration and Re-configuration of systems, Product Line Engineering
- Data-driven Systems, Business Analytics and Monitoring, Industry 4.0
Mag.(FH) Nicolas Aron
Corporate Relations / Department of Business
Corporate Relations
- Unternehmensführung
- Personalentwicklung
- Praktikumsbetreuung - Unternehmensführung (BA), Informatics (BA), Betriebswirtschaft für das Gesundheitswesen (BA), Business Administration (BA), Marketing (MA)
- Betriebswirtschaft für das GesundheitswesenBachelor of Arts in Business / Vollzeit
- Business AdministrationBachelor of Arts in Business / Vollzeit
- InformaticsBachelor of Science in Engineering / Vollzeit
- Tourism and Leisure ManagementBachelor of Arts in Business / Vollzeit
Mag.(FH) Nicolas AronCorporate Relations / Department of BusinessAlessio Gambi, PhD
Senior Lecturer Institut Digitalisierung und Informatik
Institut Digitalisierung und Informatik
- Automatisierte Softwarequalität
- Cloud computing
- Selbstanpassende und autonome Systeme
- InformaticsBachelor of Science in Engineering / Vollzeit
-
FLEXCRASH - Flexible und hybride Herstellung von grünem Aluminium zur Herstellung maßgeschneiderter adaptiver crashtoleranter Strukturen
Projektleitung, Department of Science & Technology
Birchler, Ch., Khatiri, S., Bosshard, B., Gambi, A., Panichella, S. (2023): Machine learning-based test selection for simulation-based testing of self-driving cars software. Empirical Software Engineering.
Doi: https://doi.org/10.1007/s10664-023-10286-yZohdinasab, T., Riccio, V., Gambi, A., Tonella, P. (2023): DeepHyperion: Exploring the Feature Space of Deep Learning-based Systems through Illumination Search. In Engels, G., Hebig, R., Tichy, M. (Hrsg.), Software Engineering 2023 (131-132). online: Gesellschaft für Informatik.
Devroey, X., Gambi, A., Galeotti, J.P., Just, R., Kifetew, F., Panichella, A., Panichella, S. (2022): JUGE: An infrastructure for benchmarking Java unit test generators. Journal of Software Testing, Verification & Reliability , 33(3).
Doi: https://doi.org/10.1002/stvr.1838Birchler, Ch., Ganz, N., Khatiri, S., Gambi, A., Panichella, S. (2022): Cost-effective simulation-based Test Selection in Self-driving cars software with SDC-Scissor. In Birchler, Ch., Ganz, N., Khatiri, S., Gambi, A., Panichella, S. (Hrsg.), 2022 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER) (164-168). New York: Institute of Electrical and Electronics Engineers.
Doi: https://doi.org/10.1109/SANER53432.2022.00030Gambi, A., Jahangirova, G., Riccio, V., Zampetti, F. (Hrsg.). (2022): SBST Tool Competition 2022. New York: Institute of Electrical and Electronics Engineers.
Doi: https://doi.org/10.1145/3526072.3527538Zohdinasab, T., Riccio, V., Gambi, A., Tonella, P. (2022): Efficient and effective Feature Space Exploration for testing deep learning systems. ACM Transactions on Software Engineering and Methodology.
Doi: https://doi.org/10.1145/3544792Nguyen, V., Gambi, A., Ahmed, J., Fraser, G. (2022): CRISCE: Towards Generating Test Cases from Accident Sketches. In Nguyen, V., Gambi, A., Ahmed, J., Fraser, G. (Hrsg.), 2022 IEEE/ACM 44th International Conference on Software Engineering: Companion Proceedings (ICSE-Companion) (339-340). New York: Institute of Electrical and Electronics Engineers.
Doi: https://doi.org/10.1145/3510454.3528642Khatiri, S., Birchler, Ch., Bosshard, B., Gambi, A., Panichella, S. (2021): Machine Learning-based Test Selection for Simulation-based Testing of Self-driving Cars Software. CoRR, abs/2111.04666.
Doi: https://doi.org/10.48550/arXiv.2111.04666Nguyen, V., Huber, St., Gambi, A. (2021): SALVO: Automated Generation of Diversified Tests for Self-driving Cars from Existing Maps. In - (Hrsg.), 2021 IEEE International Conference on Artificial Intelligence Testing, AITest 2021, Oxford, United Kingdom, August 23-26, 2021 (128--135). Oxford: IEEE.
Doi: https://doi.org/10.1109/AITEST52744.2021.00033Panichella, S., Gambi, A., Zampetti, F., Riccio, V. (2021): SBST Tool Competition 2021. In - (Hrsg.), 14th IEEE/ACM International Workshop on Search-Based Software Testing, SBST 2021, Madrid, Spain, May 31, 2021 (20--27). Madrid: IEEE.
Doi: https://doi.org/10.1109/SBST52555.2021.00011Zohdinasab, T., Riccio, V., Gambi, A., Tonella, P. (2021): DeepHyperion: Exploring the Feature Space of Deep Learning-Based Systems through Illumination Search. CoRR, abs/2107.06997.
