Thomas Vogel


L.079.08007 Learning, Optimization, and Assurances for Self-Adaptive Systems

Seminar, Summer 2022, Master Studies, University of Paderborn

Course in PANDA


The complexity of software systems, the evolution of requirements, and the uncertainty of requirements and environments challenge the management of running systems. One promising solution is self-adaptive systems, that is, systems that are able to adapt their behavior in response to changing and uncertain requirements and environments. To realize self-adaptive systems, software engineering activities such as software evolution and maintenance are automated and shifted to the runtime environments of such systems. In recent research, (machine) learning and optimization techniques are leveraged to realize such self-adaptation while facing the challenge of providing assurances for such dynamic systems operating in uncertain environments.

In this seminar, we will discuss recent research on learning, optimization, and assurances for self-adaptive systems.

Topics will be announced in PANDA.

General Literature

  • Weyns, Danny (2020). An Introduction to Self-adaptive Systems: A Contemporary Software Engineering Perspective. Wiley
  • de Lemos, R., Garlan, D., Ghezzi, C., Giese, H. (Eds.) (2017). Software Engineering for Self-Adaptive Systems III. Assurances. Springer
  • de Lemos, R., Giese, H., Müller, H., Shaw, M. (Eds.) (2013). Software Engineering for Self-Adaptive Systems II. Springer.
  • Cheng, B.H.C., de Lemos, R., Inverardi, P., Magee, J. (Eds.). (2009) Software Engineering for Self-Adaptive Systems. Springer.