Mathematical Research Software Engineering (RSEng) is an interface discipline linking mathematics, software engineering and open science dedicated to the development and application of software engineering practices and tools in the context of mathematical research.

Publications

  Articles in Refereed Journals

  • P.C. Africa, D. Arndt, W. Bangerth, B. Blais, M. Fehling, R. Gassmöller, T. Heister, L. Heltai, S. Kinnewig, M. Kronbichler, M. Maier, P. Munch, M. Schreter-Fleischhacker, J.P. Thiele, B. Turcksin, D. Wells, V. Yushutin, The deal.II library, Version 9.6, Journal of Numerical Mathematics, 32 (2024), pp. 0137/1--0137/10, DOI 10.1515/jnma-2024-0137 .
    Abstract
    This paper provides an overview of the new features of the finite element library deal.II, version 9.6.

  Talks, Poster

  • J. Fuhrmann, The Julia language: Reproducibility infrastructure and project workflows, Leibniz MMS Days 2025, March 26 - 28, 2025, The Leibniz Research Network "Mathematical Modeling and Simulation", Leibniz Institute for Baltic Sea Research Warnemünde (IOW), March 28, 2025.

  • P. Jaap, WIAS-PDELib: AJulia PDE solver ecosystem in a GitHub organization, deRSE25 - 5th conference for Research Software Engineering in Germany, February 25 - 27, 2025.

  • J.P. Thiele, Easy to use tools for software quality, Leibniz MMS Days 2025, March 26 - 28, 2025, The Leibniz Research Network "Mathematical Modeling and Simulation", Leibniz Institute for Baltic Sea Research Warnemünde (IOW), March 27, 2025.

  • J.P. Thiele, Software Engineering for and with Reserchers: What is required?, deRSE25 - 5th conference for Research Software Engineering in Germany, February 25 - 27, 2025, Karlsruher Institut für Technologie, February 26, 2025.

  • J. Fuhrmann, J.P. Thiele, Erfahrungen mit Softwarelizenzierung und Transfer am WIAS, Leibniz Open Transfer Workshop, Leibniz Gemeinschaft, June 5, 2024.

  • J.P. Thiele, RSE / PostDoc am WIAS, PhoenixD Research School für Promovierende, Exzellenzcluster PhoenixD, Leibniz Universität Hannover, April 4, 2024.

  • J.P. Thiele, RSE and RDM: Code and perish?! How about publishing your software (and data)?, Oberseminar Numerik und Optimierung, Institut für Angewandte Mathematik, Leibniz Universität Hannover, May 2, 2024.

  • J.P. Thiele, RSE training and professional development BoF, Research Software Engineering Conference, RSECon24, September 3 - 5, 2024, Society of Research Software Engineering (SocRSE), a charitable incorporated organisation based in the UK, Newcastle, UK, September 5, 2024.

  • J.P. Thiele, The Research Software Engineer (RSE): Who is that? And what skills do they have to help you?, European Trilinos & Kokkos User Group Meeting 2024 (EuroTUG 2024), June 24 - 26, 2024, Helmut-Schmidt-Universität, Universität der Bundeswehr Hamburg, June 24, 2024.

  External Preprints

  • S.M. Allen, N. Chue Hong, S. Druskat, T. Hodges, D.S. Katz, J. Linxweiler, F. Löffler, L. Grunske, H. Seibold, J.P. Thiele, S. Wittke, Ten simple rules for PIs to integrate Research Software Engineering into their research group, Preprint no. 2506.20217, Cornell University, 2025, DOI 10.48550/arXiv.2506.20217 .
    Abstract
    Research Software Engineering (RSEng) is a key success factor in producing high-quality research software [1] and thus improves research project outcomes, since better research software leads to better research [2]. However, as a leader of a research group or project you may not know what RSEng is, or how you can maximize its impact on your research. To make matters worse, if you try to read about RSEng or strike up a conversation about how it might be relevant to your research, you might be met with complicated technical details [3]. Surely, it must be possible to learn what RSEng is about without first enrolling in a Computer Science program at your university! Many explanations and tutorials for development aspects like testing, software architecture and version control are very technical. This prevents researchers and other decision makers from making an informed choice about employing these methods. The result may be research software that is less robust [4] and less usable [5], and research that is less reproducible [6]. In contrast, using fundamental RSEng methods can make code good enough, even when programming needs to be quick and dirty [7]. Our aim is to provide comprehensible descriptions of simple rules to improve software-enhanced research.