Description
Choose supplied prerequisite alternatives for fictional courses with bounded nonuniform DAG search and retained curriculum levels; no accreditation claims.
Worldbuilding fixtures describe an invented setting through supplied entities and explicit relations. A reproducible arrangement can support games or writing exercises while keeping constructed history and geography separate from factual claims about the real world.
Choose supplied prerequisite alternatives for fictional courses with bounded nonuniform DAG search and retained curriculum levels; no accreditation claims.
When to use this tool
Use this generator to create reproducible fictional school course map 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 courses 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 courses, order, componentCount, fictional. Use the conventions below. Keep answer-bearing fields separate when presenting an exercise.
Choose one prerequisite-option set per course using bounded randomized backtracking. Accept only acyclic combined choices under topological sorting, then compute each course level as one plus the largest prerequisite level, with zero for no prerequisites.1
Delegated operations used for this result: topological sort. Their calculation or parsing conventions apply to the corresponding result fields.2
| Input field | Meaning and units | Accepted input |
|---|---|---|
| courses | Courses | Required. Array of Object; no unknown keys.; minimum items 1; maximum items 16. |
| courses[].id | Literal identifier used independently of display labels. | Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 64. |
| courses[].prerequisiteOptions | Prerequisite Options | Required. Array of Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 64.; minimum items 0; maximum items 4.; minimum items 1; maximum items 4. |
| 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 |
|---|---|---|
| courses | Courses | Required. Array of Object; no unknown keys.; minimum items 1; maximum items 16. |
| courses[].id | Literal identifier used independently of display labels. | Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 64. |
| courses[].prerequisites | Prerequisites | Required. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 64.; minimum items 0; maximum items 4. |
| courses[].level | Level | Required. Safe integer; minimum 0; maximum 15. |
| order | Order | Required. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 64.; minimum items 1; maximum items 16. |
| componentCount | Component Count | Required. Safe integer; minimum 1; maximum 16. |
| fictional | Fictional | Required. Boolean; exactly true. |
| 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": {
"courses": [
{
"id": "basics",
"prerequisiteOptions": [
[]
]
},
{
"id": "runes",
"prerequisiteOptions": [
[
"basics"
]
]
},
{
"id": "gates",
"prerequisiteOptions": [
[
"runes"
],
[
"basics"
]
]
}
],
"seed": 42
},
"output": {
"courses": [
{
"id": "basics",
"prerequisites": [],
"level": 0
},
{
"id": "runes",
"prerequisites": [
"basics"
],
"level": 1
},
{
"id": "gates",
"prerequisites": [
"runes"
],
"level": 2
}
],
"order": [
"basics",
"runes",
"gates"
],
"componentCount": 1,
"fictional": true,
"randomness": {
"seed": 42,
"source": "seed"
}
}
}Limitations and assumptions
- The first feasible prerequisite selection is not uniform over all course maps. References must exist; the output is a fictional dependency plan rather than credential, workload, or educational-outcome validation.
- 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
Similar or alternative tools
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