Team

Florian Holldack

Academic Staff

Florian Holldack, M. Sc.

Room:
R09 R02 H44
Phone:
+49 201 18-34087
Email:
Address:
Universität Duisburg-Essen, Campus Essen
Fakultät für Informatik
Lehrstuhl für Wirtschaftsinformatik und Softwaretechnik
Universitätsstr. 9
45141 Essen

Curriculum Vitae:

  • Seit August 2024: Wissenschaftlicher Mitarbeiter am Lehrstuhl für Wirtschaftsinformatik und Softwaretechnik (Lehrstuhlinhaber: Prof. Dr. Stefan Eicker) an der Universität Duisburg-Essen
  • Seit Januar 2024: Wissenschaftliche Hilfskraft am Lehrstuhl für Wirtschaftsinformatik und Softwaretechnik (Lehrstuhlinhaber: Prof. Dr. Stefan Eicker) an der Universität Duisburg-Essen
  • Oktober 2021 - August 2024: Studium der Wirtschaftsinformatik (M. Sc.) an der Universität Duisburg-Essen
  • Oktober 2018 - September 2021: Studium der Wirtschaftsinformatik (B. Sc.) an der Universität Duisburg-Essen

Publications:

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  • Banh, Leonardo; Holldack, Florian; Strobel, Gero: Copiloting the Future: How Generative AI Transforms Software Engineering. In: Information and Software Technology, Vol 183 (2025), p. 107751. doi:10.1016/j.infsof.2025.107751CitationDetails

    Context

    With rapid technological advancements, artificial intelligence (AI) has become integral to various sectors. Generative AI (GenAI) tools like ChatGPT or GitHub Copilot, with their unique content creation capabilities, pose transformative potential in Software Engineering by offering new ways to optimize software development processes. However, the integration into current processes also presents challenges that require a sociotechnical analysis to effectively realize GenAI's potential.

    Objective

    This study investigates how GenAI can be leveraged in the domain of Software Engineering, exploring its action potentials and challenges to help businesses and developers optimize the adoption of this technology in their workflows.

    Method

    We performed a qualitative study and collected data from expert interviews with eighteen professionals working in Software Engineering-related roles. Data analysis followed the principles of Grounded Theory to analyze how GenAI supports developers' goals, aligns with organizational practices, and facilitates integration into existing routines.

    Results

    The findings demonstrate several opportunities of GenAI in Software Engineering to increase productivity in development teams. However, several key barriers were also identified, that should be accounted for in successful integrations. We synthesize the results in a grounded conceptual framework for GenAI adoption in Software Engineering.

    Conclusions

    This study contributes to the discourse on GenAI in Software Engineering by providing a conceptual framework that aids in understanding the opportunities and challenges of GenAI. It offers practical guidelines for businesses and developers to enhance GenAI integration and lays the groundwork for future research on its impact in software development.

Tutored Theses:

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  • Exploring the Potential of XAI Methods in Medical Diagnostics: Identifying Factors Influencing Acceptance and Trust Among Medical Professionals (Bachelor Thesis Business Information Systems, 2025)