Informatics bachelor degree programme
Would you like to play a creative role in shaping the ways in which we will live and work in the future? Are you also interested in technology-related fields? Then our Informatics programme is the perfect choice for you!
One thing’s for sure: informatics has had a bigger impact on developments in how we live and work than any other field over the past few decades, and will grow in significance over the years to come.
This is the tuition fee for EU and EEA citizens. In addition, the Austrian National Union of Students (ÖH) dues amount to EUR 22.70. Please note that different tuition fees apply for non-EU citizens.
The degree
As of autumn 2019 the IMC University of Applied Sciences Krems will offer the english taught Bachelor degree programme Informatics.
Informatics is a key driver of innovation that is fuelling advances in many aspects of working and everyday life. Computers make it possible to model and predict economic, ecological and social developments; bioinformatics supports the development of new drugs; and thanks to machine learning, large volumes of data become clear and readable, while pattern recognition turns it into a valuable resource with a variety of potential applications. Informatics opens up new options for creating economic added value, protecting the environment and saving lives.
IMC Krems’ English-language Informatics bachelor degree programme is aimed at people who are interested in technology-related subjects and want to play a creative part in shaping aspects of the way we will live and work in the future. The programme includes a specialisation in data science, as well as electives with a strong practical focus: Business Process and Enterprise Technologies and Bioinformatics.
Graduates can look forward to a wide range of career options, including in software development, information-based decision making and IT consulting. They will be in strong demand both in Austria and abroad, with a skills set aligned with future requirements.
This programme provides you with a broad, non-industry-specific education in informatics and will qualify you for entry level roles in a wide range of organisations and industries, as well as advanced master-level study.
“Computer science is not about machines, in the same way that astronomy is not about telescopes.” (Edsger Wybe Dijkstra)
Informatics
Informatics graduates are experts in the ways in which science and technology can help us to process information, translate it into knowledge and then make this knowledge accessible in the form of services. Graduates can work as software developers, data scientists and IT consultants, and develop human-computer interaction interfaces.
The internet of things, Industry 4.0 and social media, as well as the exponential growth in storage capacity and the increase in cloud-based processing power are all synonymous with transformative information-based technologies.
Knowledge and advances in informatics are key drivers of innovation which lead to developments in other fields. This discipline puts a strong focus on teamwork and practical application.
" Those who can imagine anything, can create the impossible. "
Pioneering computer scientist Alan Turing
A formula for success: theoretical knowledge + practical experience
The programme is built on three pillars.
- 1
1. The basics
Semesters 1-4
In the first four semesters you will concentrate on the fundamentals of applied informatics.
Lectures in theoretical informatics cover the key aspects of information processing, as well as statistical methods and techniques. You will apply what you have learned in the practical and technical informatics courses , including projects in which you will be required to develop practical solutions.We place a strong emphasis on software engineering. Utilising programming tools and methods, you will develop high-quality software systems.
Data science is another key area. You will learn the basics of how data from various sources can be made available and analysed in order to draw conclusions that help to answer specific questions. You will also study interdisciplinary models and systems for the application-focused generation of knowledge from data. Using visualisation methods, we provide insights that can be put to use in business and science.
In order to provide a sound knowledge base, IT and IT-security-related legal requirements are examined in connection with all of the fields of application covered on the curriculumYou will also critically reflect on and discuss the impact of data generation, data use and the related technology on individuals and society from different ethical perspectives.
As projects form an important part of the programme, you will carry out practical work from the very start of your degree. There is a web project in the first semester, a software project in semesters 2 and 3, and the data science capstone project in semester 4.
- 2
2. Practical experience
Semester 5
Semester 5 is all about your internship. It is compulsory for all students and lasts 22 weeks. You choose where you want to do it – at a company or other type of organisation, or at an educational or research institution. In Austria or abroad? That’s up to you, too. More than half of our students use the internship as an opportunity to gain experience abroad. The internship semester, called the Practical Training Semester, is a unique chance to get a taste of life in another country, familiarise yourself with different approaches and pick up tips from other experts.
The IMC Career Center team and your lecturers will help you to find a placement where you can gain lots of useful experience for your future career.
- 3
3. Electives
Semester 6
When you get back from your internship, you choose one of the two specialist electives: Business Process and Enterprise Technologies or Bioinformatics. This gives you the opportunity to specialise in the core fields of software development, business consulting and data science with a strong practical focus.
