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EVERSE TechRadar

This is preliminary work done as part of EVERSE project Technology Watch. It contains a collection of tools and services for research software quality designed to assess, measure, and improve the quality of software developed for research purposes. These tools incorporate features that address the unique requirements of research software, including (but not limited to):

  • Analysis of source code to identify potential issues, vulnerabilities, and adherence to coding standards specific to research contexts.

  • Evaluation of software against research-specific quality attributes such as reproducibility and FAIRness (Findability, Accessibility, Interoperability, and Reusability).

  • Support for community standards and best practices relevant to specific research disciplines.

  • Metrics and measurements tailored to assess both technical aspects and research-oriented factors.

  • Capabilities to analyze and improve software quality throughout the research software lifecycle, from development to long-term sustainability.

These tools aim to enhance the overall quality, reliability, and reusability of research software, ultimately contributing to the reproducibility and impact of scientific research.

The catalog of tools and services is presented in a visual dashboard at https://github.com/EVERSE-ResearchSoftware/TechRadar.

Contributing

We welcome both technical and content contributions.

Please see our contribution guidelines and consider joining the team if you want to add new tools and services in the TechRadar.

Development

Build the TechRadar

npm i
npm run serve

Then open here: http://localhost:3000/techradar

Build with static files

npm i
npm run build

Warning

The work is initial representation and is likely to be changed. The current version of Technology Watch is a work in progress. Any content should not be considered final at this stage.

Funding

EVERSE project is funded by the European Commission HORIZON-INFRA-2023-EOSC-01-02 call.

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EVERSE TechRadar for tools and services for software quality

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  • Python 96.1%
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