Automating Unit Test Coverage in Microservices with Cloving CLI

In a microservices architecture, each service is independently developed and deployed, but managing consistent unit test coverage across all these services can be challenging. Cloving CLI – an AI-powered command-line tool – streamlines this process, automatically generating tests and providing intelligent insights. In this post, we’ll discuss how to use Cloving to maintain and enhance unit test coverage for your microservices, ensuring high code quality and reliability.

1. Introducing Cloving CLI

Cloving CLI acts as an AI-driven pair programmer, helping you:

• Generate code and test stubs
• Review existing code for potential improvements
• Interact with an AI chat for clarifications or iterative code refinement
• Manage commits and more, all integrated into your existing workflow

By understanding your project context, Cloving aims to produce relevant tests and code suggestions tailored to your architecture.

2. Setting Up Cloving

2.1 Installation

Use npm to install Cloving globally:

npm install -g cloving@latest

2.2 Configuration

Next, configure Cloving with your API key and AI model preferences:

cloving config

Follow the prompts to enter your credentials. Cloving can then connect to the AI backend to generate code and insights suitable for your codebase.

3. Initializing Your Microservices Project

3.1 Project Setup

In a microservices environment, each service often lives in its own repository or subfolder. For Cloving to better understand each service’s structure, run:

cloving init

… inside the root directory of each microservice. This command creates a cloving.json file containing metadata that helps Cloving deliver more accurate code generation and tests.

3.2 Organization

Maintain consistent organization across microservices, e.g.:

services/
  auth-service/
    src/
    test/
    cloving.json
  order-service/
    src/
    test/
    cloving.json
  ...

This structure ensures each service is separate, and Cloving can adapt to each codebase’s context individually.

4. Automating Unit Test Generation

4.1 Example: Generating Tests for Utility Functions

Let’s say you’re working within a Node.js microservice that includes utility functions:

cd auth-service
cloving generate unit-tests -f utils/authUtils.ts utils/dbUtils.ts

Sample Output:

// utils/authUtils.test.ts
import { generateToken, verifyToken } from './authUtils';

describe('authUtils', () => {
  test('generateToken creates a valid token', () => {
    const token = generateToken({ userId: '123' });
    expect(typeof token).toBe('string');
  });

  test('verifyToken decodes a valid token', () => {
    const token = generateToken({ userId: '123' });
    const payload = verifyToken(token);
    expect(payload.userId).toBe('123');
  });
});

Notes:

• Cloving references your existing code to produce relevant test cases.
• If your utilities rely on environment variables or external services, mention these in your prompt for more targeted tests.

4.2 Integrating with a CI/CD Pipeline

In a microservices architecture, each service is updated independently. Integrating the cloving generate unit-tests command into your CI/CD pipeline ensures that whenever new code is merged, Cloving automatically regenerates or updates tests as needed.

5. Validating and Integrating Tests

5.1 Reviewing Generated Tests

After generating tests, check them in your editor or terminal:

npm test

Look for opportunities to refine coverage, e.g.:

• Error handling scenarios
• Edge cases (like invalid inputs or network issues)
• Async flows (if your functions rely on external APIs)

5.2 Maintaining Consistency

If your microservices use different test frameworks (e.g., Jest, Mocha), mention this in your Cloving prompts or place a sample test in each codebase so Cloving knows which style to follow.

6. Refining Tests with Cloving Chat

For complex scenarios or more advanced test requirements, use Cloving’s interactive chat:

cloving chat -f utils/authUtils.ts

Inside the chat session, you can:

• Ask how to expand coverage for corner cases
• Request code changes or test enhancements
• Seek clarity on the best way to mock or stub external dependencies

Example:

cloving> Please add negative tests where generateToken handles invalid payloads

Cloving might then produce additional tests covering scenarios like null payloads or missing data.

7. Ensuring Consistent Test Coverage

7.1 Revisit Tests Regularly

Because microservices evolve independently, you should re-run Cloving’s test generation whenever new features or significant refactors occur:

cloving generate unit-tests -f src/newFeature.ts

This step helps maintain coverage parity with code changes across the entire microservices ecosystem.

7.2 Pair with Coverage Tools

Combine Cloving with coverage tools like Istanbul or nyc to measure coverage:

nyc npm test

Compare coverage reports across your microservices to identify modules requiring more thorough testing. If you see a gap, run Cloving again with a relevant prompt.

8. Best Practices

1. Initialize Each Microservice
   Running cloving init in each microservice ensures Cloving has the correct context per service.

2. Modular Testing
   If microservices are truly separate, keep test code within each service’s repository. Avoid mixing across services to maintain independence.

3. Short, Specific Prompts
   When generating tests, mention the function or scenario. e.g., “Generate unit tests for calculating user quotas in userQuotaUtils.ts”.

4. Iterative Chat
   For advanced or unusual logic (e.g. domain-specific encryption, complex dependency injection), rely on cloving chat for iterative test refinements.

5. CI Integration
   You can incorporate cloving generate unit-tests in your build scripts, automatically generating or updating tests whenever code changes are pushed.

9. Example Workflow

Below is a simplified blueprint of how you might integrate Cloving in your microservices test strategy:

1. Initialize: In each service folder, cloving init.
2. Generate/Update Tests: cloving generate unit-tests -f utils/dbUtils.ts
3. Review & Run: Inspect or refine tests, run npm test to confirm.
4. Chat: Use cloving chat -f utils/dbUtils.ts for deeper clarifications or expansions.
5. Commit: Let Cloving propose commit messages with cloving commit.
6. CI/CD: In your pipeline, automatically regenerate or refine tests on code changes, ensuring continuous coverage.

10. Conclusion

The Cloving CLI provides a powerful way to automate and standardize test coverage across your microservices. Its AI-driven approach cuts down the time spent writing repetitive unit tests, freeing developers to focus on logic, architecture, and business needs.

Remember: Cloving’s generated tests are a foundation. Expand them as needed for negative cases, integration tests, or specialized domain logic. By regularly integrating Cloving into your development pipeline, you can ensure that each microservice remains thoroughly tested and that your entire microservices architecture upholds a high standard of reliability.