In the Business Process and Enterprise Technologies elective, you work on adapting and developing enterprise resource planning (ERP) systems for companies or other types of organisations. This involves applying the software development methods and fundamental interface technologies you have learned about in order to integrate business applications into ERP systems. You will get to grips with the transformation and storage of business data, as well as data warehousing technologies. The elective also features a practical ERP consulting project involving the implementation of key work stages.
In the Bioinformatics elective you work with data analysis methods in a bioinformatics context. You will compile and transform raw data sets, and analyse and interpret them using data science methods. You will also apply the fundamental principles of visual computing and the data techniques you have studied in order to analyse biological and medical imaging data. A practical bioinformatics project covers the implementation of key steps in the work process.
Curriculum
What can you expect from your studies? The curriculum provides an overview.
Click on the individual courses for further information.
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.
Key features
What makes our Informatics programme so special? Here’s an overview.
A career in a field that is shaping the future
Informatics is a growing discipline. In future, it will have an even more significant impact on our lives. Business, the environment and health – informatics is leaving its mark in all of these areas. As an informatics expert you will be able to play a role in advances in these fields. You will have the knowledge and skills to address ethical and social questions as well as technical challenges. Informatics is influencing how we live and work, perhaps to a greater extent than any other discipline.
Excellent career opportunities
A degree in informatics lays the foundations for a career, not just a job. You’ll have plenty of options at the end of your degree. You can go into software development, information-based decision making or IT consulting. There will be strong demand for informatics graduates from various sectors – in both Austria and abroad. And English as the language of instruction will stand you in very good stead.
Be part of a team
The job profiles of informatics experts have changed over time, and so have employers’ expectations of university graduates. Today there’s a strong focus on teamwork and practical application. IT development frequently employs ‘agile’ methods, meaning that developers are required to work with a high level of personal initiative, often in self-managing teams. On our Informatics programme, you will learn how to complete tasks and find new ways of storing, sharing and exploiting data as part of a team. Because it’s team players who will shape the future.
Newsletter & additional information
Do you need additional information? Subscribe to your personalised newsletter or order brochures about our degree programmes.
Get additional information nowKey skills
When you graduate from the bachelor programme, you will have developed broad-based professional and theoretical expertise, as well as strong practical skills.
You will learn how to develop technical tools and software applications, including artificial intelligence algorithms. The skills required for working with large heterogeneous data sets are essential – data science expertise, in other words. Our graduates are able to generate and visualise information from data organised in real-time.
You will be able to maintain a strong user focus and think beyond the confines of your specialist field. These are skills that will boost your employability when it comes to developing interdisciplinary applications, involving areas of biology or business, for instance.
On this programme, you will learn how to independently conduct research to answer practical questions. This encompasses aspects such as researching academic literature, selecting appropriate methods and drawing conclusions, as well as formulating and providing the rationale for solutions.
Highly skilled, creative team players with a strong sense of responsibility: these are the type of graduates that we want to produce – people who society urgently needs in an age of automated data generation. Because informatics has a bearing on ethics and socials issues, too.
Career paths
Informatics graduates can enter a range of professions and sectors.
Courses on the programme are taught in English so you will be ideally prepared for the workplace – whether you’ve set your sights on a career in Austria or abroad. In many companies and organisations today, English is used internally as well as when communicating with business partners and customers.
In additional to professional expertise, this degree will also equip you with the language skills you need to get your working life off to a great start or move up the career ladder.
- Potential entry-level positions
- Software development: front end, back end, web (for external or in-house clients)
- Data science: data collection, cleansing, analysis and interpretation (for external or in-house clients)
- IT consulting: advising clients and adapting software solutions
- Business intelligence engineering: developing and operating ERP, DWH and BI systems (for and in companies)
What makes us special? We are more than happy to tell you about the aspects of our university, which we are especially proud of.
Friendly and cosmopolitan: The city attracts students from all over the world, who come to study, research and work together.
Our university has removed a host of administrative hurdles, leaving you free to concentrate fully on your studies.
Do you have questions regarding our degree programmes or the application? Contact our Prospective Student Advisory Service.
Opinions: Informatics
Click through the videos of the degree programme.
Get to know our university of applied sciences from a new and very personal perspective.
Our Team
Get to know the core team of our bachelor degree programme Informatics.
