Verify Schema Validation Tooling

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Introduction

Schema validation is a crucial process in ensuring data integrity within a project. As the project evolves, it's essential to confirm that the existing schema validation tooling correctly processes the updated action-definition.schema.json and validates action definition files using JSON Logic prerequisites. This article will guide you through the process of verifying schema validation tooling, ensuring that the project's existing tooling works correctly with the updated schema.

Goal and Description

The primary goal of this task is to ensure that the project's existing schema validation tooling correctly processes the updated action-definition.schema.json and validates action definition files using JSON Logic prerequisites. The project relies on schema validation to ensure data integrity, and after modifying action-definition.schema.json (Ticket 3.1) and updating example files (Ticket 3.4), it's essential to confirm that the validation process itself still works correctly and successfully validates files conforming to the new structure, while correctly rejecting invalid ones.

Tasks

Identify Validation Process

To begin, we need to determine how schema validation is currently performed in the project. This may involve identifying a script run during build, a test suite task, integration with the SystemLogicInterpreter or data loader. Understanding the current validation process will help us to execute the schema validation process after the changes from Ticket 3.1 and Ticket 3.4 are completed.

Run Validation

Once we have identified the validation process, we need to execute the schema validation process after the changes from Ticket 3.1 and Ticket 3.4 are completed. This will help us to confirm that the validation process itself still works correctly and successfully validates files conforming to the new structure.

Verify Success Cases

After running the validation process, we need to confirm that all valid action definition files (including those refactored and newly created with JSON Logic prerequisites in Ticket 3.4) pass validation without errors. This will help us to ensure that the validation process is working correctly and that all valid files are being successfully validated.

Verify Failure Cases

To further test the validation process, we need to create or modify a temporary action definition file to intentionally violate the schema in the prerequisites section using the new structure. Examples of violations may include:

  • An item in prerequisites is not a valid JSON Logic object (e.g., a string, a number, an object with multiple keys).
  • A JSON Logic object within prerequisites violates the json-logic.schema.json rules (e.g., incorrect arguments for an operator).

Run Validation on Failure Cases

Once we have created or modified the temporary action definition file, we need to execute the schema validation process against the intentionally invalid file(s). This will help us to confirm that the validation tooling correctly identifies the schema violations in the invalid file(s) and reports appropriate errors referencing the prerequisites field and the underlying JSON Logic schema violation.

Confirm Rejection

After running the validation process against the intentionally invalid file(s), we need to verify that the validation tooling correctly identifies the schema violations in the invalid file(s) and reports appropriate errors referencing the prerequisites field and the underlying JSON Logic schema violation. This will help us to ensure that the validation process is working correctly and that all invalid files are being correctly rejected.

Document Findings

Finally, we need to briefly document that the validation tooling was tested and confirmed to work correctly with the updated schema referencing json-logic.schema.json. This will help us to keep a record of the testing process and ensure that the validation tooling is working correctly.

Acceptance Criteria

The existing schema validation tooling executes successfully after schema updates.

  • Valid action definition files using JSON Logic prerequisites pass schema validation.
  • Action definition files with invalid structures within the prerequisites array (violating either the array item type or the referenced JSON Logic schema) are correctly rejected by the validation tooling.
  • Error messages generated for invalid prerequisites accurately point to the location and nature of the schema violation.

Dependencies

  • Ticket 3.1: action-definition.schema.json must be updated.
  • Ticket 3.4: Valid examples using the new format must be available.

Estimate

The estimate for this task is small, primarily involving running existing tools and verifying output.

Conclusion

Introduction

In our previous article, we discussed the importance of verifying schema validation tooling in ensuring data integrity within a project. In this article, we will provide a Q&A section to address common questions and concerns related to schema validation tooling.

Q: What is schema validation tooling?

A: Schema validation tooling is a process used to ensure that data conforms to a specific schema or structure. It helps to prevent data inconsistencies and errors by validating the data against a predefined schema.

Q: Why is schema validation tooling important?

A: Schema validation tooling is important because it helps to ensure data integrity and accuracy. It prevents data inconsistencies and errors by validating the data against a predefined schema. This is particularly important in projects that involve large amounts of data or complex data structures.

Q: How does schema validation tooling work?

A: Schema validation tooling works by comparing the data against a predefined schema. The schema defines the structure and format of the data, and the validation tool checks the data against this schema to ensure that it conforms to the expected structure and format.

Q: What are the benefits of schema validation tooling?

A: The benefits of schema validation tooling include:

  • Ensuring data integrity and accuracy
  • Preventing data inconsistencies and errors
  • Improving data quality and reliability
  • Reducing the risk of data-related errors and issues

Q: How do I implement schema validation tooling in my project?

A: To implement schema validation tooling in your project, you will need to:

  • Define a schema for your data
  • Choose a schema validation tool or library
  • Integrate the schema validation tool into your project
  • Test the schema validation tool to ensure that it is working correctly

Q: What are some common challenges associated with schema validation tooling?

A: Some common challenges associated with schema validation tooling include:

  • Defining a schema that accurately reflects the structure and format of the data
  • Choosing a schema validation tool or library that meets the needs of the project
  • Integrating the schema validation tool into the project
  • Testing the schema validation tool to ensure that it is working correctly

Q: How do I troubleshoot issues with schema validation tooling?

A: To troubleshoot issues with schema validation tooling, you can:

  • Review the schema definition to ensure that it accurately reflects the structure and format of the data
  • Check the schema validation tool or library to ensure that it is configured correctly
  • Test the schema validation tool to ensure that it is working correctly
  • Consult the documentation or seek support from the schema validation tool or library vendor

Conclusion

In conclusion, schema validation tooling is an important process for ensuring data integrity and accuracy within a project. By understanding the benefits and challenges associated with schema validation tooling, and by following the steps outlined in this article, you can implement schema validation tooling in your project and ensure that your data is accurate and reliable.