Have a look at the center's research areas down below.
Cybersecurity & Safety
In cybersecurity and safety, the aim is to provide research that helps in the development of secure and safe software systems. To this end, focus is placed on techniques, methods and processes for mitigating accidental faults and security attacks. Current research areas of interest are:
- Secure software engineering,
- Security requirements engineering,
- Threat modelling and analysis,
- Static code analysis,
- Penetration testing,
- Human factors, and
- Blockchain applications (Dapps).
We address real-world challenges by engaging in both academic and industrial collaborations at national and international level. Please contact us if you are interested in building a partnership or conducting research.
The focus of the Data Analytics (DA) research area at SDU Software Engineering is to advance the tools and methodologies that facilitate the effective use of (big) data in various decision support contexts. DA can be utilized to effectively assess and interpret systems’ conditions, early detect systems’ anomalies, quickly diagnose fault root causes, accurately predict future conditions, intelligently make decisions (such as schedules for maintenance, inventory, and logistics), and optimally control systems for operations. We have identified the following objectives:
- to design and develop tools and methodology for data-based knowledge extraction,
- to design and develop new methods for utilizing data for decision support,
- to support industry by providing tools and methodology for data analytics in different application areas.
We are interested in collaborations with industry and academia for identifying new challenges and advancing the research in the area of data analytics with new case studies and methodologies.
Modeling & Simulation
The focus of the Modeling and Simulation (M&S) research area at SDU Software Engineering is to identify and study the challenges in the methodology and use of M&S for understanding complex systems, in both general and specific scenarios. Our goal is to advance the research in M&S with new and improved approaches. We have identified the following objectives:
- to design and develop simulation tools and methodology for design, modification, and evaluation of complex systems and inter-dependent decisions,
- to support industry by designing and analyzing decision-making scenario models that can be applied to different application areas,
- to develop methods and tools that automatically derive simulation models from data.
As such, we are interested in forming partnerships with industry and academia to explore new emerging developments in specific applications of societal importance in order to assess the needs and impacts that advances in modeling and simulation will have within those domains.
Software Process & Product Improvement
The focus of the software process and product improvement (SPPI) research area at SDU Software Engineering is to increase the body of knowledge of industrial software engineering and further develop software engineering methods and practices in the industry. Examples of areas we are interested in are as follows:
- Agile in non-agile environments such as DevOps in medical device software development
- Vertical usage of agile in large companies, i.e. agile beyond software development function
- Integrating user experience, security etc. into agile ways of working
- Software developer experience, i.e. how to improve the work life of the developer
We collaborate with local and international industrial and academic partners in several ways from small student projects to large research programmes. Please contact us if you are interested in hearing more about SPPI research and collaboration with our section.
The focus of the Systems Development research area is to improve software constructs, tools, and approaches for building software that solve complex industrial problems. We are specifically interested in:
- Analyzing and creating the architectural basis for realizing the system concepts and requirements for the problem at hand
- Identification and development of the software constructs that are strategic to the industrial solution
- Design of data, functions, constrained language, or tools appropriate to the domain and the software layer
- Delivering and containing functionality as services, controllers, agents
We collaborate with local and international industrial and academic partners in several ways from small student projects to large research programmes. Please contact us if you are interested in hearing more about Systems Development research area and collaboration with our section.
Members: Lone Borgersen
Teaching in Software Engineering
The focus of the Teaching in Software Engineering (TeaSE) research and development area is through research-based methodologies, experiments and collaboration with the surrounding industry and society, with the aim of creating an efficient and relevant software engineering education. The Examples of areas we are interested in are as follows:
- Software Engineering
- Activating teaching
- Study intensity
- Collaboration, communication and relations
- Blended learning and online learning
- Case based teaching
- Interdisciplinary projects
- Problem oriented projects
- Project supervision
- Collaboration among teachers
We collaborate with other education fields locally and contribute to teaching conferences nationally. Please contact us if you are interested in hearing more about TeaSE research and collaboration with our section.
Verification & Validation
The focus of Verification & Validation (V&V) research at SDU Software Engineering is on the development of high-assurance system design and analysis methodologies for complex systems (CS), e.g., Cyber-Physical Systems, which is at the confluence of embedded systems, applied formal methods, static analysis and property-based testing. The approach is to pursue the following research directions:
- To assure safety, reliability and effectiveness of interconnectivity and interoperability of CS;
- To prove both functional and non-functional requirements for CS;
- To uncover hidden faults and analyse potential safety hazards in CS at different abstraction levels;
- To demonstrate in an industrial setting the effectiveness of the methodologies in a variety of application domains such as autonomous vehicles and robotic systems.
We address real-world challenges by engaging in both academic and industrial collaborations at national and international level. If you would like to talk further about building a partnership in line with our V&V expertise, please contact us.
Contacts: Eun-Young Kang and Jan Midtgaard