Doi: https://doi.org/10.48550/arXiv.2107.06997Zohdinasab, T., Riccio, V., Gambi, A., Tonella, P. (2021): DeepHyperion: exploring the feature space of deep learning-based systems through illumination search. In Cristian Cadar and Xiangyu Zhang (Hrsg.), ISSTA 21: 30th ACM SIGSOFT International Symposium on Software Testing and Analysis, Virtual Event, Denmark, July 11-17, 2021 (79--90). Denmark, Virtual Event: ACM.
Doi: https://doi.org/10.1145/3460319.3464811Devroey, X., Gambi, A., Galeotti, J.-P., Just, R., Kifetew, F.-M., Panichella, A., Panichella, S. (2021): JUGE: An Infrastructure for Benchmarking Java Unit Test Generators. CoRR, abs/2106.07520.
Doi: https://doi.org/10.48550/arXiv.2106.07520Devroey, X., Panichella, S., Gambi, A. (2020): Java Unit Testing Tool Competition: Eighth Round. In - (Hrsg.), ICSE 20: 42nd International Conference on Software Engineering, Workshops, Seoul, Republic of Korea, 27 June - 19 July, 2020 (545--548). Seoul: ACM.
Doi: https://doi.org/10.1145/3387940.3392265Gambi, A., Müller, M., Fraser, G. (2019): AsFault: testing self-driving car software using search-based procedural content generation. In Atlee, J.-M., Bultan, T., Whittle, J. (Hrsg.), Proceedings of the 41st International Conference on Software Engineering: Companion Proceedings, ICSE 2019, Montreal, QC, Canada, May 25-31, 2019 (27-30). Montreal: IEEE / ACM.
Doi: https://doi.org/10.1109/ICSE-Companion.2019.00030Huynh, T., Gambi, A., Fraser, G. (2019): AC3R: automatically reconstructing car crashes from police reports. In Atlee, J.-M., Bultan, T., Whittle, J. (Hrsg.), Proceedings of the 41st International Conference on Software Engineering: Companion Proceedings, ICSE 2019, Montreal, QC, Canada, May 25-31, 2019 (31--34). Montreal: IEEE / ACM.
Doi: https://doi.org/10.1109/ICSE-Companion.2019.00031Gambi, A., Huynh, T., Fraser, G. (2019): Automatically reconstructing car crashes from police reports for testing self-driving cars. In Joanne M. Atlee and Tevfik Bultan and Jon Whittle (Hrsg.), Proceedings of the 41st International Conference on Software Engineering: Companion Proceedings, ICSE 2019, Montreal, QC, Canada, May 25-31, 2019 (290--291). Montreal: IEEE / ACM.
Doi: https://doi.org/10.1109/ICSE-Companion.2019.00119Gambi, A., Huynh, T., Fraser, G. (2019): Generating effective test cases for self-driving cars from police reports. In Dumas, M., Pfahl, D., Apel, S., Russo, A. (Hrsg.), Proceedings of the ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering, ESEC/SIGSOFT FSE 2019, Tallinn, Estonia, August 26-30, 2019 (257--267). Tallin: ACM.
Doi: https://doi.org/10.1145/3338906.3338942Gambi, A., Müller, M., Fraser, G. (2019): Automatically testing self-driving cars with search-based procedural content generation. In Zhang, D., Moller, A. (Hrsg.), Proceedings of the 28th ACM SIGSOFT International Symposium on Software Testing and Analysis, ISSTA 2019, Beijing, China, July 15-19, 2019 (318--328). Beijing: ACM.
Doi: https://doi.org/10.1145/3293882.3330566Fraser, G., Gambi, A., Kreis, M., Rojas, J.-M., (2019): Gamifying a Software Testing Course with Code Defenders. In Hawthorne, E.-K., Perez-Quinones, M.-A., Heckman, S., Zhang, J. (Hrsg.), Proceedings of the 50th ACM Technical Symposium on Computer Science Education, SIGCSE 2019, Minneapolis, MN, USA, February 27 - March 02, 2019 (571--577). Minneapolis: ACM.
Doi: https://doi.org/10.1145/3287324.3287471Fraser, G., Gambi, A., Rojas, J.-M. (2018): A Preliminary Report on Gamifying a Software Testing Course with the Code Defenders Testing Game. In Mottok, J. (Hrsg.), Proceedings of the 3rd European Conference of Software Engineering Education, ECSEE 2018, Seeon Monastery, Bavaria, Germany, June 14-15, 2018 (50-54). Seeon, Germany: ACM.
Doi: https://doi.org/10.1145/3209087.3209103Gambi, A., Bell, J., Zeller, A. (2018): Practical Test Dependency Detection. In - (Hrsg.), 11th IEEE International Conference on Software Testing, Verification and Validation, ICST 2018, Västeraas, Sweden, April 9-13, 2018 (1--11). Västeras, Sweden: IEEE Computer Society.
