In 2021, the task area Betty has been focussing on three main topics related to research software: quality assurance, reproducibility and findability. Our vision is that the engineering sciences produce validated, high-quality software, that can be found and reused by other researchers in their own research. To make research software findable, we have laid out the concept for a service that allows users to specifically search for research software repositories using domain-specific terms, as e.g. an algorithm or a mathematical method. The service is anticipated to go live at some point in 2022.
Computational research often involves a series of different tasks, performed by different pieces of software that have to be executed in a particular order, passing the data produced by one task as input to a subsequent task. In order for research to be reproducible, it is beneficial if this process is automated and made publicly available. Therefore, we have initiated the Special Interest Group „Tools for describing, reproducing and reusing scientific workflows“, in which we are currently evaluating a number of workflow languages and tools regarding their usefulness to be employed in research, focusing on measures such as ease-of-use, composability, capabilities of encapsulating the required software environments and support for HPC (High-Performance- Computing) environments. The documentation of this project is provided in a public git repository at https://github.com/BAMresearch/NFDI4IngScientificWorkflowRequirements.
Finally, we are thinking about means to facilitate quality assurance for researchers that write software. Our focus so far has been on research software that is used to carry out simulations of physical processes, which is a wide-spread use case in the engineering sciences. For such code bases, regression tests provide an easy means of testing the software by using small simulations as tests, comparing the results against reference solutions that were obtained beforehand. In order to help researchers to use this technique, we are currently developing a Python framework that provides the tools required to compare simulation results, and which supports a wide range of standard file formats. At the same time, we are developing a small C++ library that researchers can use in their code to write the simulation data obtained with their own methods and data structures into these standard file formats.
[Betty has 3 items on her scientific dissemination list 2021]