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Random Sqids Reversible ID Fixture Generator

Draw fixed-length tuples of nonnegative safe integers from an inclusive range, delegate standard-alphabet/blocklist Sqids encoding and decoding, and report round trips plus repeated tuples; this is reversible obfuscation, not encryption, uniqueness allocation or a custom-alphabet generator.

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Description

Draw fixed-length tuples of nonnegative safe integers from an inclusive range, delegate standard-alphabet/blocklist Sqids encoding and decoding, and report round trips plus repeated tuples; this is reversible obfuscation, not encryption, uniqueness allocation or a custom-alphabet generator.

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.

Draw fixed-length tuples of nonnegative safe integers from an inclusive range, delegate standard-alphabet/blocklist Sqids encoding and decoding, and report round trips plus repeated tuples; this is reversible obfuscation, not encryption, uniqueness allocation or a custom-alphabet generator.

When to use this tool

Use this generator to create reproducible sqids reversible id 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 minimum, maximum, tupleLength, 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 fixtures, duplicatePairs. Use the conventions below and keep answer-bearing fields separate when presenting an exercise.

Draw fixed-length tuples of nonnegative safe integers from the inclusive range. Encode and decode each using the standard-alphabet Sqids tools, compare decoded tuples, and report index pairs whose encoded IDs repeat.1

Delegated operations used for this result: sqids; sqids. Their calculation or parsing conventions apply to the corresponding result fields.2, 3

Input fieldMeaning and unitsAccepted input
minimumMinimumRequired. Safe integer; minimum 0; maximum 9007199254740991.
maximumMaximumRequired. Safe integer; minimum 0; maximum 9007199254740991.
tupleLengthTuple LengthRequired. Safe integer; minimum 1; maximum 16.
countRequested count; the mechanics explain whether one draw expands into several returned records.Required. Safe integer; minimum 1; maximum 64.
seedOptional numeric seed; takes precedence over context randomness. Without either, use the fixed tool.io default seed.Optional. Safe integer.
Output fieldInterpretationReturned shape
fixturesFixturesRequired. Array of Object; no unknown keys.; minimum items 1; maximum items 64.
fixtures[].numbersNumbersRequired. Array of Safe integer; minimum 0; maximum 9007199254740991.; minimum items 1; maximum items 16.
fixtures[].idLiteral identifier used to match records, independently of their display labels.Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 1000.
fixtures[].decodedDecodedRequired. Array of Safe integer; minimum 0; maximum 9007199254740991.; minimum items 1; maximum items 16.
fixtures[].roundTripVerifiedRound Trip VerifiedRequired. Boolean.
duplicatePairsDuplicate PairsRequired. Array of Array of Safe integer; minimum 0; maximum 63.; minimum items 2; maximum items 2.; maximum items 2016.
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": {
    "minimum": 0,
    "maximum": 9,
    "tupleLength": 3,
    "count": 3,
    "seed": 42
  },
  "output": {
    "fixtures": [
      {
        "numbers": [
          6,
          4,
          8
        ],
        "id": "YFEbTW",
        "decoded": [
          6,
          4,
          8
        ],
        "roundTripVerified": true
      },
      {
        "numbers": [
          6,
          1,
          5
        ],
        "id": "WJ0jrU",
        "decoded": [
          6,
          1,
          5
        ],
        "roundTripVerified": true
      },
      {
        "numbers": [
          2,
          6,
          8
        ],
        "id": "uh2MYQ",
        "decoded": [
          2,
          6,
          8
        ],
        "roundTripVerified": true
      }
    ],
    "duplicatePairs": [],
    "randomness": {
      "seed": 42,
      "source": "seed"
    }
  }
}

Limitations and assumptions

  • Sqids is reversible obfuscation, not encryption or unique ID allocation. Repeated tuples can recur, the default blocklist remains in effect, and custom alphabets are not configured here.
  • 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 Sqids Reversible ID Fixture Generator — tool.io

  2. Calculation or validation: encode/sqids — tool.io

  3. Calculation or validation: decode/sqids — tool.io

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