Doi: https://doi.org/10.1109/ICST.2018.00011Gambi, A., Kappler, S., Lampel, J., Zeller, A. (2017): CUT: automatic unit testing in the cloud. In Bultan, T., Sen, K. (Hrsg.), Proceedings of the 26th ACM SIGSOFT International Symposium on Software Testing and Analysis, Santa Barbara, CA, USA, July 10 - 14, 2017 (364--367). Santa Barbara, USA: ACM.
Doi: https://doi.org/10.1145/3092703.3098222Havrikov, N., Gambi, A., Zeller, A., Arcuri, A., Galeotti, J.-P. (2017): Generating Unit Tests with Structured System Interactions. In - (Hrsg.), 12th IEEE/ACM International Workshop on Automation of Software Testing, [email protected] 2017, Buenos Aires, Argentina, May 20-21, 2017 (30--33). Buenos Aires: IEEE Computer Society.
Doi: https://doi.org/10.1109/AST.2017.2Gambi, A., Gorla, A., Zeller, A. (2017): O!Snap: Cost-Efficient Testing in the Cloud. In - (Hrsg.), 2017 IEEE International Conference on Software Testing, Verification and Validation, ICST 2017, Tokyo, Japan, March 13-17, 2017 (454--459). Tokio: IEEE Computer Society.
Doi: https://doi.org/10.1109/ICST.2017.51Gambi, A., Mayr-Dorn, Ch., Zeller, A. (2017): Model-based testing of end-user collaboration intensive systems. In Seffah, A., Penzenstadler, B., Alves, C., Peng, X. (Hrsg.), Proceedings of the Symposium on Applied Computing, SAC 2017, Marrakech, Morocco, April 3-7, 2017 (1213--1218). Marrakesch: ACM.
Doi: https://doi.org/10.1145/3019612.3019778Gambi, A., Pezze, M., Toffetti, G. (2016): Kriging-Based Self-Adaptive Cloud Controllers. IEEE Trans. Serv. Comput., 9(3): 368--381.
Doi: https://doi.org/10.1109/TSC.2015.2389236Gambi, A., Zabolotnyi, R., Dustdar, Sch. (2015): Poster: Improving Cloud-Based Continuous Integration Environments. In Bertolino, A., Canfora, G., Elbaum, S.-G. (Hrsg.), 37th IEEE/ACM International Conference on Software Engineering, ICSE 2015, Florence, Italy, May 16-24, 2015, Volume 2 (797--798). Florenz: IEEE Computer Society.
Doi: https://doi.org/10.1109/ICSE.2015.253Dustdar, Sch., Gambi, A., Krenn, W., Nickovic, D. (2015): A Pattern-Based Formalization of Cloud-Based Elastic Systems. In Babar, M.-A., Paik, H.-Y., Chetlur, M., Bauer, M., Sharifloo, A.-M. (Hrsg.), 7th IEEE/ACM International Workshop on Principles of Engineering Service-Oriented and Cloud Systems, PESOS 2015, Florence, Italy, May 23, 2015 (31-37). Florenz: IEEE Computer Society.
Doi: https://doi.org/10.1109/PESOS.2015.13Truong, H.-L., Dustdar, Sch., Copil, G., Gambi, A., Hummer, W., Le, D.-H., Moldovan, D. (2014): CoMoT - A Platform-as-a-Service for Elasticity in the Cloud. In - (Hrsg.), 2014 IEEE International Conference on Cloud Engineering, Boston, MA, USA, March 11-14, 2014 (619--622). Boston: IEEE Computer Society.
Doi: https://doi.org/10.1109/IC2E.2014.44Bersani, M., Bianculli, D., Dustdar, Sch., Gambi, A., Ghezzi, C., Krstic, S. (2014): Towards the formalization of properties of cloud-based elastic systems. In Babar, M., Paik, H.-Y., Chetlur, M., Bauer, M. (Hrsg.), Proceedings of the 6th International Workshop on Principles of Engineering Service-Oriented and Cloud Systems, PESOS 2014, Hyderabad, India, May 31, 2014 (38--47). Hyderabad, India: ACM.
Doi: https://doi.org/10.1145/2593793.2593798Gambi, A., Moldovan, D., Copil, G., Truong, H.-L., Dustdar, Sch. (2013): On estimating actuation delays in elastic computing systems. In Litoiu, M., Mylopoulos, J. (Hrsg.), Proceedings of the 8th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2013, San Francisco, CA, USA, May 20-21, 2013 (33-42). San Francisco: IEEE Computer Society.
Doi: https://doi.org/10.1109/SEAMS.2013.6595490Leitner, Ph., Zabolotnyi, R., Gambi, A., Dustdar, Sch. (2013): A Framework and Middleware for Application-Level Cloud Bursting on Top of Infrastructure-as-a-Service Clouds. In - (Hrsg.), IEEE/ACM 6th International Conference on Utility and Cloud Computing, UCC 2013, Dresden, Germany, December 9-12, 2013 (163--170). Dresden: IEEE Computer Society.
Doi: https://doi.org/10.1109/UCC.2013.39Gambi, A., Hummer, W., Dustdar, Sch. (2013): Automated testing of cloud-based elastic systems with AUToCLES. In Ewen Denney and Tevfik Bultan and Andreas Zeller (Hrsg.), 2013 28th IEEE/ACM International Conference on Automated Software Engineering, ASE 2013, Silicon Valley, CA, USA, November 11-15, 2013 (714--717). Silicon Valley: IEEE.
