Random JSON Flattening Round-Trip Corpus Generator

Description

Reuse the random nested-document generator for its safe dot-path/contiguous-array subset, then actually flatten and rebuild every generated document with both existing cores; retain intermediate leaves and original/rebuilt forms, excluding sparse/mixed containers, reserved segments, literal-dot keys and empty-container loss cases rather than claiming arbitrary JSON round trips.

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.

When to use this tool

Use this generator to create reproducible json flattening round trip corpus 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 documentCount, fields, indent 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 documents. Use the conventions below and keep answer-bearing fields separate when presenting an exercise.

Generate the linked nested-document subset, flatten it with the existing tool, and compare the sorted leaf map with independently generated leaf truth. Unflatten and require exact serialization agreement with the original document.^[1]

Delegated operations used for this result: nested json document; flatten. Their calculation or parsing conventions apply to the corresponding result fields.^{[2, 3]}

Input field	Meaning and units	Accepted input
documentCount	Document Count	Required. Safe integer; minimum 1; maximum 64.
fields	Fields	Required. Array of Object; no unknown keys. or Object; no unknown keys. or Object; no unknown keys. or Object; no unknown keys.; minimum items 1; maximum items 64.
indent	Indent	Required. Safe integer; minimum 1; maximum 8.
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
documents	Documents	Required. Array of Object; no unknown keys.; minimum items 1; maximum items 64.
documents[].original	Original	Required. Object.
documents[].originalPretty	Original Pretty	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 1000000.
documents[].flattened	Flattened	Required. Object.
documents[].rebuilt	Rebuilt	Required. Object.
documents[].exactRoundTrip	Exact Round Trip	Required. Boolean.
randomness	Replay 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.seed	Optional numeric 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": {
    "documentCount": 2,
    "fields": [
      {
        "key": "profile.name",
        "kind": "text",
        "choices": [
          "Ada",
          "Grace"
        ]
      },
      {
        "key": "scores.0",
        "kind": "integer",
        "minimum": 1,
        "maximum": 5
      },
      {
        "key": "scores.1",
        "kind": "integer",
        "minimum": 1,
        "maximum": 5
      }
    ],
    "indent": 2,
    "seed": 42
  },
  "output": {
    "documents": [
      {
        "original": {
          "profile": {
            "name": "Grace"
          },
          "scores": [
            3,
            5
          ]
        },
        "originalPretty": "{\n  \"profile\": {\n    \"name\": \"Grace\"\n  },\n  \"scores\": [\n    3,\n    5\n  ]\n}\n",
        "flattened": {
          "profile.name": "Grace",
          "scores.0": 3,
          "scores.1": 5
        },
        "rebuilt": {
          "profile": {
            "name": "Grace"
          },
          "scores": [
            3,
            5
          ]
        },
        "exactRoundTrip": true
      },
      {
        "original": {
          "profile": {
            "name": "Grace"
          },
          "scores": [
            1,
            3
          ]
        },
        "originalPretty": "{\n  \"profile\": {\n    \"name\": \"Grace\"\n  },\n  \"scores\": [\n    1,\n    3\n  ]\n}\n",
        "flattened": {
          "profile.name": "Grace",
          "scores.0": 1,
          "scores.1": 3
        },
        "rebuilt": {
          "profile": {
            "name": "Grace"
          },
          "scores": [
            1,
            3
          ]
        },
        "exactRoundTrip": true
      }
    ],
    "randomness": {
      "seed": 42,
      "source": "seed"
    }
  }
}

Limitations and assumptions

The round trip is guaranteed only for the generator's restricted supported structure and key grammar. It does not establish reversible flattening for arbitrary arrays, empty containers, or colliding path spellings.
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

Tool behavior and example: Random JSON Flattening Round-Trip Corpus Generator — tool.io
Calculation or validation: random/nested-json-document — tool.io
Calculation or validation: json/flatten — tool.io

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