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Random JSON Merge Conflict Scenario Generator

Construct flat base/left/right edits and report true three-way conflicts with explicit left, right or base resolution policy.

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Description

Construct flat base/left/right edits and report true three-way conflicts with explicit left, right or base resolution policy.

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 flat base/left/right edits and report true three-way conflicts with explicit left, right or base resolution policy.

When to use this tool

Use this generator to create reproducible json merge conflict scenario 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 base, changes, forceOverlap, operations, resolution 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 base, left, right, edits, overlappingPaths, conflicts, merged, pretty. Use the conventions below and keep answer-bearing fields separate when presenting an exercise.

Copy a flat scalar base object into left and right edits, selecting set or delete on sampled keys. Compare own-key presence and values to detect actual overlapping changes and conflicts, then merge using the selected left, right, or base conflict rule.1

Input fieldMeaning and unitsAccepted input
baseBaseRequired. Array of Object; no unknown keys.; minimum items 1; maximum items 16.
base[].keyKeyRequired. Text; minimum UTF-16 length 1; maximum UTF-16 length 128.
base[].valueValueRequired. Text; maximum UTF-16 length 65536. or Finite number. or Boolean. or Null.
changesChangesRequired. Object; no unknown keys.
changes.leftLeftRequired. Text; maximum UTF-16 length 65536. or Finite number. or Boolean. or Null.
changes.rightRightRequired. Text; maximum UTF-16 length 65536. or Finite number. or Boolean. or Null.
forceOverlapForce OverlapRequired. Boolean.
operationsOperationsRequired. Array of Text; one of "set", "delete".; minimum items 1; maximum items 2.
resolutionResolutionRequired. Text; one of "left", "right", "base".
seedOptional numeric seed; takes precedence over context randomness. Without either, use the fixed tool.io default seed.Optional. Safe integer.
Output fieldInterpretationReturned shape
baseBaseRequired. Object.
leftLeftRequired. Object.
rightRightRequired. Object.
editsEditsRequired. Array of Object; no unknown keys.; minimum items 2; maximum items 2.
edits[].sideSideRequired. Text; maximum UTF-16 length 65536.
edits[].keyKeyRequired. Text; maximum UTF-16 length 65536.
edits[].operationOperationRequired. Text; maximum UTF-16 length 65536.
overlappingPathsOverlapping PathsRequired. Array of Text; maximum UTF-16 length 65536.; minimum items 0; maximum items 16.
conflictsConflictsRequired. Array of Text; maximum UTF-16 length 65536.; minimum items 0; maximum items 16.
mergedMergedRequired. Object.
prettyPrettyRequired. Text; maximum UTF-16 length 65536.
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": {
    "base": [
      {
        "key": "theme",
        "value": "light"
      },
      {
        "key": "size",
        "value": 2
      }
    ],
    "changes": {
      "left": "blue",
      "right": "dark"
    },
    "forceOverlap": true,
    "operations": [
      "set"
    ],
    "resolution": "right",
    "seed": 42
  },
  "output": {
    "base": {
      "theme": "light",
      "size": 2
    },
    "left": {
      "theme": "light",
      "size": "blue"
    },
    "right": {
      "theme": "light",
      "size": "dark"
    },
    "edits": [
      {
        "side": "left",
        "key": "size",
        "operation": "set"
      },
      {
        "side": "right",
        "key": "size",
        "operation": "set"
      }
    ],
    "overlappingPaths": [
      "size"
    ],
    "conflicts": [
      "size"
    ],
    "merged": {
      "theme": "light",
      "size": "dark"
    },
    "pretty": "{\n  \"theme\": \"light\",\n  \"size\": \"dark\"\n}\n",
    "randomness": {
      "seed": 42,
      "source": "seed"
    }
  }
}

Limitations and assumptions

  • forceOverlap selects the same key but does not guarantee a conflict: a no-op or identical edits can avoid one. This is a flat three-way model, not a recursive merge algorithm or filesystem merge.
  • 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 Merge Conflict Scenario Generator — tool.io

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