Doi: https://doi.org/10.1109/ASE.2013.6693140Gambi, A., Hummer, W., Truong, H.-L., Dustdar, Sch. (2013): Testing Elastic Computing Systems. IEEE Internet Comput., 17(6): 76-82.
Doi: https://doi.org/10.1109/MIC.2013.119Gambi, A., Pautasso, C. (2013): RESTful business process management in the cloud. In - (Hrsg.), 5th International ICSE Workshop on Principles of Engineering Service-Oriented Systems, PESOS 2013, May 26, 2013, San Francisco, CA, USA (1--10). San Francisco: IEEE Computer Society.
Doi: https://doi.org/10.1109/PESOS.2013.6635971Gambi, A., Hummer, W., Dustdar, Sch. (2013): Testing elastic systems with surrogate models. In Paige, R., Harman, M., Williams, J. (Hrsg.), 1st International Workshop on Combining Modelling and Search-Based Software Engineering, [email protected] 2013, San Francisco, CA, USA, May 20, 2013 (8-11). San Francisco: IEEE Computer Society.
Doi: https://doi.org/10.1109/CMSBSE.2013.6604429Gambi, A., Filieri, A., Dustdar, Sch. (2013): Iterative test suites refinement for elastic computing systems. In Bertrand Meyer and Luciano Baresi and Mira Mezini (Hrsg.), Joint Meeting of the European Software Engineering Conference and the ACM SIGSOFT Symposium on the Foundations of Software Engineering, ESEC/FSE13, Saint Petersburg, Russian Federation, August 18-26, 2013 (635--638). St. Petersburg: ACM.
Doi: https://doi.org/10.1145/2491411.2494579Gambi, A., Toffetti, G., Pezze, M. (2013): Assurance of Self-adaptive Controllers for the Cloud. In Camara, J., de Lemos, R., Ghezzi, C., Lopes, A. (Hrsg.), Assurances for Self-Adaptive Systems - Principles, Models, and Techniques (311--339). -: Springer.
Doi: https://doi.org/10.1007/978-3-642-36249-1\_12Gambi, A., Toffetti, G., Pautasso, C., Pezze, M. (2013): Kriging Controllers for Cloud Applications. IEEE Internet Comput., 17(4): 40-47.
Doi: https://doi.org/10.1109/MIC.2012.142Gambi, A., Toffetti, G. (2012): Modeling Cloud performance with Kriging. In Glinz, M., Murphy, G.-C., Pezze, M. (Hrsg.), 34th International Conference on Software Engineering, ICSE 2012, June 2-9, 2012, Zurich, Switzerland (1439--1440). Zurich: IEEE Computer Society.
Doi: https://doi.org/10.1109/ICSE.2012.6227075Toffetti, G., Gambi, A., Pezze, M., Pautasso, C. (2010): Engineering Autonomic Controllers for Virtualized Web Applications. In Benatallah, B., Casati, F., Kappel, G., Rossi, G. (Hrsg.), Web Engineering, 10th International Conference, ICWE 2010, Vienna, Austria, July 5-9, 2010. Proceedings (66--80). Vienna: Springer.
Doi: https://doi.org/10.1007/978-3-642-13911-6\_5Gambi, A., Toffetti, G., Comai, S. (2010): Model-Driven Web Engineering Performance Prediction with Layered Queue Networks. In Daniel, F., Facca, F.-M. (Hrsg.), Current Trends in Web Engineering - 10th International Conference on Web Engineering, ICWE 2010 Workshops, Vienna, Austria, July 2010, Revised Selected Papers (25--36). Vienna: Springer.
Doi: https://doi.org/10.1007/978-3-642-16985-4\_3Gambi, A., Toffetti, G., Pezze, M. (2010): Protecting SLAs with surrogate models. In Lewis, G.-A., Metzger, A., Pistore, M., Smith, D.-B., Zisman, A. (Hrsg.), Proceedings of the 2nd International Workshop on Principles of Engineering Service-Oriented Systems, PESOS 2010, Cape Town, South Africa, May 1-2, 2010 (71-77). Cape Town: ACM.
Doi: https://doi.org/10.1145/1808885.1808900Gambi, A., Pezze, M., Young, M. (2009): SLA Protection models for virtualized data centers. In - (Hrsg.), 2009 ICSE Workshop on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2009, Vancouver, BC, Canada, May 18-19, 2009 (10--19). Vancouver: IEEE Computer Society.
Doi: https://doi.org/10.1109/SEAMS.2009.5069069Di Nitto, E., Di Penta, M., Gambi, A., Ripa, G., Villani, M.-L. (2007): Negotiation of Service Level Agreements: An Architecture and a Search-Based Approach. In Krämer, B.-J., Lin, K.-J., Narasimhan, P. (Hrsg.), Service-Oriented Computing - ICSOC 2007, Fifth International Conference, Vienna, Austria, September 17-20, 2007, Proceedings (295--306). Vienna: Springer.
