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Random Semantic Edit Markup Fixture Generator

Construct escaped caller edit fragments using ins/del/s annotations with an explicit before/after ledger and lexical tag keys, without assigning legal meaning.

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Description

Construct escaped caller edit fragments using ins/del/s annotations with an explicit before/after ledger and lexical tag keys, without assigning legal meaning.

A protocol fixture is local test data representing headers, messages, identifiers, or request decisions. Serialization and parsing can be checked without contacting a server, while authentication, delivery, and actual client behavior require separate tests.

Construct escaped caller edit fragments using ins/del/s annotations with an explicit before/after ledger and lexical tag keys, without assigning legal meaning.

When to use this tool

Use this generator to create reproducible semantic edit markup 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 fragments, kinds, 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 ledger, beforeText, afterText, html. Use the conventions below and keep answer-bearing fields separate when presenting an exercise.

Sample edit fragments and insertion, deletion, replacement, or obsolete modes. Serialize escaped text inside ins, del, or s tags with data-edit indexes, parse the opening tags, and concatenate beforeText and afterText from the ledger.1

Input fieldMeaning and unitsAccepted input
fragmentsFragmentsRequired. Array of Object; no unknown keys.; minimum items 1; maximum items 32.
fragments[].beforeBeforeRequired. Text; maximum UTF-16 length 256.
fragments[].afterAfterRequired. Text; maximum UTF-16 length 256.
kindsKindsRequired. Array of Text; one of "replacement", "insertion", "deletion", "obsolete".; 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
ledgerLedgerRequired. Array of Object; no unknown keys.; minimum items 1; maximum items 32.
ledger[].indexIndexRequired. Safe integer; minimum 0; maximum 31.
ledger[].kindKindRequired. Text; one of "replacement", "insertion", "deletion", "obsolete".
ledger[].suppliedBeforeSupplied BeforeRequired. Text; maximum UTF-16 length 256.
ledger[].suppliedAfterSupplied AfterRequired. Text; maximum UTF-16 length 256.
ledger[].beforeBeforeRequired. Text; maximum UTF-16 length 256.
ledger[].afterAfterRequired. Text; maximum UTF-16 length 256.
ledger[].markupMarkupRequired. Text; maximum UTF-16 length 131072.
ledger[].tagsTagsRequired. Array of Object; no unknown keys.; minimum items 1; maximum items 2.
ledger[].tags[].nameNameRequired. Text; maximum UTF-16 length 256.
ledger[].tags[].attributesAttributesRequired. Array of Object; no unknown keys.; minimum items 0; maximum items 16.
ledger[].tags[].attributes[].nameNameRequired. Text; maximum UTF-16 length 256.
ledger[].tags[].attributes[].valueValueRequired. Text; maximum UTF-16 length 2048.
beforeTextBefore TextRequired. Text; maximum UTF-16 length 8192.
afterTextAfter TextRequired. Text; maximum UTF-16 length 8192.
htmlHtmlRequired. Text; maximum UTF-16 length 131072.
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": {
    "fragments": [
      {
        "before": "Old",
        "after": "New"
      },
      {
        "before": "Draft",
        "after": "Final"
      }
    ],
    "kinds": [
      "replacement",
      "insertion",
      "deletion",
      "obsolete"
    ],
    "count": 1,
    "seed": 42
  },
  "output": {
    "ledger": [
      {
        "index": 0,
        "kind": "insertion",
        "suppliedBefore": "Draft",
        "suppliedAfter": "Final",
        "before": "",
        "after": "Final",
        "markup": "<ins data-edit=\"0\">Final</ins>",
        "tags": [
          {
            "name": "ins",
            "attributes": [
              {
                "name": "data-edit",
                "value": "0"
              }
            ]
          }
        ]
      }
    ],
    "beforeText": "",
    "afterText": "Final",
    "html": "<ins data-edit=\"0\">Final</ins>",
    "randomness": {
      "seed": 42,
      "source": "seed"
    }
  }
}

Limitations and assumptions

  • Obsolete text remains in both text views, unlike deletion. Markup is synthetic semantic-edit evidence, not a browser diff or a general HTML sanitizer; supplied originals remain available separately.
  • 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 Semantic Edit Markup Fixture Generator — tool.io

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