Code Coverage in Azure Pipelines

This tutorial will guide you through the process of integrating code coverage reporting into your Azure Pipelines. Understanding code coverage is crucial for ensuring the quality and reliability of your software by identifying which parts of your codebase are exercised by your tests.

Why is Code Coverage Important?

Code coverage is a metric used in software testing that describes the degree to which the source code of a program is executed when a particular test suite runs. High code coverage does not guarantee bug-free software, but it does indicate that a significant portion of your code has been tested. It helps in:

  • Identifying untested code: Pinpoint areas of your application that lack test coverage.
  • Improving test suites: Guide the creation of new tests to cover critical or risky areas.
  • Reducing technical debt: Ensure that older, potentially neglected code is also being tested.
  • Boosting developer confidence: Provide assurance that changes are well-tested.

Steps to Integrate Code Coverage

1. Configure Your Project for Coverage

Before you can collect coverage data, your project needs to be configured to generate it. This typically involves using a code coverage tool specific to your programming language or framework.

  • .NET: Use `dotnet test --collect "Code Coverage"` or configure your project file.
  • Java: Use tools like JaCoCo or Cobertura.
  • Python: Use `coverage.py`.
  • JavaScript: Use Istanbul (often integrated with Jest or other test runners).

Ensure your build process generates coverage reports in a standard format, such as Cobertura or LCOV.

2. Set Up Your Azure Pipeline

In your `azure-pipelines.yml` file, you'll need to include steps to build your project, run your tests (which will generate coverage data), and then publish these reports.

Example using .NET and Coverlet

This example assumes you are using Coverlet for .NET code coverage.


trigger:
- main

pool:
  vmImage: 'windows-latest' # Or your preferred agent image

steps:
- task: DotNetCoreCLI@2
  displayName: 'Build Project'
  inputs:
    command: 'build'
    projects: '**/*.csproj'

- task: DotNetCoreCLI@2
  displayName: 'Run Tests with Coverage'
  inputs:
    command: 'custom'
    customCommand: 'test --configuration $(buildConfiguration) --collect "XPlat Code Coverage"'
    projects: '**/*[Tt]ests/*.csproj' # Adjust path to your test projects

- task: PublishCodeCoverageResults@1
  displayName: 'Publish Code Coverage'
  inputs:
    codeCoverageTool: 'Cobertura' # Or 'Lcov', 'JaCoCo'
    summaryFileLocation: '$(System.DefaultWorkingDirectory)/**/*.cobertura.xml' # Path to your coverage report
    reportDirectory: '$(System.ArtifactsDirectory)/CodeCoverage'

3. Configure the `PublishCodeCoverageResults` Task

The `PublishCodeCoverageResults@1` task is essential for making your code coverage reports visible within Azure DevOps. Key inputs include:

  • codeCoverageTool: Specifies the format of your coverage report (e.g., 'Cobertura', 'Lcov', 'JaCoCo').
  • summaryFileLocation: The path to your coverage summary file. This is where the task looks for the main report data.
  • reportDirectory: An optional directory where the detailed HTML reports will be published as pipeline artifacts.

Viewing Code Coverage Reports

Once your pipeline successfully runs and the `PublishCodeCoverageResults` task completes, you can view the code coverage information directly in the pipeline run summary. Navigate to the 'Test Results' tab of your pipeline run, and you should see a 'Code Coverage' section. You can click on this to view detailed reports, including line-by-line coverage and any uncovered code.

Troubleshooting Common Issues

  • Report Not Found: Double-check the `summaryFileLocation` path. Ensure your tests are actually generating the coverage report in the expected format and location.
  • Incorrect Tool Type: Make sure the `codeCoverageTool` input matches the format of the generated report file.
  • Permissions: Ensure the service connection or agent has the necessary permissions to access and publish artifacts.

By implementing code coverage reporting in your Azure Pipelines, you significantly enhance your understanding of test effectiveness and the overall quality of your codebase.