Doi: https://doi.org/10.1007/978-3-540-74974-5\_24
Alessio Gambi, PhDSenior Lecturer Institut Digitalisierung und InformatikProf.(FH) Dipl.-Ing. Dr. Roger Hage
Studiengangsleitung Digital Business Innovation and Transformation
Institut Digitalisierung und Informatik
- Digitale Transformation
- Internationale Geschäftsentwicklung
- R Programmierung
- InformaticsBachelor of Science in Engineering / Vollzeit
- Digital Business Innovation and TransformationMaster of Arts in Business / Berufsbegleitend
- Tourism and Leisure Management in HanoiBachelor of Arts in Business / Vollzeit
-
Digital Innovation Hub OST (DIHOST)
Department of Science & Technology
-
eMobSim - Elektromobilität im Alltag
Projektleitung, Department of Business
Hage R., Lovasz-Bukvova, H., Hopp, M., Hölzl, M., Kormann-Hainzl G., Reiner, M., Dhungana, D. (2021): Agile Approach for E-Learning in Digital-Leadership Training for Small and Medium Enterprises. In Softic, S.K., Read, T. (Hrsg.), Proceedings of the EDEN Annual Conference: Lessons Learned from the Pandemic. Madrid: EDEN.
Lovazs-Bukova, H., Hage, R., Waiguny, M.K.J., Gruber-Mücke, T. (2020): ESTABLISHING AN AVATAR-BASED PRESENCE ON INSTAGRAM. In Doucek, P., Chroust, G., Oškrdal, V. (Hrsg.), IDIMT-2020 Digitalized Economy, Society and Information Management (245-252). Linz: Trauner Verlag.
Prof.(FH) Dipl.-Ing. Dr. Roger HageStudiengangsleitung Digital Business Innovation and TransformationProf.(FH) Mag. Gerhard Kormann-Hainzl
Fachhochschulprofessor Institut Digitalisierung und Informatik
Institut Digitalisierung und Informatik
- Digital Business Transformation mit Schwerpunkt neue digitale Geschäftsmodelle, Bewertung digitaler Transformationsprozesse, Digitale Innovation, Digitale Transformationskompetenzen und Digital Leadership
- Risikomanagement, Außenhandelsfinanzierung, Internationale Finanzierung, Alternative Formen der Finanzierung wie z. B. Crowd Funding
- Strategie und Internationalisierung von Unternehmen und Geschäftsmodellen
- Digital Business Innovation and TransformationMaster of Arts in Business / Berufsbegleitend
- InformaticsBachelor of Science in Engineering / Vollzeit
-
Dataskop – Sensor-Based Data Economy in Niederösterreich
Projektleitung, Department of Science & Technology
-
Digital Innovation Hub OST (DIHOST)
Projektleitung, Department of Science & Technology
-
Mixed Reality Based Collaboration for Industry (MRBC4i)
Projektleitung, Department of Science & Technology
-
Digitales Kompetenzmonitoring in Produktionsunternehmen
Department of Business
-
Enterprise 4.0 – Erfolg im digitalen Zeitalter
Projektleitung, Department of Business
-
Digital Business Transformation
Projektleitung, Department of Business
Hage R., Lovasz-Bukvova, H., Hopp, M., Hölzl, M., Kormann-Hainzl G., Reiner, M., Dhungana, D. (2021): Agile Approach for E-Learning in Digital-Leadership Training for Small and Medium Enterprises. In Softic, S.K., Read, T. (Hrsg.), Proceedings of the EDEN Annual Conference: Lessons Learned from the Pandemic. Madrid: EDEN.
Kormann-Hainzl, G., Lovasz-Bukvova, H., Hoelzl, M. (2021): Are smarts villages just smaller smart cities? Call for a region-type-specific approach to the smartification of communities. In Hemker, T., Müller-Török, R., Prosser, A., Sasvari, P., Scola, D., Urs, N. (Hrsg.), Central and Eastern European e/Dem and e/Gov days 2021. Conference Proceedings (115-126). virtual: Facultas.
Moser, T., Hohlagschwandtner, M., Kormann-Hainzl, G., Pölzlbauer, S., Wolfartsberger, J. (2019): Mixed reality applications in industry: challenges and research areas. Software Quality: The Complexity and Challenges of Software Engineering and Software Quality in the Cloud, 338: 95-105.
Doi: https://doi.org/10.1007/978-3-030-05767-1_7Schwand, C., Kormann, G., Pacher, F., Bartz, M. (2018): Digitale Transformation: Mehrwert durch Vernetzung und Austausch in Multi-Projekt-Umgebungen durch strategische Partnerschaften. In Fachhochschule Salzburg GmbH (Hrsg.), Online Tagungsband FHK Forschungsforum 2018 (1-9). Salzburg: FFH.
Hammerschmid, S., Kormann, G., Moser, T., Reiner, M. (2017): A conceptual Mixed Realities (AR/VR) capability maturity model – with special emphasis on implementation. In Stolfa, J., Stolfa, S., O'Connor, R., Messnarz, R. (Hrsg.), Software and Services Process Improvement. EuroSPI 2017. Communications in Computer and Information Science, vol 748 (372-377). Ostrava: Springer, Cham.
