Random Multi-Select Option Fixture Generator

Description

Sample enabled option IDs without replacement under explicit minimum/maximum selection constraints, preserving caller groups, disabled flags and duplicate 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.

Sample enabled option IDs without replacement under explicit minimum/maximum selection constraints, preserving caller groups, disabled flags and duplicate labels.

When to use this tool

Use this generator to create reproducible multi select option 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

Supply options, minimumSelected, maximumSelected 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 options, selectedIds. Use the conventions below and keep answer-bearing fields separate when presenting an exercise.

Filter disabled options, draw a selection count in the supplied bounds, and sample that many enabled IDs without replacement. Return all options with code-point label previews and selected flags.^[1]

Input field	Meaning and units	Accepted input
options	Options	Required. Array of Object; no unknown keys.; minimum items 1; maximum items 32.
options[].id	Literal identifier used to match records, independently of their display labels.	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 32.
options[].label	Caller-facing text label; not a globally unique identifier.	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 128.
options[].group	Group	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 128.
options[].disabled	Disabled	Required. Boolean.
minimumSelected	Minimum Selected	Required. Safe integer; minimum 0; maximum 32.
maximumSelected	Maximum Selected	Required. Safe integer; minimum 0; maximum 32.
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
options	Options	Required. Array of Object; no unknown keys.; minimum items 1; maximum items 32.
options[].id	Literal identifier used to match records, independently of their display labels.	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 32.
options[].label	Caller-facing text label; not a globally unique identifier.	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 128.
options[].group	Group	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 128.
options[].disabled	Disabled	Required. Boolean.
options[].displayLabel	Display Label	Required. Text; maximum UTF-16 length 256.
options[].selected	Selected	Required. Boolean.
selectedIds	Selected Ids	Required. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 32.; minimum items 0; maximum items 32.
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": {
    "options": [
      {
        "id": "a",
        "label": "Same",
        "group": "A",
        "disabled": false
      },
      {
        "id": "b",
        "label": "Same",
        "group": "B",
        "disabled": false
      },
      {
        "id": "c",
        "label": "Locked",
        "group": "B",
        "disabled": true
      }
    ],
    "minimumSelected": 2,
    "maximumSelected": 2,
    "seed": 42
  },
  "output": {
    "options": [
      {
        "id": "a",
        "label": "Same",
        "group": "A",
        "disabled": false,
        "displayLabel": "Same",
        "selected": true
      },
      {
        "id": "b",
        "label": "Same",
        "group": "B",
        "disabled": false,
        "displayLabel": "Same",
        "selected": true
      },
      {
        "id": "c",
        "label": "Locked",
        "group": "B",
        "disabled": true,
        "displayLabel": "Locked",
        "selected": false
      }
    ],
    "selectedIds": [
      "a",
      "b"
    ],
    "randomness": {
      "seed": 42,
      "source": "seed"
    }
  }
}

Limitations and assumptions

maximumSelected must fit the enabled pool. IDs must be distinct even when labels match. Selection state does not implement keyboard navigation, validation feedback, or a rendered multi-select control.
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 Multi-Select Option Fixture Generator — tool.io

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