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A library to implement Software Quality Assurance (SQA) checks in Jenkins environments

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Motivation

The v2 series of the present library provide a straightforward way for software projects to be compliant with common SQA practices.

In particular, the library provides the functionality to cover as much criteria as possible from the Software and Service quality baselines below:

Short intro

The SQA requirements are defined through a YAML-based configuration file that hides the complexity of handling directly the Jenkins Pipeline as Code's features. As a result, the SQA work, as defined in the YAML file config.yml, is organized according to the criteria code names from the aforementioned baselines.

As an example, qc_style setting in the YAML is a direct reference to the QC.Sty criteria in the previous software quality baseline, which establishes the good practices that the source code shall follow in terms of style. The following example runs flake8 to check style consistency in a Python project:

sqa_criteria:
  qc_style:
    container: python-test-tools
    commands:
      - flake8

As it can be seen in the example, the library provides the container option as a way to specify the agent where the check will run. In the current version, the library supports Docker Compose as the container orchestration tool to fire up the required set of services. In this example, the python-test-tools is the identifier of a Docker Compose service.

You can check a full working example here

In order to get started with the library, please check our documentation.

Contributing

Jenkins CI/CD pipelines are often similar in the type of actions that are triggered. It then makes sense to have a common library for tackling them, covering different programming languages and interfaces to software lifecycle management tools.

Contributions are really welcome. Please check our contribution guidelines.

License

License

indigo-dc/jenkins-shared-library is licensed under Apache 2.0

Acknowledgments

The development of the v2 series is taking place under the EOSC-Synergy's project that has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement number 857647.