Doi: https://doi.org/10.1007/978-3-319-64218-5_31Kormann, G., Hanus, F., & Moser, T. (2016): Autonomisierung von Produktionsprozessen–Theorie, Anwendung und Werkzeuge. In Fachhochschule des BFI Wien (Hrsg.), Online-Tagungsband FHK Forschungsforum 2016 (eFFH2016-112-2). Wien: FFH.
Schwand, C., Kotek, K., Kormann, G. (2016): GW St. Pölten – Industriell. Integrativ. Innovativ. In Wagner, U., Reisinger, H., Schwand, C. (Hrsg.), Fallstudien aus der österreichischen Marketingpraxis 7 (99-108). Wien: Facultas.
Kormann, G., Andersson, S., Moser, R., & Wictor, I. (2015): Will Digital Transformation become a Game Changer in the Field of Internationalisation Research?. In Department of Management, Birkbeck, University of London (Hrsg.), 19th McGill International Entrepreneurship Conference. International Entrepreneurship in a Multi-Speed Global Economy: Opportunities and Challenges (50). London: McGill.
Kormann, G. (2013): Porsche - A company of its own?. In Wagner, U., Reisinger, H., Schwand, C. (Hrsg.), Fallstudien aus der österreichischen Marketingpraxis (67-74). Wien: Facultas.
Kormann, G., Schuneritsch, W., Bartz, M., Kotek, K., Schwand, C. (2011): Risikoadjustierte Entscheidungsmodelle im Servicebereich - ein Mythos trifft auf Best Practice. In FH Campus Wien (Hrsg.), Tagungsband 5. Forschungsforum der österreichischen Fachhochschulen, 27.-28. April 2011 (-). Wien: FFH.
Schwand, C., Berger, C., Hartbach, S., Kleiss, D., Kotek, K., Kormann, G., Schachner, M., & Neuherz, C. (2011): Grundelemente der Verkaufsraumgestaltung: Die Suche nach dem Stern. In FH Campus Wien (Hrsg.), Tagungsband 5. Forschungsforum der österreichischen Fachhochschulen, 27.-28. April 2011 (-). Wien: FFH.
Prof.(FH) Mag. Gerhard Kormann-HainzlFachhochschulprofessor Institut Digitalisierung und InformatikDr. techn. Dipl.-Ing. Sarita Paudel
Senior Lecturer Institut Digitalisierung und Informatik
Institut Digitalisierung und Informatik
- Business AdministrationBachelor of Arts in Business / Vollzeit
- InformaticsBachelor of Science in Engineering / Vollzeit
- Medical and Pharmaceutical BiotechnologyBachelor of Science in Engineering / Vollzeit
- Applied ChemistryBachelor of Science in Engineering / Vollzeit
- Tourism and Leisure ManagementBachelor of Arts in Business / Vollzeit
- Tourism and Leisure ManagementBachelor of Arts in Business / Berufsbegleitend
- International Wine BusinessBachelor of Arts in Business / Vollzeit
-
NOEDIKOM
Department of Science & Technology
Paudel, S., Smith, P., Zseby, T. (2018): Stealthy Attacks on Smart Grid PMU State Estimation. Proceedings of the 13th International conference on Availability, Reliability and Security (ARES 2018), Article 16: 1-10.
Doi: https://doi.org/10.1145/3230833.3230868Paudel, S., Smith, P., Zseby, T. (2017): Attack Models for Advanced Persistent Threats in Smart Grid Wide Area Monitoring. Proceedings of the 2nd Workshop on Cyber-Physical Security and Resilience in Smart Grids (CPSR-SG'17): 61-66.
Doi: https://doi.org/10.1145/3055386.3055390Paudel, S., Smith, P., Zseby, T. (2017): Data Attacks in Wide Area Monitoring System. Proceedings of the Symposium on Innovative Smart Grid Cybersecurity Solutions.
Paudel, S., Smith, P., Zseby, T. (2016): Data integrity attacks in smart grid wide area monitoring. Proceedings of the 4th International Symposium for ICS & SCADA Cyber Security Research 2016 (ICS-CSR '16).
Doi: https://doi.org/10.14236/ewic/ICS2016.9Paudel, S., Tauber, M., Wagner, C., Hudic, A., Ng, W. (2014): Categorization of Standards, Guidelines and Tools for Secure System Design for Critical Infrastructure IT in the Cloud. 2014 IEEE 6th International Conference on Cloud Computing Technology and Science, Singapore: 956-963.
Florian, M., Paudel, S., Tauber, M. (2013): Trustworthy evidence gathering mechanism for multilayer cloud compliance. 8th International Conference for Internet Technology and Secured Transactions (ICITST-2013).
Doi: https://doi.org/10.1109/ICITST.2013.6750257Paudel, S., Tauber, M., Brandic, I. (2013): Security standards taxonomy for Cloud applications in Critical Infrastructure IT. 8th International Conference for Internet Technology and Secured Transactions (ICITST-2013).
