Dr. Justus Bogner
Researcher, Educator, Software Engineer
Hi! I'm Justus, a researcher in empirical software engineering. I also teach software engineering courses at the university and as a trainer for companies. Before and during my PhD, I was employed for more than 9 years as a software engineer in the industry, building mostly web- and service-based enterprise applications.
In May 2020, I received my PhD in Computer Science (Dr. rer. nat.) from the University of Stuttgart, Germany. My advisors were Prof. Dr. Alfred Zimmermann and Prof. Dr. Stefan Wagner, with Prof. Dr. Cesare Pautasso as external reviewer. Currently, I'm a postdoc at the Institute of Software Engineering at the University of Stuttgart. Within Prof. Wagner's Empirical Software Engineering Group, I lead the division "Software Engineering for AI- & Microservice-Based Systems" (SE4AI&MS). I regularly review for journals, conferences, and workshops, such as IEEE TSE, PeerJ CS, IEEE Software, Wiley SPE, ECSA, Euromicro SEAA, or XP. I am also a co-organizer of the SAML workshop, which combines software architecture and machine learning. Lastly, I'm part of the student admission committee for the M.Sc. study programme "Software Engineering" in my department.
You can reach or follow me via the following ways:Email: email@example.com
Researchgate: Justus Bogner
Google Scholar: Justus Bogner
If you have questions about my research, want to write your student thesis with me, or have an idea for a study collaboration related to my research interest, feel free to reach out!
To study and improve software engineering, I apply both quantitative and qualitative empirical methods, such as controlled experiments, systematic literature reviews, surveys, interviews, repository mining, or case studies. Based on these results, I then create and evaluate tools or methods to support software professionals. While I conducted studies in other areas, my two main SE knowledge areas are software architecture and software quality, especially maintainability, evolvability, and technical debt. Moreover, I mainly study two types of systems described below. For more details, please refer to my publications.
In my PhD thesis, I studied the evolvability assurance of the architectural style microservices, and approached the topic via metrics, scenario-based evaluation, and (anti-)patterns. While I still continue parts of this line of research, I'm also interested in microservices migration, the design of RESTful APIs, and web-based applications in general.
After my PhD, I also broadened my scope with an additional research area: software engineering for AI-based systems (SE4AI). Here, I am mostly interested in the development process, architecture, and quality assurance of systems with AI components, e.g., systems which include one or more machine learning models.
I have won the following awards:
Best Reviewer Award
At the European Conference on Software Architecture (ECSA), 2022
infos Dissertation Award
From the Informatik Forum Stuttgart, 2021, for my PhD thesis:
"On the Evolvability Assurance of Microservices: Metrics, Scenarios, and Patterns"
Best Presentation Award
At the International Conference on Technical Debt (TechDebt), 2021, for the paper:
"Characterizing Technical Debt and Antipatterns in AI-Based Systems: A Systematic Mapping Study"
IEEE TCSE Distinguished Paper Award
At the International Conference on Software Maintenance and Evolution (ICSME), 2019, for the paper:
"Assuring the Evolvability of Microservices: Insights into Industry Practices and Challenges"
Best Student Paper Award
At the European Conference on Service-Oriented and Cloud Computing (ESOCC), 2018, for the paper:
"Towards an Evolvability Assurance Method for Service-Based Systems"
Best Presentation Award
At the Central European Workshop on Services and their Composition (ZEUS), 2018, for the paper:
"Analyzing the Relevance of SOA Patterns for Microservice-Based Systems"
Master Thesis Award
From the Herman Hollerith Center, 2015, for my M.Sc. thesis:
"Identifying Relevant Software Architecture Patterns for IT Service Monitoring and Reporting Solutions"