Prof.(FH) Dipl. Ing. Dr. techn. Deepak Dhungana
Head of Institute Digitalisation and Informatics / Programme Director Informatics
Institute Digitalisation and Informatics
- 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 / full-time
-
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
Project Leader, Department of Science & Technology
-
UniLab - Von der Universität zum Arbeitsmarkt im 21. Jahrhundert: ein Schritt vorwärts in der Vermittlung von Praktikumsplätzen
Project Leader, 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 DhunganaHead of Institute Digitalisation and Informatics / Programme Director InformaticsHead of Institute Digitalisation and Informatics / Programme Director Informatics
Prof.(FH) Dipl. Ing. Dr. techn. Deepak Dhungana
Core Competencies
- 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
- Business Administration
- Human Resource Development
- Internship Coordinator - Unternehmensführung (BA), Betriebswirtschaft für das Gesundheitswesen (BA), Business Administration (BA), Marketing (MA)
- Betriebswirtschaft für das GesundheitswesenBachelor of Arts in Business / full-time
- Business AdministrationBachelor of Arts in Business / full-time
- InformaticsBachelor of Science in Engineering / full-time
- Tourism and Leisure ManagementBachelor of Arts in Business / full-time
Mag.(FH) Nicolas AronCorporate Relations / Department of BusinessAlessio Gambi, PhD
Senior Lecturer Institute Digitalisation and Informatics
Institute Digitalisation and Informatics
- Automated Software Quality
- Cloud computing
- Self-adaptive and autonomous Systems
- InformaticsBachelor of Science in Engineering / full-time
-
FLEXCRASH - Flexible und hybride Herstellung von grünem Aluminium zur Herstellung maßgeschneiderter adaptiver crashtoleranter Strukturen
Project Leader, 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 Institute Digitalisation and InformaticsProf.(FH) Dipl.-Ing. Dr. Roger Hage
Programme Director Digital Business Innovation and Transformation
Institute Digitalisation and Informatics
- Digital Transformation
- International Business Development
- R Programming
- InformaticsBachelor of Science in Engineering / full-time
- Digital Business Innovation and TransformationMaster of Arts in Business / part-time
- Tourism and Leisure Management in HanoiBachelor of Arts in Business / full-time
-
Digital Innovation Hub OST (DIHOST)
Department of Science & Technology
-
eMobSim - Elektromobilität im Alltag
Project Leader, 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 HageProgramme Director Digital Business Innovation and TransformationProf.(FH) Mag. Gerhard Kormann-Hainzl
Professor (FH) Institute Digitalisation and Informatics
Institute Digitalisation and Informatics
- Digital Business Transformation such as digital business model innovation, digitalization processes innovation, digital leadership
- Risk management, international trade and finance and alternative financial instruments such as crowd funding
- Strategic Management and Internationalisation
- Export-oriented ManagementBachelor of Arts in Business / full-time
- Digital Business Innovation and TransformationMaster of Arts in Business / part-time
- InformaticsBachelor of Science in Engineering / full-time
-
Dataskop – Sensor-Based Data Economy in Niederösterreich
Project Leader, Department of Science & Technology
-
Digital Innovation Hub OST (DIHOST)
Project Leader, Department of Science & Technology
-
Mixed Reality Based Collaboration for Industry (MRBC4i)
Project Leader, Department of Science & Technology
-
Digitales Kompetenzmonitoring in Produktionsunternehmen
Department of Business
-
Enterprise 4.0 – Erfolg im digitalen Zeitalter
Project Leader, Department of Business
-
Digital Business Transformation
Project Leader, 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-HainzlProfessor (FH) Institute Digitalisation and InformaticsDr. techn. Dipl.-Ing. Sarita Paudel
Senior Lecturer Institute Digitalisation and Informatics
Institute Digitalisation and Informatics
- Business AdministrationBachelor of Arts in Business / full-time
- Export-oriented ManagementBachelor of Arts in Business / full-time
- InformaticsBachelor of Science in Engineering / full-time
- Medical and Pharmaceutical BiotechnologyBachelor of Science in Engineering / full-time
- Applied ChemistryBachelor of Science in Engineering / full-time
- Tourism and Leisure ManagementBachelor of Arts in Business / full-time
- Tourism and Leisure ManagementBachelor of Arts in Business / part-time
- International Wine BusinessBachelor of Arts in Business / full-time
-
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 Institute Digitalisation and InformaticsDr. Rubén Ruiz Torrubiano
Senior Lecturer Institute Digitalisation and Informatics
Institute Digitalisation and Informatics
- Combinatorial optimization
- Machine learning / data mining
- Systems architecture
- UnternehmensführungBachelor of Arts in Business / full-time
- InformaticsBachelor of Science in Engineering / full-time
- Digital Business Innovation and TransformationMaster of Arts in Business / part-time
-
Kursplanung in modularen Schulsystemen
Project Leader, 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 Institute Digitalisation and Informatics
Application and admissions – the next steps
You've found a course that's a perfect fit? Great – you’ve already taken the most important step! We’ve put together an overview to guide you through the next steps.
