Description
Construct shuffled tie-heavy key rows with original ordinals and compare the core's stable UTF-16 sort against a deliberately reversed-within-ties ordering.
CSV stores records as delimited text fields. Quoting can protect embedded delimiters and newlines, so a record need not equal one physical line. Cleaning field contents, interpreting their types, and preserving an exact import/export round trip are separate operations.
Construct shuffled tie-heavy key rows with original ordinals and compare the core's stable UTF-16 sort against a deliberately reversed-within-ties ordering.
When to use this tool
Use this generator to create reproducible csv sort stability exercise 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 keys, rowCount 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 rows, stableOrdinals, unstableOrdinals, stableCsv. Use the conventions below. Keep answer-bearing fields separate when presenting an exercise.
Include each distinct key at least once, add enough repeated keys, shuffle, and assign source ordinals. Delegate ascending lexical stable sorting and construct a contrasting order that reverses ordinals within key ties.1
Delegated operations used for this result: sort rows column lexicographic. Their calculation or parsing conventions apply to the corresponding result fields.2
| Input field | Meaning and units | Accepted input |
|---|---|---|
| keys | Keys | Required. Array of Text; maximum UTF-16 length 64.; minimum items 1; maximum items 16. |
| rowCount | Row Count | Required. Safe integer; minimum 2; 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 |
|---|---|---|
| rows | Rows | Required. Array of Object; no unknown keys.; minimum items 0; maximum items 32. |
| rows[].key | Key | Required. Text; maximum UTF-16 length 64. |
| rows[].ordinal | Ordinal | Required. Safe integer; minimum 0; maximum 31. |
| stableOrdinals | Stable Ordinals | Required. Array of Safe integer; minimum 0; maximum 31.; minimum items 0; maximum items 32. |
| unstableOrdinals | Unstable Ordinals | Required. Array of Safe integer; minimum 0; maximum 31.; minimum items 0; maximum items 32. |
| stableCsv | Stable Csv | Required. Text; maximum UTF-16 length 100000. |
| 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": {
"keys": [
"b",
"a"
],
"rowCount": 3,
"seed": 42
},
"output": {
"rows": [
{
"key": "b",
"ordinal": 0
},
{
"key": "a",
"ordinal": 1
},
{
"key": "a",
"ordinal": 2
}
],
"stableOrdinals": [
1,
2,
0
],
"unstableOrdinals": [
2,
1,
0
],
"stableCsv": "key,ordinal\na,1\na,2\nb,0",
"randomness": {
"seed": 42,
"source": "seed"
}
}
}Limitations and assumptions
- rowCount must exceed key-bank size to ensure a repeated key. Stable order refers to original ordinal positions and lexical comparison, not numeric or locale-aware collation.
- 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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