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Random JSON Schema Union Branch Fixture Generator

Construct caller-labeled tagged-union documents with missing, unknown or conflicting payload controls and explicit branch-selection keys.

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Description

Construct caller-labeled tagged-union documents with missing, unknown or conflicting payload controls and explicit branch-selection keys.

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 caller-labeled tagged-union documents with missing, unknown or conflicting payload controls and explicit branch-selection keys.

When to use this tool

Use this generator to create reproducible json schema union branch 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

  1. Supply discriminator, branches, modes, count in the field shapes below. Set seed when you need an explicit replay.
  2. 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.
  3. Read documents. Use the conventions below and keep answer-bearing fields separate when presenting an exercise.

Choose a tagged branch and construct its discriminator and payload fields. Apply missing, unknown, conflicting, or valid mode, then report branch selection and validity under this explicit discriminator model.1

Input fieldMeaning and unitsAccepted input
discriminatorDiscriminatorRequired. Text; minimum UTF-16 length 1; maximum UTF-16 length 128.
branchesBranchesRequired. Array of Object; no unknown keys.; minimum items 1; maximum items 16.
branches[].tagTagRequired. Text; minimum UTF-16 length 1; maximum UTF-16 length 128.
branches[].payloadKeyPayload KeyRequired. Text; minimum UTF-16 length 1; maximum UTF-16 length 128.
branches[].payloadPayloadRequired. Text; maximum UTF-16 length 65536. or Finite number. or Boolean. or Null.
branches[].labelCaller-facing text label; not a globally unique identifier.Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 128.
modesModesRequired. Array of Text; one of "valid", "missing", "unknown", "conflicting".; minimum items 1; maximum items 4.
countRequested count; the mechanics explain whether one draw expands into several returned records.Required. Safe integer; minimum 1; maximum 32.
seedOptional numeric seed; takes precedence over context randomness. Without either, use the fixed tool.io default seed.Optional. Safe integer.
Output fieldInterpretationReturned shape
documentsDocumentsRequired. Array of Object; no unknown keys.; minimum items 1; maximum items 32.
documents[].modeModeRequired. Text; maximum UTF-16 length 65536.
documents[].documentDocumentRequired. Object.
documents[].prettyPrettyRequired. Text; maximum UTF-16 length 65536.
documents[].selectedTagSelected TagRequired. Text; maximum UTF-16 length 65536. or Null.
documents[].branchLabelBranch LabelRequired. Text; maximum UTF-16 length 65536. or Null.
documents[].validValidity under the specific model or delegated checker described above.Required. Boolean.
randomnessReplay metadata: source is seed or context; seed is the normalized 32-bit seed or null for a context source.Required. Object; no unknown keys.
randomness.seedOptional numeric replay seed; normalization and precedence are explained below.Required. Safe integer. or Null.
randomness.sourceSourceRequired. 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": {
    "discriminator": "kind",
    "branches": [
      {
        "tag": "red",
        "payloadKey": "redValue",
        "payload": 2,
        "label": "Red branch"
      },
      {
        "tag": "blue",
        "payloadKey": "blueValue",
        "payload": "b",
        "label": "Blue branch"
      }
    ],
    "modes": [
      "valid"
    ],
    "count": 1,
    "seed": 42
  },
  "output": {
    "documents": [
      {
        "mode": "valid",
        "document": {
          "kind": "blue",
          "blueValue": "b"
        },
        "pretty": "{\n  \"kind\": \"blue\",\n  \"blueValue\": \"b\"\n}\n",
        "selectedTag": "blue",
        "branchLabel": "Blue branch",
        "valid": true
      }
    ],
    "randomness": {
      "seed": 42,
      "source": "seed"
    }
  }
}

Limitations and assumptions

  • This does not run a general JSON Schema validator. Conflicting mode adds another branch's payload and requires distinct payload keys; a recognized tag alone does not make that control valid.
  • A replay requires the same complete input and implementation. Randomized construction does not guarantee uniform coverage of every feasible output; finite samples can repeat unless a distinct-selection rule is explicitly stated.
  • 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

  1. Tool behavior and example: Random JSON Schema Union Branch Fixture Generator — tool.io

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