Dominik Holling is a researcher at the software engineering chair of Prof. Pretschner at the department of computer science at the TUM since 2012. His main areas of research include software testing and symbolic execution. One of the topics in these areas is using defect models for quality assurance. Defect models allow the systematic creation of fault-based tests. The operationalization of defect models allows the (semi-)automatic derivation of test cases or review checklists.
Before becoming a researcher at TUM, Dominik Holling studied computer science at the TU Kaiserslautern (2006 – 2011) with a software engineering and security focus. During these studies, he published an approach to establish trust in cloud infrastructures and worked on approaches to bring guarantees to the field of usage control.
While developing defect model concepts, Dominik Holling has worked with various companies to elicit and classify defect models using a defect model lifecycle framework. This framework allowed the documentation of tacit knowledge leading to process improvements and later operationalization of defect models in practice.
In the world of IT, DevOps has taken the development of applications to a new level of velocity, quality as well as resilience and reshaped the thinking towards value deliver to the customer. With the addition of computing power and connectivity in (medical) devices, their development is also moving towards continuous X (integration, testing, deliver and even deployment) using methods of DevOps in Systems Engineering. Creating an overarching and comprehensive test strategy enables the connection of the disciplines involved in systems engineering to the continuous X / DevOps world and aligns them accordingly to deliver value to the customer with high velocity and quality. On the journey to create and implement such a test strategy, we will touch on the following points:
The intersection where security practices and DevOps transformations meet have a distinct significance particularly in the Healthcare/Life Science environment which are highly regulated and compliance-oriented and where the protection of data is of utmost importance. Some of the key points of discussion include:
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