Analyse der Nutzung von KI für AENEAS (ANuKI) - Repository

This repository contains source code of software projects related to ANuKI. Further information about the project, its contributors and funding can be found here

Overview of projects

Repository Title Related Publication
Artefaktextraktor-/Generator Bülbül, M., Straub, P., Münch, J., Kuhrmann, M. (2025). Towards Generating Measurable Artifact Models from Standards in Regulated Domains. In: Pfahl, D., Gonzalez Huerta, J., Klünder, J., Anwar, H. (eds) Product-Focused Software Process Improvement. PROFES 2024. Lecture Notes in Computer Science, vol 15452. Springer, Cham. 10.1007/978-3-031-78386-9_18
Metric Catalog Tool

Vasylieva, K., Brenner, T., Kuhrmann, M., Münch, J. (2025). Enhancing Transparency in Space Metrics Use: Insights from an Initial Study. In: Pfahl, D., Gonzalez Huerta, J., Klünder, J., Anwar, H. (eds) Product-Focused Software Process Improvement. PROFES 2024. Lecture Notes in Computer Science, vol 15452. Springer, Cham. 10.1007/978-3-031-78386-9_22

Vasylieva, K., Kuhrmann, M., Xavier, M. K., & Klünder, J. (2023, September). How agile are you? discussing maturity levels of agile maturity models. In 2023 49th Euromicro Conference on Software Engineering and Advanced Applications (SEAA) (pp. 270-277). IEEE. 10.1109/SEAA60479.2023.00049

Aligned Quality Model P. Beyersdorffer, J. Münch and M. Kuhrmann, "Alignment of Quality Models for Assessing Software Requirements in Large-scale Projects: A Case from Space," 2023 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC), Edinburgh, United Kingdom, 2023, pp. 1-9, doi: 10.1109/ICE/ITMC58018.2023.10332295.
RequirementsQuality Extraktor

Korfmann, R., Beyersdorffer, P., Gerlich, R., Münch, J., & Kuhrmann, M. (2025). Overcoming Data Shortage in Critical Domains With Data Augmentation for Natural Language Software Requirements. Journal of Software: Evolution and Process, 37(5), e70027.

Korfmann, R., Beyersdorffer, P., Münch, J., & Kuhrmann, M. (2024, September). Using data augmentation to support AI-based requirements evaluation in large-scale projects. In European Conference on Software Process Improvement (pp. 97-111). Cham: Springer Nature Switzerland. 10.1007/978-3-031-71139-8_7

Augmentation
Measurement

Note

All software has been tested on MacMini M1, 2020