The Next Generation of Metadata-Oriented Testing of Research Software

TL;DR

This paper discusses advanced metadata-oriented testing methods for research software, emphasizing data-driven approaches to improve system robustness and maintainability amid increasing complexity and evolving codebases.

Contribution

It introduces novel testing strategies that leverage metadata to enhance testing effectiveness and system adaptability in research software environments.

Findings

Metadata-based testing improves fault detection.

Data-driven testing simplifies maintenance.

Enhanced testing regimes increase system robustness.

Abstract

Research software refers to software development tools that accelerate discovery and simplifies access to digital infrastructures. However, although research software platforms can be built increasingly more innovative and powerful than ever before, with increasing complexity there is a greater risk of failure if unplanned for and untested program scenarios arise. As systems age and are changed by different programmers the risk of a change impacting the overall system increases. In contrast, systems that are built with less emphasis on program code and more emphasis on data that describes the application can be more readily changed and maintained by individuals who are less technically skilled but are often more familiar with the application domain. Such systems can also be tested using automatically generated advanced testing regimes.