Tutorial / Cram Notes

Automating unit tests and code coverage is a foundational practice for any DevOps team aiming to improve its software development lifecycle, and it’s especially relevant for those preparing for the AWS Certified DevOps Engineer – Professional exam.

Unit tests are the first line of defense in ensuring code quality. They are designed to test individual components of the code to verify that each part is working correctly. Automating these tests means they are run consistently without manual intervention, often as part of Continuous Integration (CI) pipelines.

Code coverage, on the other hand, is a measure used to describe the degree to which the source code of a program is tested by the automated tests. It provides an indication of how much of the codebase the tests are exercising and is typically expressed as a percentage.

AWS services such as AWS CodeBuild and AWS CodePipeline can be utilised to automate unit tests and track code coverage. Here’s how they can be integrated into a CI/CD workflow:

AWS CodeBuild

AWS CodeBuild is a fully managed build service that compiles source code, runs tests, and produces software packages that are ready to deploy. It can be configured to automatically run unit tests every time code is pushed to a repository.

To set up unit testing with CodeBuild, define a buildspec.yml file in your repository root, detailing the commands for running tests and generating code coverage reports. Here’s a simplified example of a buildspec.yml file that installs dependencies, runs unit tests, and generates a coverage report:

version: 0.2

phases:
install:
commands:
– echo Installing dependencies…
– npm install
pre_build:
commands:
– echo Running tests…
build:
commands:
– npm test
– npm run coverage
artifacts:
files:
– ‘/*’
reports:
codecoverage:
files:
– ‘path/to/coverage/report’

In this example, npm test might run the unit tests, and npm run coverage might generate a code coverage report. Both commands would be defined in the project’s package.json file.

AWS CodePipeline

AWS CodePipeline is a continuous delivery service that automates the build, test, and deploy phases of the release process. It can work with AWS CodeBuild to run unit tests and report on code coverage.

To integrate CodeBuild with CodePipeline:

  1. Create a new pipeline in CodePipeline and add a source stage that specifies the version control system to monitor for code commits.
  2. Add a build stage and select the previously configured AWS CodeBuild project as the build provider. CodeBuild will now run according to the buildspec.yml when the pipeline executes.
  3. Following the build stage, add a deploy stage if you want to deploy your code to an AWS service such as AWS Elastic Beanstalk or Amazon EC2.

Code Coverage Reporting

Once CodeBuild runs your tests, you will want to view the code coverage results. AWS CodeBuild integrates with several code coverage reporting tools like Jacoco, Cobertura, and Clover.

Here’s an example outline of steps to send the code coverage reports to a reporting tool:

  1. Configure your test runner to generate code coverage reports. This is typically done in the build or testing tool configuration.
  2. Update the buildspec.yml to specify the location of the output code coverage reports.
  3. Use AWS CodeBuild’s built-in reporting features to process the code coverage report files and send them to the reporting tool.
  4. Optionally, define alarms or triggers based on the code coverage metrics using AWS CloudWatch.

In terms of reporting and tracking progress, many teams set goals for code coverage percentages. For example, a team might aim for at least 80% of their code to be covered by unit tests. Tools like CodeClimate or SonarQube can also be integrated with AWS services to provide detailed code quality and coverage insights.

Benefits of Automating Unit Tests and Code Coverage

Benefit Description
Consistency Automated tests are run the same way every time, eliminating variance.
Speed Tests run quickly and provide immediate feedback on code changes.
Reliability Reduces the chance of human error affecting test outcomes.
Improved Quality Helps ensure that new code doesn’t break existing functionality.
Continuous Improvement Regular testing tracks progress over time and highlights areas for improvement.

Automating unit tests and code coverage is not just about ensuring that code works. It is a core principle within the DevOps philosophy of continuous integration, constant feedback, and high-quality software delivery. Understanding these concepts is critical for any aspiring AWS Certified DevOps Engineer – Professional.

Practice Test with Explanation

True or False: AWS CodeBuild automatically generates a code coverage report for each build.

  • True
  • False

Answer: False

Explanation: AWS CodeBuild compiles source code, runs tests, and produces software packages. Code coverage reports are not automatically generated; they need to be set up using tools like JaCoCo for Java or coverage.py for Python.