Doi: https://doi.org/10.1109/ICITST.2013.6750282
Dr. techn. Dipl.-Ing. Sarita PaudelSenior Lecturer Institut Digitalisierung und InformatikDr. Rubén Ruiz Torrubiano
Senior Lecturer Institut Digitalisierung und Informatik
Institut Digitalisierung und Informatik
- Kombinatorische Optimierung
- Maschinelles Lernen / Data mining
- Systemarchitektur
- UnternehmensführungBachelor of Arts in Business / Vollzeit
- InformaticsBachelor of Science in Engineering / Vollzeit
- Digital Business Innovation and TransformationMaster of Arts in Business / Berufsbegleitend
-
Kursplanung in modularen Schulsystemen
Projektleitung, Department of Science & Technology
-
BRfit für Künstliche Intelligenz
Department of Business
-
Dataskop – Sensor-Based Data Economy in Niederösterreich
Department of Science & Technology
Dhungana, D., Haselböck, A., Ruiz-Torrubiano, R., Wallner, S. (2022): Variability of safety risks in production environments. In Alexander Felfernig et. al. (Hrsg.), SPLC '22: Proceedings of the 26th ACM International Systems and Software Product Line Conference (178-187). Graz, Austria: Association for Computing Machinery.
Doi: https://doi.org/10.1145/3546932.3547074Ruiz-Torrubiano, R., Suárez, A. (2015): A memetic algorithm for cardinality-constrained portfolio optimization with transaction costs. Applied Soft Computing, 36: 125-142.
Doi: https://doi.org/10.1016/j.asoc.2015.06.053Ruiz-Torrubiano, R., Suarez, A. (2011): The TransRAR crossover operator for genetic algorithms with set encoding. In Ruiz-Torrubiano, R., Suarez, A. (Hrsg.), Proceedings of the 13th annual conference on Genetic and evolutionary computation (489-496). New York: Association for Computing Machinery.
Doi: https://doi.org/10.1145/2001576.2001644Ruiz-Torrubiano, R., Suarez, A. (2010): Hybrid approaches and dimensionality reduction for portfolio selection with cardinality constraints. IEEE Computational Intelligence Magazine, 5(2): 92-107.
Doi: https://doi.org/10.1109/MCI.2010.936308Ruiz-Torrubiano, R., García-Moratilla, S., Suárez, A. (2010): Optimization problems with cardinality constraints. In Ruiz-Torrubiano, R., García-Moratilla, S., Suárez, A. (Hrsg.), Optimization problems with cardinality constraints (105-130). Berlin Heidelberg: Springer.
Doi: https://doi.org/10.1007/978-3-642-12775-5_5Ruiz-Torrubiano, R., Suárez, A. (2009): A hybrid optimization approach to index tracking. Annals of Operations Research, 166(1): 57-71.
Doi: https://doi.org./10.1007/s10479-008-0404-4Ruiz-Torrubiano, R., Suárez, A. (2007): Use of heuristic rules in evolutionary methods for the selection of optimal investment portfolios. In IEEE (Hrsg.), IEEE. Singapore: IEEE.
Doi: https://doi.org/10.1109/CEC.2007.4424474Moral-Escudero, R., Ruiz-Torrubiano, R., Suárez, A. (2006): Selection of optimal investment portfolios with cardinality constraints. In Moral-Escudero, R., Ruiz-Torrubiano, R., Suárez, A. (Hrsg.), 2006 IEEE International Conference on Evolutionary Computation (2382-2388). New York: IEEE.
Doi: https://doi.org/10.1109/CEC.2006.1688603Hernández-Lobato, D., Hernández-Lobato, J., Ruiz-Torrubiano, R., Valle, A. (2006): Pruning adaptive boosting ensembles by means of a genetic algorithm. In Hernández-Lobato, D., Hernández-Lobato, J., Ruiz-Torrubiano, R., Valle, A. (Hrsg.), International Conference on Intelligent Data Engineering and Automated Learning (322-329). Berlin Heidelberg: Springer.
Doi: https://doi.org/10.1007/11875581_39
Dr. Rubén Ruiz TorrubianoSenior Lecturer Institut Digitalisierung und Informatik
Zulassung & Aufnahme – die nächsten Schritte
Sie haben einen Studiengang gefunden, der perfekt zu Ihnen passt? Sehr gut – das Wichtigste ist damit schon geschafft. Informieren Sie sich jetzt über die nächsten Schritte. Wir haben alle relevanten Informationen für Sie zusammengefasst.
Welche Zugangsvoraussetzungen gelten für unsere Bachelor-Studiengänge?
Ein Bachelor-Studium setzt voraus, dass Sie über eine allgemeine Hochschulreife – also über die Matura oder eine gleichwertige Qualifikation – verfügen. Falls Sie diese Voraussetzung nicht erfüllen, können Sie sich im Bereich Studieren ohne Matura darüber informieren, wie Sie sich trotzdem für einen unserer Bachelor-Studiengänge qualifizieren können.
Sie verfügen über ein ausländisches Zeugnis der allgemeinen Hochschulreife?
