Random Document Localization Key Fixture Generator

Description

Construct supplied message-key usages with explicit removed-catalog and orphan controls, retaining repeated, missing and unused-key answers.

A parser corpus pairs literal input spellings or structured documents with observable parser results or explicitly constructed expectations. Successful parsing, semantic validity, and exact round-trip preservation are separate properties, so test records retain the relevant evidence.

Construct supplied message-key usages with explicit removed-catalog and orphan controls, retaining repeated, missing and unused-key answers.

When to use this tool

Use this generator to create reproducible document localization key fixture cases from the supplied model or bank. Inspect the returned evidence before using cases in a test or exercise.

How to use the tool and how it works

Supply catalog, usageCount, removeUsedKey, orphanControl in the field shapes below. Set seed when you need an explicit replay.
Run the tool and correct any input error. For generated controls, distinguish a successful fixture containing an invalid case from failure to generate the fixture.
Read catalog, usages, missingKeys, repeatedKeys, unusedKeys, pretty. Use the conventions below. Keep answer-bearing fields separate when presenting an exercise.

Draw localization-key usages from the supplied catalog, optionally remove a used catalog key or append a guaranteed unknown key, then return missing, repeated, and unused keys with the retained catalog's serialized mapping.^[1]

Input field	Meaning and units	Accepted input
catalog	Catalog	Required. Array of Object; no unknown keys.; minimum items 1; maximum items 16.
catalog[].key	Key	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 128.
catalog[].message	Message	Required. Text; maximum UTF-16 length 65536.
usageCount	Usage Count	Required. Safe integer; minimum 1; maximum 31.
removeUsedKey	Remove Used Key	Required. Boolean.
orphanControl	Orphan Control	Required. Boolean.
seed	Optional numeric seed; takes precedence over context randomness. Without either, use the fixed tool.io default seed.	Optional. Safe integer.

Output field	Interpretation	Returned shape
catalog	Catalog	Required. Array of Object; no unknown keys.; minimum items 0; maximum items 16.
catalog[].key	Key	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 128.
catalog[].message	Message	Required. Text; maximum UTF-16 length 65536.
usages	Usages	Required. Array of Text; maximum UTF-16 length 65536.; minimum items 1; maximum items 32.
missingKeys	Missing Keys	Required. Array of Text; maximum UTF-16 length 65536.; minimum items 0; maximum items 32.
repeatedKeys	Repeated Keys	Required. Array of Text; maximum UTF-16 length 65536.; minimum items 0; maximum items 16.
unusedKeys	Unused Keys	Required. Array of Text; maximum UTF-16 length 65536.; minimum items 0; maximum items 16.
pretty	Pretty	Required. Text; maximum UTF-16 length 65536.
randomness	Replay source and normalized 32-bit seed, or null seed for an advancing context source.	Required. Object; no unknown keys.
randomness.seed	Optional safe-integer replay seed; normalization and precedence are explained below.	Required. Safe integer. or Null.
randomness.source	Source	Required. Text; one of "context", "seed".

An explicit safe-integer seed takes precedence over injected context randomness and is normalized to an unsigned 32-bit integer. With no seed and no context source, replay uses the fixed tool.io default seed. A context source must return finite values from zero inclusive to one exclusive; its advancing state must be retained separately. randomness records the source and normalized seed, or null for context. These generators are not cryptographic random sources.

json

{
  "input": {
    "catalog": [
      {
        "key": "title",
        "message": "Hello"
      },
      {
        "key": "body",
        "message": "Text"
      }
    ],
    "usageCount": 3,
    "removeUsedKey": false,
    "orphanControl": true,
    "seed": 42
  },
  "output": {
    "catalog": [
      {
        "key": "title",
        "message": "Hello"
      },
      {
        "key": "body",
        "message": "Text"
      }
    ],
    "usages": [
      "body",
      "title",
      "body",
      "__orphan__"
    ],
    "missingKeys": [
      "__orphan__"
    ],
    "repeatedKeys": [
      "body"
    ],
    "unusedKeys": [],
    "pretty": "{\n  \"title\": \"Hello\",\n  \"body\": \"Text\"\n}\n",
    "randomness": {
      "seed": 42,
      "source": "seed"
    }
  }
}

Limitations and assumptions

Repeated usage is not automatically an error. These checks concern exact keys, not translation quality, locale fallback, interpolation variables, or pluralization; no locale data is downloaded.
A replay requires the same complete input and implementation. The stated sampling convention applies within its eligible space. A finite draw does not exhaust all possible outputs; repeats remain possible unless a distinct-selection rule is explicit.
The field tables state structural bounds; cross-field constraints and bounded search or output budgets also apply. Unknown keys are rejected where the object contract disallows them. Input errors are distinct from null fields and deliberate invalid controls in a successful output.

Alternative or Complementary methods

For a supplied example, inspect the returned construction or delegated check directly. To evaluate a consumer, also test cases chosen for its own boundaries; a generated finite corpus does not establish exhaustive coverage.

References

Tool behavior and example: Random Document Localization Key Fixture Generator — tool.io

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