RegComp
Project description
The RegComp project develops novel methods for supporting regulatory requirements engineering through automated regulatory change analysis and impact assessment. Instead of focusing solely on verifying compliance, the project investigates how changes in regulations can be systematically analyzed to understand their implications for software systems.
The research combines advances in natural language processing, semantic search, information retrieval, and large language models to automatically identify regulatory changes, characterize their type and scope, and determine which software artifacts are likely to be affected. The developed approaches support engineers in prioritizing implementation activities, tracing the rationale behind regulatory updates, and understanding the relationships between evolving regulations and software assets.
Particular emphasis is placed on explainable AI-assisted decision support that enables engineers to efficiently assess regulatory changes while maintaining transparency and confidence in the generated results. The developed methods are evaluated using real-world industrial case studies to ensure their practical applicability and usefulness in regulated software development.
Research contribution
The RegComp project advances the state of the art in regulatory requirements engineering by introducing AI-assisted methods for automated regulatory change analysis and software impact assessment. The project contributes models, techniques, and tool-supported approaches that enable organizations to better understand how evolving regulations influence software systems throughout their lifecycle.
The research contributes methods for automatically detecting and categorizing regulatory changes, assessing their impact on software artifacts, supporting traceability between regulations and engineering assets, and providing explainable recommendations for software evolution. By integrating artificial intelligence with regulatory engineering practices, the project aims to improve the efficiency, scalability, and transparency of regulatory change management while reducing the manual effort required to maintain compliance in continuously evolving regulatory environments.
Funding
Project duration
01.01.2023 – 31.12.2026
Contact
Project partner
Publications
- Investigating Automated Change Impact Analysis in FinTech Regulations Information and Software Technology Journal, ():, 2026. Details URL DOI BIB
- Designing NLP-based solutions for requirements variability management: experiences from a design science study at Visma , 2024. The 30th International Conference on Requirement Engineering: Foundation for Software Quality (REFSQ). Details URL DOI BIB
- Practices, Challenges, and Opportunities When Inferring Requirements From Regulations in the FinTech Sector - An Industrial Study In 9th International Workshop on Empirical Requirements Engineering, 2024. IEEE. Details DOI BIB



