Mock Data Generator

// HOW TO USE

1. 01Pick a preset or build your schema field-by-field. Each field gets a name and a type.
2. 02Choose how many rows (1–1000) and click Generate.
3. 03Switch the output between JSON, CSV, and SQL INSERT — same rows, different shape.

// WHEN TO USE

Use this when you need realistic-looking but entirely fake structured data for API mocks, UI prototypes, database seeding, or demo environments. The generator produces consistent schema-based records rather than hardcoded values, which avoids the bias that comes from typing test data by hand. Choose JSON for API mocks, CSV for data-driven tests, or SQL INSERT for database fixture scripts — all from the same schema definition.

// WHAT BUGS THIS FINDS

• Missing null/empty field handling

  Hardcoded test data never exercises null or empty values for optional fields — generate records with optional fields included and excluded to confirm the application handles both states.

• Schema field ordering assumptions

  A parser that reads fields by position rather than name breaks when JSON object key order varies — generate multiple records and compare key order to detect position-dependent parsing code.

• Insufficient data volume for pagination

  Pagination logic is untested if seed data has fewer rows than one page — generate 100+ records to fill multiple pages and exercise next/previous navigation and total count display.

• Type coercion in SQL INSERT output

  A numeric field generated without quotes causes a type error in strict SQL mode — switch to SQL output and review the INSERT statements to confirm value quoting matches the column type.

// QA USE CASES