In AWS, which service can be used to automate unit tests execution for your application?

  • AWS CodeDeploy
  • AWS CodePipeline
  • AWS CodeCommit
  • AWS CodeBuild

Answer: AWS CodeBuild

Explanation: AWS CodeBuild is used to compile the source code, run unit tests, and produce artifacts that are ready to deploy, whereas AWS CodePipeline automates the build, test, and deploy phases of your release process.

True or False: AWS CodePipeline allows you to define different stages for building and testing your source code.

  • True
  • False

Answer: True

Explanation: AWS CodePipeline allows you to model the various stages of your software release process including build, test, and deployment.

When using AWS CodeBuild, which file do you configure to define how the unit tests should be run?

  • buildspec.yml
  • dockerfile
  • codespec.json
  • pipeline.yml

Answer: buildspec.yml

Explanation: In AWS CodeBuild, the buildspec.yml file is used to define build commands and settings, such as the commands to run unit tests.

Which of the following AWS CLI commands is used to trigger a build in AWS CodeBuild?

  • aws codebuild start-build
  • aws codebuild run-build
  • aws codecommit trigger-build
  • aws codepipeline start-build

Answer: aws codebuild start-build

Explanation: The ‘aws codebuild start-build’ CLI command is used to start running a build in AWS CodeBuild.

True or False: In AWS, integrating unit tests and code coverage into a CI/CD pipeline ensures that you can automatically catch issues before they make it to production.

  • True
  • False

Answer: True

Explanation: Integrating unit tests and code coverage into a CI/CD pipeline allows for automatic detection of issues early in the development cycle, before code is deployed to production.

Which AWS service provides a managed source control service that hosts Git-based repositories and can be integrated with automated testing and deployment services?

  • AWS CodeBuild
  • AWS CodeDeploy
  • AWS CodePipeline
  • AWS CodeCommit

Answer: AWS CodeCommit

Explanation: AWS CodeCommit is a managed source control service that hosts Git-based repositories and can integrate with continuous integration and continuous delivery services like AWS CodeBuild and AWS CodePipeline.

What is the purpose of the ‘post_build’ phase in a CodeBuild buildspec file?

  • To run unit tests
  • To clean up resources
  • To execute commands after the build phase is completed
  • To set environmental variables

Answer: To execute commands after the build phase is completed

Explanation: The ‘post_build’ phase is used to define commands that are run after the build phase is completed, such as commands to run unit tests or commands for deploying code.

True or False: AWS CodeStar provides a unified interface for managing software development activities including code commits, builds, and deployments, but it does not support unit testing.

  • True
  • False

Answer: False

Explanation: AWS CodeStar is a unified user interface that manages software development activities, including continuous integration and continuous delivery (CI/CD). It integrates with AWS CodeBuild and other services, thereby supporting unit testing.

What type of testing ensures that the smallest parts of an application, the units, are individually and independently scrutinized for proper operation?

  • Integration testing
  • Smoke testing
  • Unit testing
  • System testing

Answer: Unit testing

Explanation: Unit testing involves the testing of individual components or units of a software to ensure each unit functions correctly independently.

Interview Questions

Can you describe the benefits of automating unit tests in a continuous integration/continuous deployment (CI/CD) pipeline?

Automating unit tests ensures that code changes are validated for functionality, performance, and compliance against expected results in real-time. It ensures a reliable and repeatable testing process, which is essential for CI/CD pipelines. Automated tests reduce manual effort, increase test coverage, and help to detect and resolve issues early in the development cycle, leading to improved code quality and faster release cycles.

How does code coverage differ from unit testing, and why is it important to measure code coverage?

Unit testing involves writing tests to verify the functionality of individual units of code, while code coverage measures the extent to which the codebase is exercised by the unit tests. It is important because it provides insights into potentially untested parts of the code, allowing developers to write additional tests to improve the quality and robustness of the software.

What AWS tools can be utilized to automate unit tests and measure code coverage, and how do they integrate with a CI/CD pipeline?

AWS CodeBuild and AWS CodePipeline are two key services for automating unit tests and measuring code coverage. AWS CodeBuild can run unit tests and generate code coverage reports as part of the build process, while AWS CodePipeline orchestrates the overall CI/CD workflow, including triggering CodeBuild actions. Integration with these services aids in automating the entire build-test-deploy cycle.

