Dr. rer. nat. Chico Sundermann

I joined the ISF as a postdoc in 2025 after receiving my PhD from the University of Ulm. My research focuses on configurable systems and automated reasoning. Hereby, one of the main goals of my research is tackling scalability issues for complex analyses in practice.

Research Interests

Knowledge Compilation

Many analyses relevant in the context of configurable systems rely on numerous (potentially millions in pracftice) complex operations.  With knowledge compilation, the original format is translated with an initial effort to a target format that allows more efficient reasoning for subsequent operations. However, many challenges arise when trying to apply knowledge compilation in practice. In my research, I aim to identify promising target formats, develop efficient algorithms to compile into the formats, and reduce practice-relevant analyses to operations on the formats.

Featured Publications:

• Chico Sundermann, Heiko Raab, Tobias Heß, Thomas Thüm, and Ina Schaefer. 2024. Reusing d-DNNFs for Efficient Feature-Model Counting. TOSEM. https://doi.org/10.1145/3680465
• Chico Sundermann, Jacob Loth, and Thomas Thüm. 2024. Efficient Slicing of Feature Models via Projected d-DNNF Compilation. ASE '24. https://doi.org/10.1145/3691620.3695594
• Chico Sundermann, Elias Kuiter, Tobias Heß, Heiko Raab, Sebastian Krieter, Thomas Thüm. 2023. AMAI. https://doi.org/10.1007/s10472-023-09906-6

Configuration Counting

In practice, many analyses for configurable systems rely on knowing the number of valid configurations induced by the system (aka. configuration counting). Internally, the analyses rely on the #SAT problem, which is computationally complex. In my research, I reduce real-world problems to counting operations and develop scalable solutions for configuration counting in different practical settings.

Featured Publication:

• Chico Sundermann. Unleashing the potential of configuration counting for product-line analyses. 2025. Dissertation. https://doi.org/10.18725/OPARU-58985

Variability Languages

To employ automated support when working with configurable systems, researchers and practitioners require to specify dependencies between parts of their systems and serialize the resulting constraint system. With my research on such variability languages, I aim to identify requirements for usage in practice, provide a design for widely applicable language, and foster a reusable tool ecosystem. In cooperation with researchs from across the globe, we developed the Universal Variability Language (UVL), a community effort towards a unified format for specifying variability models.

Featured Publication:  

• David Benavides, Chico Sundermann, Kevin Feichtinger, José A. Galindo, Rick Rabiser, Thomas Thüm. 2025. UVL: Feature modelling with the Universal Variability Language. JSS. https://doi.org/10.1016/j.jss.2024.112326