Description
Generate rooted trees within explicit depth/branching capacities, reject provably infeasible sizes and retain parent/depth tables verified by breadth-first traversal.
A graph uses vertices and edges to represent relationships. Direction, duplicate handling, indexing, and traversal order affect its interpretation; returning a constructed graph together with a witness or calculated answer helps verify an algorithm.
Generate rooted trees within explicit depth/branching capacities, reject provably infeasible sizes and retain parent/depth tables verified by breadth-first traversal.
When to use this tool
Use this generator to create reproducible rooted tree depth profile 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 nodes, maximumDepth, maximumChildren 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 nodes, edges, parents, depths, degrees. Use the conventions below and keep answer-bearing fields separate when presenting an exercise.
Check theoretical tree capacity, then attach each later input node to a sampled earlier node with depth and child capacity remaining. Return aligned parents and depths and verify depths through breadth-first traversal from the first node.1
Delegated operations used for this result: breadth first traversal. Their calculation or parsing conventions apply to the corresponding result fields.2
| Input field | Meaning and units | Accepted input |
|---|---|---|
| nodes | Nodes | Required. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 64.; minimum items 1; maximum items 32. |
| maximumDepth | Maximum Depth | Required. Safe integer; minimum 0; maximum 31. |
| maximumChildren | Maximum Children | Required. Safe integer; minimum 0; maximum 31. |
| 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 |
|---|---|---|
| nodes | Nodes | Required. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 64.; minimum items 1; maximum items 32. |
| edges | Edges | Required. Array of Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 64.; minimum items 2; maximum items 2.; minimum items 0; maximum items 31. |
| parents | Parents | Required. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 64. or Null.; minimum items 1; maximum items 32. |
| depths | Depths | Required. Array of Safe integer.; minimum items 1; maximum items 32. |
| degrees | Degrees | Required. Array of Safe integer.; minimum items 1; 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.
{
"input": {
"nodes": [
"a",
"b",
"c",
"d"
],
"maximumDepth": 2,
"maximumChildren": 2,
"seed": 42
},
"output": {
"nodes": [
"a",
"b",
"c",
"d"
],
"edges": [
[
"a",
"b"
],
[
"a",
"c"
],
[
"c",
"d"
]
],
"parents": [
null,
"a",
"a",
"c"
],
"depths": [
0,
1,
1,
2
],
"degrees": [
2,
1,
2,
1
],
"randomness": {
"seed": 42,
"source": "seed"
}
}
}Limitations and assumptions
- maximumDepth and maximumChildren are upper bounds rather than an exact depth profile. The first node is the root with null parent; sequential attachment is not uniform over labeled trees.
- 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
Similar or alternative tools
- Random Labeled Tree Topology Generator
Generate recursive labeled trees by attaching each later supplied ID uniformly to an earlier ID, retaining degrees and connectivity; this is not uniform over labeled trees.
- Random Minimax Game Tree Test Case Generator
Generate a bounded complete fixed-branching game tree with seeded integer leaf utilities, retain preorder node IDs and portable tree JSON, and delegate alternating minimax alpha–beta evaluation; pruning counts are skipped immediate child branches, not skipped leaves or a game-playing guarantee.