The portfolio of Software Competence Center Hagenberg (SCCH) reflects five areas:
Rigorous Methods in Software Engineering
Despite having numerous practical guidelines, success stories, and convivial methods and tools, current software engineering practices still lack the maturity of other engineering disciplines. Major problems include a high rate of software faults and inefficient quality assurance techniques. Rigorous methods, when applied correctly, complement contemporary software development practices and help to precisely model the critical system parts where safety, integrity and reliability are coveted system traits. Together with our partner companies, RSE intends to develop and employ new rigorous model-based techniques to improve the overall software development process.
Process and Quality Engineering
The development of high-quality software products demands effective methods and tools along with efficient development processes. In cooperation with partner companies, PQE’s seeks to research and develop new concepts and methods for quality and process management as well as their continuous improvement and realization in customized tools and company processes. PQE focuses particularly on requirements, architecture and test management, quality and process management, application life-cycle management, sustainable development paradigms, and engineering strategies. PQE addresses companies that develop software as a product or service or as part of a product.
Models Architectures and Tools
MAT is involved in modern constructive approaches in Software Engineering with the goal of facilitating the creation and further development of complex technical software systems over long time ranges and ensuring their ultimate reliability. Here model-based and formal approaches to automatic generation of software from domain models are employed along with the option of end-user programming via domain-specific programming languages. The various research aspects in MAT pursue the long-range vision of automatic software generation from verified abstract specifications for various technologies and platforms. This is necessary to ensure the long-range documentation and storage of the expert (usually technical) know-how of a company independently of short-lived software technologies.
Knowldege-Based Vision Systems
KVS develops analysis methods for image data on the basis of Computational Intelligence. One example is data-driven model building for the characterization of defect-free textures. KVS also researches logic-based and knowledge-based modeling of quality criteria and cognitive aspects in aesthetic evaluation. Rigid and deformable geometric structures are analyzed via registration. KVS’ research results are applied to motion analysis and tracking of objects and persons as well as to quality inspection for textured or shiny surfaces and 3D structures.
Data Analysis Systems
DAS develops methods for automatic analysis of sensor data for the purpose of knowledge acquisition and model refinement. The spectrum of applications encompasses process analysis, process optimization, conditioning monitoring, virtual sensors, disruption prognoses and optimal control systems in the process industry and production, in machine manufacture and in environmental technology such as heating system controls.