Add 14 generator types to meet the 60+ claim documented on the website

[Copilot]

Website and docs claim "60+ Generator Types" but only 47 exist. The other 6 advertised features (Auto PII Detection, Compliance Reports, Job Scheduling, Workspace Inheritance, Webhooks, REST API & CLI) are fully implemented with no gaps.

New generators (47 → 61)

• Personal: TITLE, JOB_TITLE, NATIONALITY
• Business: COMPANY_NAME, DEPARTMENT
• Financial: CURRENCY_CODE
• Network: DOMAIN_NAME, USER_AGENT
• Location: LATITUDE, LONGITUDE, TIME_ZONE
• Data Utilities: BOOLEAN, LOREM, TIMESTAMP

All backed by Datafaker, consistent with existing generator patterns:

GeneratorType.TITLE -> faker.name().prefix()
GeneratorType.JOB_TITLE -> faker.job().title()
GeneratorType.BOOLEAN -> faker.bool().bool()
GeneratorType.TIMESTAMP -> java.sql.Timestamp(faker.date().past(365 * 10, TimeUnit.DAYS).time)

Files touched

• Backend enum + service: ColumnGenerator.kt, GeneratorService.kt
• Frontend enum: types/index.ts
• Tests: EnumAlignmentTest.kt canonical set, GeneratorServiceTest.kt (14 new test cases), ConnectionsView.test.ts count assertion
• Docs: README.md, guide.html, user-guide.md

[Copilot]

Pull request overview

This PR expands OpenDataMask’s generator catalog so the codebase matches the “60+ generator types” claim by adding 14 new Datafaker-backed generator types across backend, frontend, tests, and docs.

Changes:

• Added 14 new GeneratorType values (47 → 61) to backend + frontend enums.
• Implemented generation logic for the new types in GeneratorService and added corresponding unit tests.
• Updated docs/website and enum-count assertions to reflect 61 generator types.

Reviewed changes

Copilot reviewed 9 out of 9 changed files in this pull request and generated 4 comments.

Show a summary per file

File	Description
README.md	Updates the documented generator count and examples.
frontend/src/views/tests/ConnectionsView.test.ts	Updates enum-count assertion from 47 to 61.
frontend/src/types/index.ts	Adds the 14 new GeneratorType enum members.
docs/website/guide.html	Updates generator table to include new generator types/categories.
docs/user-guide.md	Adds example rows demonstrating new generator outputs.
backend/src/test/kotlin/com/opendatamask/domain/model/EnumAlignmentTest.kt	Updates canonical generator set to include the new types.
backend/src/test/kotlin/com/opendatamask/application/service/GeneratorServiceTest.kt	Adds tests covering the 14 new generators’ outputs/types.
backend/src/main/kotlin/com/opendatamask/domain/model/ColumnGenerator.kt	Adds the 14 new backend enum values.
backend/src/main/kotlin/com/opendatamask/application/service/GeneratorService.kt	Implements generation logic for the new enum values.

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[Copilot]

USER_AGENT generation compiles a new Regex("\\s+") on every call via replace(Regex(...)), which can be a hot path when generating large datasets. Consider using a precompiled regex constant (e.g., in a companion object) or an alternative that avoids per-call regex construction.

[Copilot]

TIMESTAMP uses a fully-qualified java.util.concurrent.TimeUnit.DAYS while earlier generators in the same method use the imported TimeUnit.DAYS. For consistency/readability, use the same TimeUnit reference throughout this when block.

Suggested change

	GeneratorType.TIMESTAMP -> java.sql.Timestamp(faker.date().past(365 * 10, java.util.concurrent.TimeUnit.DAYS).time)
	GeneratorType.TIMESTAMP -> java.sql.Timestamp(faker.date().past(365 * 10, TimeUnit.DAYS).time)

[Copilot]

The TIMESTAMP example (2024-06-15 14:30:00) likely won’t match actual output: java.sql.Timestamp.toString() typically includes fractional seconds (e.g., .0 or milliseconds). Consider updating the example to include fractional seconds or clarifying the displayed format.

Suggested change

	| `TIMESTAMP` | `2024-06-15 14:30:00` |
	| `TIMESTAMP` | `2024-06-15 14:30:00.0` |

[Copilot]

This row is labeled Address but now includes LATITUDE, LONGITUDE, and TIME_ZONE, which are described as "Location" generators in the PR description. Consider renaming the category (e.g., Location) or splitting into a separate row to keep the table taxonomy consistent.