Random Notification Inbox Dataset Generator

Description

Compose supplied notification templates into a synthetic inbox with feasible read timestamps, chronological order, and unread and category counts.

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.

Compose supplied notification templates into a synthetic inbox with feasible read timestamps, chronological order, and unread and category counts.

When to use this tool

Use this generator to create reproducible notification inbox dataset 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 templates, count, startMilliseconds, endMilliseconds, readProbability 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 notifications, unreadCount, categoryCounts. Use the conventions below and keep answer-bearing fields separate when presenting an exercise.

Sample notification templates and timestamps, independently choose read status, and place read timestamps between creation and the supplied end. Sort newest first and return unread and category counts.^[1]

Input field	Meaning and units	Accepted input
templates	Templates	Required. Array of Object; no unknown keys.; minimum items 1; maximum items 128.
templates[].category	Category	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 128.
templates[].text	Text	Required. Text; maximum UTF-16 length 4096.
count	Requested count; the mechanics explain whether one draw expands into several returned records.	Required. Safe integer; minimum 1; maximum 128.
startMilliseconds	Start Milliseconds	Required. Safe integer.
endMilliseconds	End Milliseconds	Required. Safe integer.
readProbability	Read Probability	Required. Finite number; minimum 0; maximum 1.
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
notifications	Notifications	Required. Array of Object; no unknown keys.; minimum items 1; maximum items 128.
notifications[].id	Literal identifier used to match records, independently of their display labels.	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 128.
notifications[].category	Category	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 128.
notifications[].text	Text	Required. Text; maximum UTF-16 length 4096.
notifications[].createdMilliseconds	Created Milliseconds	Required. Safe integer.
notifications[].read	Read	Required. Boolean.
notifications[].readAtMilliseconds	Read At Milliseconds	Required. Safe integer. or Null.
unreadCount	Unread Count	Required. Safe integer.
categoryCounts	Category Counts	Required. Array of Object; no unknown keys.; minimum items 0; maximum items 128.
categoryCounts[].label	Caller-facing text label; not a globally unique identifier.	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 128.
categoryCounts[].count	Requested count; the mechanics explain whether one draw expands into several returned records.	Required. Safe integer.
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": {
    "templates": [
      {
        "category": "updates",
        "text": "A fictional file changed."
      },
      {
        "category": "social",
        "text": "A fictional invitation arrived."
      },
      {
        "category": "system",
        "text": "A fictional task finished."
      }
    ],
    "count": 2,
    "startMilliseconds": 1000,
    "endMilliseconds": 5000,
    "readProbability": 0.7,
    "seed": 42
  },
  "output": {
    "notifications": [
      {
        "id": "notification-1",
        "category": "social",
        "text": "A fictional invitation arrived.",
        "createdMilliseconds": 2793,
        "read": false,
        "readAtMilliseconds": null
      },
      {
        "id": "notification-2",
        "category": "system",
        "text": "A fictional task finished.",
        "createdMilliseconds": 1699,
        "read": true,
        "readAtMilliseconds": 2601
      }
    ],
    "unreadCount": 1,
    "categoryCounts": [
      {
        "label": "social",
        "count": 1
      },
      {
        "label": "system",
        "count": 1
      }
    ],
    "randomness": {
      "seed": 42,
      "source": "seed"
    }
  }
}

Limitations and assumptions

Unread entries have null readAtMilliseconds. These are synthetic timestamps and messages; no delivery, permission, persistence, or real inbox access occurs.
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 Notification Inbox Dataset Generator — tool.io

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