Problem Description
Business departments typically run hundreds to thousands of business-managed applications such as Excel sheets, self-developed Access databases, Lotus Notes or other self-created “shadow IT” systems. The large quantity and the sheer complexity of these fragmented IT landscapes imposes an increasing problem for companies in terms of various factors, e.g. costs, compliance, maintenance, compatibility, consistency, security, upgradeability, and monitoring. Thus, companies target transforming their existing fragmented IT landscapes towards consolidated target landscape.
Industry Partner
The appeleon gmbh, located in Mannheim (Germany) offers its customers the product appeleon agile environment to create and adapt applications very fast in order to digitalize individual business processes. appeleon is driven by the vision to digitalize the implementation and the migrations of Business Managed Applications itself. The two main modules of the appeleon agile environment are ZeroCoding and Transformer.
appeleon is productive at well-known DAX-Companies as well as small and medium-sized businesses.
Goal of the Thesis
The master thesis seeks to design and evaluate a machine learning algorithm to automatically analyze existing business-managed applications and to provide decision support for the migration of these applications towards a state-of-the-art target technology platform.
Skills
To apply for the master thesis, we welcome students with the following skills:
• Good technical and programming skills, knowledge of machine learning algorithms is advantageous
• Very good time management and self-organization
• German & English speaking
• High social skills
The master thesis is carried in cooperation with appeleon.
