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Test Strategy for Node.js Service Accessing MySQL Database

NOTE: This text was generated (after some prompting) by ChatGPT. It is a bit over-kill, but I feel ChatGPT has raised good points that in the real-world should be discussed with the team and possibly with the internal customers to gain a beter understanding of the user needs for the application.

Overview

This document outlines a test strategy for a service written in JavaScript, running in Node.js, and interacting with a MySQL database using the MySQL2 driver. The service performs queries and insertions on database tables like the given example.

Preconditions

  • Database Table Example:
ID name create_date amount
1 test 2024-04-23 12.55
  • The service executes SQL queries (SELECT, INSERT) against such tables.

Test Environments

  • Development Environment: Where developers perform their initial tests.
  • Integration Environment: For integrating various system components and running integration tests.
  • Acceptance Environment: For performing acceptance tests that simulate real user scenarios to validate the product against business requirements.

Pipeline Stages

  1. Code Commit: Trigger automated unit tests.
  2. Build: On successful unit tests, the service is built.
  3. Unit Test: Automated tests to ensure individual parts function correctly.
  4. Integration Test: Ensure that the service interacts correctly with the MySQL database.
  5. Acceptance Test: Run scenarios that mimic real-world use.
  6. Deployment: Automated deployment to production on passing all tests.

Testing Types

Unit Testing

  • Objective: Test individual functions for generating and executing SQL queries.
  • Tools: Use frameworks like Mocha or Jest for testing.
  • Test Cases:
  • TC1: Function returns correct SQL query for given parameters.

Integration Testing

  • Objective: Ensure that the service interacts correctly with the MySQL database.
  • Tools: Use the test instance of the MySQL database.
  • Test Cases:
  • TC2: SELECT * FROM test_table returns correct data.
  • TC3: Insert operation adds new record into the database.

Acceptance Testing

  • Objective: Validate the service against business requirements.
  • Tools: Simulate real user environment.
  • Test Cases:
  • TC4: Service handles a mix of simultaneous select and insert operations.

Risk Analysis

  • High:
  • Data corruption due to concurrent writes.
  • Medium:
  • Performance issues under load.
  • Low:
  • Minor delays in data retrieval for infrequently used queries.

Automation Strategy

  • Unit Tests: Fully automated.
  • Integration Tests: Automated scripts to validate database integration.
  • Acceptance Tests: Automated to simulate user interaction scenarios.
  • Failures in any test prevent deployment to subsequent environments.

Conclusion

This strategy ensures that the service is robust, performs well under load, and meets the defined requirements. Continuous monitoring and iterative improvement of the test suite are recommended based on feedback and observed issues.