Wir prüfen die Gleichwertigkeit mit der allgemeinen Hochschulreife gemäß § 4 FHG (Fachhochschulgesetz) idgF, sobald die Online-Bewerbung vollständig abgeschlossen ist. Falls die Gleichwertigkeit nicht gegeben ist, erhalten Sie von uns alle Informationen über die nötigen Ergänzungsprüfungen.
Welchen Sprachnachweis benötigen Sie für unseren englischsprachigen Bachelor-Studiengang?
Wir werden Ihre Englischkenntnisse im Rahmen des Aufnahmegesprächs überprüfen. Gesonderte Zertifikate sind also nicht nötig.
Wichtig
Steht Ihnen der Präsenz- beziehungsweise Zivildienst noch bevor? Als männlicher Bewerber mit österreichischer Staatsbürgerschaft empfehlen wir Ihnen dringend, die Wehrpflicht noch vor dem Studium abzuleisten. So können Sie Ihr Studium ohne Unterbrechung durchführen und direkt nach dem Studium in das Berufsleben einsteigen.
Aufnahmegespräch
Wir möchten Sie gerne persönlich kennen lernen:
Im Rahmen der Online-Bewerbung ist ein Motivationsschreiben und ein kurzes Essay zu einem studiengangsrelevanten Thema zu verfassen. Vorgegebene Fragen zu Ihren Beweggründen, sowie die Anforderungen und Themenstellungen für Ihr Essay finden Sie in der Online-Bewerbung. Sie wählen eines der vorgeschlagenen Themen aus, führen eine Recherche durch um Ihren Wissenstand zu erweitern, setzen sich mit den Fragestellungen auseinander und bringen im Essay Ihren eigenen Standpunkt ein. Ihre Antworten sind in eigens dafür vorgesehene Eingabefelder einzutragen.
Für Ihr Aufnahmegespräch werden Ihr Motivationsschreiben und Ihr Essay als Grundlage herangezogen. Jede Bewerberin und jeder Bewerber erhält die Möglichkeit, sich in einem Einzelgespräch, das in der Regel mit dem Studiengangsleiter bzw. der Studiengangsleiterin geführt wird, vorzustellen. Neben dem persönlichen Kennenlernen werden Ihre Beweggründe für das Studium besprochen, das ausgewählte Thema und die Argumentation im Essay diskutiert, sowie die Relevanz dieses Themas für den Studiengang erörtert.
Das Aufnahmegespräch wird in der Unterrichtssprache des Studiengangs geführt und findet entweder online über Microsoft Teams oder Vorort statt.
Nach dem Aufnahmegespräch werden das Motivationsschreiben, der Essay und das Gespräch nach den inhaltlichen Aussagen, der Ausdruckskraft und der Argumentation bewertet.
Welche Aufnahmetermine gibt es?
Sie haben in der Regel die Wahl zwischen mehreren Aufnahmetagen, die mit Kontingenten hinterlegt sind. Im Zuge der Online-Bewerbung können Sie Ihren bevorzugten Termin auswählen. Um noch von der vollen Auswahl an Terminen profitieren zu können, empfehlen wir Ihnen, Ihre Bewerbung rechtzeitig durchzuführen.
Verschaffen Sie sich jetzt einen Überblick über die für Sie relevanten Termine:
Aufnahmegespräch
15.06.202327.06.202329.06.202305.07.202306.07.2023Nachdem Sie Ihre Online Bewerbung erfolgreich abgeschlossen haben, wird Ihre Bewerbung auf Vollständigkeit und Richtigkeit geprüft. Sobald dieser Vorgang abgeschlossen ist, informieren wir Sie per E-Mail und bestätigen dabei auch den Aufnahmetermin.
Ende der Bewerbungsfrist für EU StaatsbürgerInnen / Nachfrist | 15.04.2023 / 15.08.2023 |
---|---|
Ende der Bewerbungsfrist für Nicht-EU StaatsbürgerInnen
Bewerbung für das nächste Studienjahr möglich ab 01.12.2023 | 15.04.2023 |
Sie haben sich für einen unserer Studiengänge entschieden? Zuerst einmal: Gratulation und vielen Dank für Ihr Vertrauen! Gerne führen wir Sie Schritt für Schritt durch Ihre Online-Bewerbung.
Sie planen gerne voraus und möchten wissen, wann Ihr Studiengang startet? Hier werden Sie fündig!
Fragen zum Studienangebot?
Studienberatung
Sie haben Fragen zu den Zugangsvoraussetzungen, zum Aufnahmeverfahren und Co? Unsere Studienberatung hilft Ihnen gerne weiter.
Ask a Student
Richten Sie Ihre Fragen direkt an unsere Studierenden und holen Sie sich Erfahrungen aus erster Hand. Unsere Facebook-Gruppe macht es möglich.
Zur Facebook-Seite
Ask Jaqueline
Sie möchten Informationen aus erster Hand zum Studiengang Informatics? Kontaktieren Sie Jaqueline direkt, sie beantwortet Ihnen gerne alle Fragen zum Studium.
[email protected]Diese Studiengänge könnten Sie auch interessieren

Unternehmensführung
