About us


  • We received the Open-Source Award 2020 of the state Thuringia (Germany) for our software-engineering teaching project „Ferienpass“. The project brought together students, practitioners from codecentric (Jonas Hecht, Bertram Vogel) and the members of the charity organization Kinderbüro („Kids Office“) Weimar. We developed an open-source solution to register as a child for a holiday ticket online. The students learned foundations of microservices, CI/CD, databases, and Web frontends.


The Chair of Software Systems at Leipzig University develops theory, methods, and tools to automate the development, maintenance, and optimization of reliable, efficient, complex, configurable, and evolvable software systems, including cloud-based systems and AI-based systems. We apply cutting edge techniques from machine learning to the inherent complex problems in software engineering to, for example, reduce energy consumption, improve performance, guide the evolution of software, and support developers in their daily tasks. As for research, our teaching covers fundamental and advanced software engineering topics as well as modern courses on how to develop AI-based and data-centric systems. We advise Bachelor, Master, and PhD theses in these areas, publish in the most renowned conferences and journal, sucessfully receive funding, and collaborate with industry, including codecentric AG, Jetbrains, and REWE Digital.

Die Abteilung „Softwaresysteme“ am Institut für Informatik entwickelt Methoden, Werkzeuge und Theorien zur Automatisierung der Konstruktion, Wartung und Optimierung komplexer, konfigurierbarer Softwaresysteme. Besonderer Fokus liegt auf der Entwicklung KI-basierter Softwaresysteme, hoch skalierbare Softwarearchitekturen wie Microservices sowie die Messung und Optimierung von nicht-funktionalen Eigenschaften, wie Performance und Energieverbrauch. Wir explorieren die Schnittstelle zwischen maschinellem Lernen und Software Engineering:

  • Software Engineering strebt nach ständiger Automatisierung, Optimierung und Effizienzsteigerung in der Softwareentwicklung. Techniken des maschinellen Lernens können hier helfen neue Einsichten zu gewinnen und Probleme zu lösen, die zu komplex und zu groß sind, um sie manuell zu bewältigen.
  • Andererseits können Techniken des Software Engineerings, insbesondere aus dem Bereich des Konfigurations- und Variantenmanagements, helfen, die stetig wachsende Zahl immer komplexerer Methoden im maschinellen Lernen wartbar, einsatzbar und generell beherrschbar zu machen.


We acknowledge gratefully the support of the German Research Foundation (DFG) for funding the projects Green Configuration and Pervolution. Moreover, we are grateful for the support of the German Federal Ministry of Education and Research (BMBF) for funding the project Agile AI.