What are the admission requirements for bachelor programmes?
To qualify for admission to a university of applied sciences bachelor degree programme, you must have an Austrian school-leaving certificate or an equivalent qualification.
Do you have a school-leaving certificate issued outside Austria?
We’ll check to make sure it’s equivalent to an Austrian certificate in accordance with section 4 of the University of Applied Sciences Studies Act (FHG) when you’ve sent us all the relevant documentation via our online application tool. If it is not an equivalent, you’ll receive information on the supplementary examinations you’ll need to pass. In a nutshell, you will have the option of completing a summer school and the necessary supplementary examinations at IMC Krems or look for an external provider. In that case, you might consider our cooperation partner, the University of Applied Sciences Upper Austria: It offers a one-year International Foundation Programme which provides you with all the necessary qualifications you need in order to start your studies in Krems.
What proof of your language skills is required for our English-language bachelor degree programme?
We’ll assess your English language proficiency at your interview, so there is no need to provide additional evidence of your English skills.
Important
Do you still need to complete your military or alternative service? If you’re a male Austrian citizen, we strongly recommend completing your compulsory national service before beginning your studies. This will allow you to finish your degree with no interruptions and start your career without delay afterwards.
Application interview
We would like to get to know you as a person:
As part of the online application you will have to write a statement of motivation and a short essay on a topic relevant to the degree programme. Predefined questions about your motivations as well as the requirements and topics for your essay can be found in the online application. You choose one of the suggested topics, conduct research to broaden your knowledge, deal with the issues and bring your own point of view to the essay. Your answers are to be entered in the fields provided.
Your statement of motivation and your essay form the basis for your application interview. Every applicant has an opportunity to introduce themselves in a face-to-face discussion, usually with the degree programme director. In addition to the personal introduction and your motivation to study, the applicant and the interviewer discuss the topic selected and the arguments used in the essay, as well as the topic’s relevance for the degree programme.
The application interview is held in the language of instruction of the degree programme and can take place either online via Microsoft Teams or in presence.
After the application interview, your statement of motivation, the essay and your performance throughout the interview are assessed on the basis of the content-related remarks, the manner in which they express themselves and the arguments used.
Interview dates
There is usually a selection of dates to choose from, with quotas allocated for each date. You can select a preferred date and time slot for your admission interview during the online application process. In order to still benefit from the full selection of dates, we recommend that you submit your application in good time.
Get an overview of the dates for your programme.
Admission Interview
15/06/202327/06/202329/06/202305/07/202306/07/2023After you have successfully completed your online application, your application will be checked for completeness and correctness. As soon as this process is completed, we will inform you by e-mail and confirm the date for your admission interview. We will send you the Microsoft Teams Meeting Link in a separate e-mail a few days before the application interview date.
Application deadline for EU nationals / Extended application deadline | 15/04/2023 / 15/08/2023 |
---|---|
Application deadline for non-EU nationals
Application for the next study year possible from 01/12/2023 | 15/04/2023 |
You've decided for one of our degree programmes? First of all: congratulations and thank you for choosing us! We’ll be happy to guide you step-by-step through your online application.
You would like to plan ahead and would like to know when your degree programme starts? Here you will find the answer!
Questions about the degree programme?
Prospective Student Advisory Service
Do you have questions regarding the entry requirements, the admission procedure and more? Our Prospective Student Advisory Service is happy to help.
Ask a Student
Join our Facebook group: Direct your questions to our students and get first-hand accounts about studying at IMC Krems.
Zur Facebook-Seite
Ask Jaqueline
Would you like first-hand information about the Informatics degree programme? Contact Jaqueline directly, she will be happy to answer all your questions about the study programme.
[email protected]Similar degree programmes

Applied Chemistry
