Conception of a digital Sales Bonus System based on Blockchain Technology
N. N., Conception of a Digital Sales Bonus System Based on Blockchain Technology, 2019.

Textaufgaben lesen und verstehen lernen – Entwicklungsforschungsstudie zur mathematikspezifischen Leseverständnisförderung
J. Dröse, Textaufgaben lesen und verstehen lernen – Entwicklungsforschungsstudie zur mathematikspezifischen Leseverständnisförderung, Springer Spektrum, Heidelberg, 2019.

Scaffolding für fachbezogene textsortenspezifische Lesestrategien – Entwicklungsforschungsstudie zur Förderung des Umgangs mit Textaufgaben
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Know your analysis: how instrumentation aids understanding static analysis
P. Schubert, R. Leer, B. Hermann, E. Bodden, in: Proceedings of the 8th ACM SIGPLAN International Workshop on State Of the Art in Program Analysis  - SOAP 2019, 2019.

Frühe mathematische Bildung im elementarpädagogischen Alltag
J. Bruns, L. Eichen, KiTa aktuell Österreich 7 (2019) 85–86.

VimaS_num: Measuring situational perception in mathematics of early childhood teachers
J. Bruns, H. Gasteiger, in: M. Graven, H. Venkat, A. Essien, P. Vale (Eds.), Proceedings of the 43rd Conference of the International Group for the Psychology of Mathematics Education, 2019, pp. 129–136.

Mathematical pedagogical content knowledge of early childhood teachers: a standardized situation-related measurement approach
H. Gasteiger, J. Bruns, C. Benz, E. Brunner, P. Sprenger, ZDM 52 (2019) 193–205.

Mathematikdidaktischen Wissen von frühpädagogischen Fachkräften aus kognitiv-situationsbezogener Perspektive – Theoretisches Konstrukt und empirische Erfassung
J. Bruns, H. Gasteiger, in: A. Frank, S. Krauss, K. Binder (Eds.), Beiträge zum Mathematikunterricht 2019, WTM-Verlag,  Münster, 2019, pp. 169–172.

Selbst erstellte Skizzen beim mathematischen Modellieren: Ergebnisse einer empirischen Untersuchung [Self-generated drawings for modelling problems: Findings of an empirical study]
J. Schönherr, Selbst erstellte Skizzen beim mathematischen Modellieren: Ergebnisse einer empirischen Untersuchung [Self-generated drawings for modelling problems: Findings of an empirical study], Springer Spektrum, Wiesbaden, 2019.

Implementing a Real-time System on a Platform FPGA operated with ReconOS
C. Lienen, Implementing a Real-Time System on a Platform FPGA Operated with ReconOS, Universität Paderborn, n.d.

A General Algorithm to Calculate the Inverse Principal p-th Root of Symmetric Positive Definite Matrices
D. Richters, M. Lass, A. Walther, C. Plessl, T. Kühne, Communications in Computational Physics 25 (2019) 564–585.

FPGAs im Rechenzentrum
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Bi-Objective Orienteering: Towards a Dynamic Multi-Objective Evolutionary Algorithm
J. Bossek, C. Grimme, S. Meisel, G. Rudolph, H. Trautmann, in: K. Deb, E. Goodman, C.C.A. Coello, K. Klamroth, K. Miettinen, S. Mostaghim, P. Reed (Eds.), Evolutionary Multi-Criterion Optimization (EMO), Springer International Publishing, East Lansing, Michigan, USA, 2019, pp. 516–528.

Multimodality in Multi-Objective Optimization — More Boon than Bane?
C. Grimme, P. Kerschke, H. Trautmann, in: K. Deb, E. Goodman, C.C.A. Coello, K. Klamroth, K. Miettinen, S. Mostaghim, P. Reed (Eds.), Proceedings of the 10$^th$ International Conference on Evolutionary Multi-Criterion Optimization (EMO), Springer, East Lansing, MI, USA, 2019, pp. 126–138.

Automated Algorithm Selection: Survey and Perspectives
P. Kerschke, H.H. Hoos, F. Neumann, H. Trautmann, Evolutionary Computation (ECJ) 27 (2019) 3–45.

Evolving Diverse TSP Instances by Means of Novel and Creative Mutation Operators
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Multi-Objective Performance Measurement: Alternatives to PA and Expected Running Time
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Optimizing Data Stream Representation: An Extensive Survey on Stream Clustering Algorithms
M. Carnein, H. Trautmann, Business and Information Systems Engineering (BISE) 61 (2019) 277–297.

A Recommender System Based on Omni-Channel Customer Data
M. Carnein, L. Homann, H. Trautmann, G. Vossen, in: Proceedings of the 21$^st$ IEEE Conference on Business Informatics (CBI’ 19), Moscow, Russia, 2019, pp. 65–74.

Customer Segmentation Based on Transactional Data Using Stream Clustering
M. Carnein, H. Trautmann, in: Proceedings of the 23$^rd$ Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD ’19), Macau, China, 2019, pp. 280–292.