In AWS, how can you ensure that code changes do not get deployed unless certain code coverage thresholds are met?

By integrating tools like CodeBuild with AWS CodePipeline, you can enforce rules in the buildspec.yml file that set conditions for passing the build phase based on code coverage metrics. If the coverage threshold is not met, CodeBuild can fail the build causing the pipeline to stop, preventing deployment until the code coverage is improved.

Can you explain what is meant by “test-driven development” (TDD)? How does it relate to unit testing?

Test-driven development is a software development approach where tests are written before the actual code. Developers write unit tests for a new function or feature before implementing it, ensuring it meets the specified requirements. This process is iterative, enhancing the code quality through continuous refactoring and validating against predefined tests.

What is a “mock” in unit testing, and when would you use it?

A mock is a simulated object that mimics the behavior of real objects in controlled ways. Mocks are used in unit testing when you need to isolate the unit of code being tested from its external dependencies, allowing you to test the unit’s functionality without any side effects from the other parts of the system.

Explain how you can use AWS CodeCommit along with other AWS services to automate unit testing.

AWS CodeCommit is a managed source control service that hosts Git repositories. It can be integrated with AWS CodeBuild to automatically trigger the execution of unit tests every time code is pushed to a repository. This creates an automated process where new commits are continuously tested, ensuring that the codebase remains in a deployable state.

Describe how you can utilize AWS CloudWatch along with testing tools for monitoring code coverage over time.

AWS CloudWatch can be used to monitor and log custom metrics from code coverage tools. By using CloudWatch Alarms, developers can be notified if the code coverage falls below a certain threshold. These metrics can be used to track and improve code coverage trends over time to maintain or improve software quality.

What are some industry-standard tools for measuring code coverage, and how would you integrate them with AWS services?

Industry-standard tools for measuring code coverage include JaCoCo for Java, Istanbul for JavaScript, and coverage.py for Python. These tools can be used within the build process managed by AWS CodeBuild, and the results can be exported to Amazon S3 for storage or used to trigger other actions within AWS CodePipeline depending on the coverage results.

How can you automate unit testing and code coverage for serverless applications deployed using AWS Lambda?

To automate unit testing and code coverage for AWS Lambda functions, you can use AWS CodeBuild to execute test suites as part of the build stage. The SAM CLI (Serverless Application Model Command Line Interface) can also be used to invoke Lambda functions locally or in the cloud during the test phase. Code coverage results can be published using CodeBuild reporting or third-party services integrated with the AWS ecosystem.

What is branch coverage, and how does it relate to unit testing in a CI/CD pipeline?

Branch coverage is a metric that measures the coverage of all the possible paths (branches) in the code, such as if/else statements and loops. It’s more thorough than line coverage because it ensures that each branch condition is tested. In a CI/CD pipeline, branch coverage can be measured as part of the automated testing to ensure more comprehensive testing before deployments.

How can you implement a strategy for an incremental increase in code coverage within an AWS CI/CD pipeline?

You can define a code coverage goal and use AWS CodeBuild or other integrated tools to measure the coverage on each build. By setting incremental goals for each release, developers can be guided to write additional tests for the poorly covered code. A build failure can be triggered if the incremental goal is not met, ensuring attention is placed on writing better tests and gradually increasing the overall coverage.

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مهراد قاسمی

The section on automating unit tests with AWS CodeBuild was very insightful.

Ellen Baker
6 months ago

Thanks for the post! The examples were very helpful.

Silas Meunier
6 months ago

The integration of AWS CodePipeline with CodeBuild for automated testing and deployment was well-explained.

Tommy Thomas
6 months ago

Can someone explain how to configure AWS CodeBuild to trigger unit tests on each code commit?

Björn Laurent
5 months ago

The tutorial is good, but it could use more examples on real-world scenarios.

Gabriela Vidal
6 months ago

For code coverage, is it better to use AWS CodeBuild or integrate a third-party tool like SonarQube?

Pilar Gil
6 months ago

Great content as always. Thanks!

Gerfried Schott
6 months ago

How do you handle environment variables securely in AWS CodePipeline and CodeBuild?

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