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Random Rating Widget State Fixture Generator

Draw bounded integer rating ticks under a supplied maximum and subdivision contract, retaining fractional fills and disabled states with caller labels.

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Description

Draw bounded integer rating ticks under a supplied maximum and subdivision contract, retaining fractional fills and disabled states with caller labels.

An interface fixture makes content and state explicit so a consumer can test a rendering or interaction. Literal labels, modeled states, and calculated geometry remain separate from what a browser or assistive technology actually displays or announces.

Draw bounded integer rating ticks under a supplied maximum and subdivision contract, retaining fractional fills and disabled states with caller labels.

When to use this tool

Use this generator to create reproducible rating widget state 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 labels, maximum, subdivisions, 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 states. Use the conventions below and keep answer-bearing fields separate when presenting an exercise.

Draw an integer rating tick from zero through maximum times subdivisions and divide by subdivisions. Return whole and fractional portions, independently drawn disabled state, a label preview, and each item's clamped fill fraction.1

Input fieldMeaning and unitsAccepted input
labelsLabelsRequired. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 128.; minimum items 1; maximum items 32.
maximumMaximumRequired. Safe integer; minimum 1; maximum 32.
subdivisionsSubdivisionsRequired. Safe integer; minimum 1; maximum 32.
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
statesStatesRequired. Array of Object; no unknown keys.; minimum items 1; maximum items 32.
states[].labelCaller-facing text label; not a globally unique identifier.Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 128.
states[].valueValueRequired. Finite number; minimum 0; maximum 32.
states[].wholeWholeRequired. Safe integer; minimum 0; maximum 32.
states[].fractionFractionRequired. Finite number; minimum 0; strictly below 1.
states[].disabledDisabledRequired. Boolean.
states[].fillsFillsRequired. Array of Finite number; minimum 0; maximum 1.; minimum items 1; maximum items 32.
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": {
    "labels": [
      "Quality",
      "Comfort"
    ],
    "maximum": 3,
    "subdivisions": 2,
    "count": 1,
    "seed": 42
  },
  "output": {
    "states": [
      {
        "label": "Comfort",
        "value": 2,
        "whole": 2,
        "fraction": 0,
        "disabled": true,
        "fills": [
          1,
          1,
          0
        ]
      }
    ],
    "randomness": {
      "seed": 42,
      "source": "seed"
    }
  }
}

Limitations and assumptions

  • The grid includes both zero and the maximum. This is state data, not rendered stars, pointer behavior, keyboard semantics, or an accessibility audit; labels are previewed by code point.
  • 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 Rating Widget State Fixture Generator — tool.io

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