HOW CAN I SET UP CONTINUOUS INTEGRATION FOR AUTOMATED TESTING

Continuous integration (CI) is a development practice that requires developers to integrate code into a shared repository several times a day. Each check-in is then verified by an automated build, allowing teams to detect problems early. Setting up CI enables automated testing to run with every code change, catching bugs or issues quickly.

To set up CI, you will need a source code repository to store your code, a CI server to run your builds, and configuration to integrate your repository with the CI server. Some popular open source options are GitHub for the repository and Jenkins, GitLab CI, or Travis CI for the CI server. You can also use hosted CI/CD services that provide these tools together.

The first step is to store your code in a version control repository like GitHub. If you don’t already have one, create a new repository and commit your initial project code. Make sure all developers on the team have push/pull access to this shared codebase.

Next, you need to install and configure your chosen CI server software. If using an on-premise solution like Jenkins, install it on a build server machine following the vendor’s instructions. For SaaS CI tools, sign up and configure an account. During setup, connect the CI server to your repository via its API so it can detect new commits.

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Now you need to set up a continuous integration pipeline – a series of steps that will run automated tests and tasks every time code is pushed. The basic pipeline for automated testing includes:

Checking out (downloading) the code from the repository after every push using the repository URL and credentials configured earlier. This fetches the latest changes.

Running automated tests against the newly checked out code. Popular unit testing frameworks include JUnit, Mocha, RSpec etc depending on your language/stack. Configure the CI server to execute npm test, ./gradlew test etc based on your project.

Reporting test results. Have the CI server publish success/failure reports to provide feedback on whether tests passed or failed after each build.

Potentially deploying to testing environments. Some teams use CI to also deploy stable builds to testing systems after tests pass, to run integration or UI tests.

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Archiving build artifacts. Save logs, test reports, packages/binaries generated by the build for future reference.

Email notifications. Configure the CI server to email developers or operations teams after each build with its status.

You can define this automated pipeline in code using configuration files specific to your chosen CI server. Common formats include Jenkinsfile for Jenkins, .travis.yml for Travis etc. Define stages for the steps above and pin down the commands, scripts or tasks required for each stage.

Trigger the pipeline by making an initial commit to the repository that contains the configuration file. The CI server should detect the new commit, pull the source code and automatically run your defined stages one after the other.

Developers on the team can now focus on development and committing new changes without slowing down to run tests manually every time. As their commits are pushed, the automated pipeline will handle running tests without human involvement in between. This allows for quicker feedback on issues and faster iterations.

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Some additional configuration you may want to add includes:

Caching node_modules or other dependencies between builds for better performance

Enabling parallel job execution to run unit/integration tests simultaneously

Defining environments and deploy stages to provision and deploy to environments like staging automatically after builds

Integrating with slack/teams for custom notifications beyond email

Badge status widgets to showcase build trends directly on READMEs

Gating deployment behind all tests passing to ensure quality

Code quality checks via linters, static analysis tools in addition to tests

Versioning and tagging releases automatically when builds are stable

Continuous integration enables teams to adopt test-driven development processes through automation. Bugs are found early in the commit cycle rather than late. The feedback loop is tightened and iteration speeds up considerably when testing happens seamlessly with every change. This paves the way for higher code quality, fewer defects and faster delivery of working software.

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