We collaborate with several well-known research labs and compentence centers. Below we provide a rough overview of our activities there.
We have a long standing collaboration with the LCM in context of mutli-domain engineering. Engineering is a collaborative effort among many participants - from different engineering domains. Complex and multidisciplinary problems are broken down into tasks that individual engineers solve with the available tools and methods. However, the tool landscape is diverse. Companies commonly use dozens, if not hundreds, of tools. And these tools differ fundamentally depending on engineering discipline. Yet the artifacts in these tools are often interdependent. Inconsistencies arise if these dependencies are not understood completely and correctly.
Machine to Machine Communication
Product and Production Processes
Manufacturing enterprises of the future are networked and Pro2Future Area 2 will develop a middleware-based approach to support communication of modular and autonomous, intelligent mechatronic systems. To do so, a message based approach for a scalable system of networked shopfloor systems and software systems is taken. Modularity and loose coupling is required to support adaptation of these systems.
Over the past ten years, we have collaborated with SCCH in context of software testing and software product lines. Software Product Lines (SPLs) are families of related software systems distinguished by the set of features each one provides. SPLs practices have proven benefits such as better product customization and reduced time to market. Testing (in context of SPLs and beyond) pose additional challenges stemming from the typically large number of product variants which make it infeasible to test every single one of them.
In context of the LIT Lab, we develop theories, methods and tools for specification, design, implementation, testing, monitoring, and evolution of large and complex software systems. Our current focus is on formal software systems modeling and the modeling of software systems variability.
Machine Learning and Artificial Intelligence
The LIT AI Lab headed by Prof. Sepp Hochreiter was founded as a permanent research center of the Linz Institute of Technology (LIT). In the unique environment offered by the Johannes Kepler University (JKU) Linz, the LIT AI Lab bundles JKU’s world-class expertise in artificial intelligence (AI) for shaping and advancing AI research and its industrial applications. We are participating in the LIT AI Lab in applying ML/AI techologies for software and systems engineering.