Description
Sample caller-owned fictional avatar records, derive word initials and missing-image flags, and produce visible/overflow counts without creating image assets.
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 caller-owned fictional avatar records, derive word initials and missing-image flags, and produce visible/overflow counts without creating image assets.
When to use this tool
Use this generator to create reproducible avatar group overflow 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 records, count, visibleLimit 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 avatars, visibleCount, overflowCount, overflowLabel. Use the conventions below. Keep answer-bearing fields separate when presenting an exercise.
Sample avatar records, form uppercase initials from the first code point of up to two name tokens, and independently model a missing image label. Mark the first visibleLimit positions visible and return overflow count and a plus-count label.1
| Input field | Meaning and units | Accepted input |
|---|---|---|
| records | Records | Required. Array of Object; no unknown keys.; minimum items 1; maximum items 32. |
| records[].name | Name | Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 128. |
| records[].imageLabel | Image Label | Required. Text; maximum UTF-16 length 256. |
| count | Count | Required. Safe integer; minimum 1; maximum 32. |
| visibleLimit | Visible Limit | 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 |
|---|---|---|
| avatars | Avatars | Required. Array of Object; no unknown keys.; minimum items 1; maximum items 32. |
| avatars[].id | Literal identifier used independently of display labels. | Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 32. |
| avatars[].name | Name | Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 128. |
| avatars[].initials | Initials | Required. Text; maximum UTF-16 length 256. |
| avatars[].imageLabel | Image Label | Required. Text; maximum UTF-16 length 256. or Null. |
| avatars[].visible | Visible | Required. Boolean. |
| visibleCount | Visible Count | Required. Safe integer; minimum 0; maximum 32. |
| overflowCount | Overflow Count | Required. Safe integer; minimum 0; maximum 32. |
| overflowLabel | Overflow Label | Required. Text; maximum UTF-16 length 256. |
| randomness | Replay source and normalized 32-bit seed, or null seed for an advancing context source. | Required. Object; no unknown keys. |
| randomness.seed | Optional safe-integer 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.
{
"input": {
"records": [
{
"name": "Ana Reed",
"imageLabel": "portrait-a"
},
{
"name": "Bo Li",
"imageLabel": "portrait-b"
}
],
"count": 3,
"visibleLimit": 2,
"seed": 42
},
"output": {
"avatars": [
{
"id": "avatar-0",
"name": "Bo Li",
"initials": "BL",
"imageLabel": null,
"visible": true
},
{
"id": "avatar-1",
"name": "Bo Li",
"initials": "BL",
"imageLabel": "portrait-b",
"visible": true
},
{
"id": "avatar-2",
"name": "Ana Reed",
"initials": "AR",
"imageLabel": "portrait-a",
"visible": false
}
],
"visibleCount": 2,
"overflowCount": 1,
"overflowLabel": "+1",
"randomness": {
"seed": 42,
"source": "seed"
}
}
}Limitations and assumptions
- Repeated people and initials are allowed. Names must contain nonwhitespace text. No images are fetched and this does not measure visual fit, verify identities, or implement accessible group interactions.
- A replay requires the same complete input and implementation. The stated sampling convention applies within its eligible space. A finite draw does not exhaust all possible outputs; repeats remain possible unless a distinct-selection rule is explicit.
- 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
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