Ensuring Reliable Legacy Modernization:
LLM-based hybrid approaches enabling explainability and automated quality assurance of transformation code within legacy modernization pipelines
Reliable Legacy Modernization: This PhD project develops hybrid LLM and XAI frameworks to transform Legacy Code to Java. It integrates automated quality assurance to ensure functional correctness, making AI-driven pipelines transparent and auditable for critical infrastructures.
Projektverantwortliche:
Amrei Kugler
Mitglied im Verbundkolleg: 2026
Betreuender Hochschule Neu-Ulm:
Prof. Dr. Philipp Brune
OTH Amberg-Weiden:
Prof. Dr. Daniel Loebenberger
Amrei Kugler
Hochschule Neu-Ulm Projekt: Ensuring Reliable Legacy Modernization:
Publikationen:
Weinfurter, V., Kirmaier, A., Brune, P., Bergande, B. (2021). Raising Awareness for IT Security in
Higher Education – A Teaching Experiment on SQL Injection for Non-Computer Science Majors.
619-620
10.1145/3456565.3460035.
Bergande, B., Meyer, D., Kirmaier, A., Kellermayer, B., Stirzel, M. (2020). Raising Motivation of
Programming Novices? Findings from a Controlled Laboratory Experiment Using Anki Vector TM Robots.
10.1109/TALE48869.2020.9368406.
in Review: Dreher, S., Kugler, A., Brune, P., (2025). GenAI-Driven Automation for Legacy User-Interface and Code Documentation and Testing.
Kugler, A., Kuck, C., Weber, P., Brune, P.(2026). Preserving Domain Correctness in AI-Powered Legacy System Modernization: An Automated Pipeline for Migrating Legacy Code to Clean Java.