OBDDimal

The goal of the project "Optimal Binary Decision Diagrams for Information Visualization, Model Analysis, and Logic Operations" (OBDDimal, for short) focuses at its core on improving the scalability of binary decision diagrams (BDDs) and related data structures. Domains which would benefit from an increase in scalability are, among others, information visualization (e.g., interactive configurators), model analysis (e.g., feature-model analysis, static code analysis), and logic operations in general (e.g., negation of CNFs).

Student Members, Workers, and Projecteers

B.Sc. Sean Duft
B.Sc. Niklas Hoehne
B.Sc. Konstantin Kistner
B.Sc. Daniel Klier
M.Sc. Eric Langenbucher
B.Sc. Marc Lukas
M.Sc. Tobias Müller
B.Sc. Timo Netzer
B.Sc. Jonas Otto

Publications & Theses

Publications

2021

T. Heß, C. Sundermann and T. Thüm, "On the Scalability of Building Binary Decision Diagrams for Current Feature Models" in Proc. Int'l Systems and Software Product Line Conf. (SPLC), New York, NY, USA: ACM, Sep. 2021, pp. 131-135.

DOI:	10.1145/3461001.3474452
ISBN:	9781450384698
Datei:	https://github.com/SoftVarE-Group/Papers/raw/main/2021/2021-SPLC-Hess.pdf

Theses

2022

K. Kistner, "Survey and Evaluation of Dynamic Variable Ordering Heuristics for the Construction of Binary Decision Diagrams", Bachelor's Thesis, University of Ulm, Germany, Jan. 2022.