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Random CSV Control Character Audit Fixture Generator

Insert caller-selected tab, line-break, DEL or NEL controls at sampled UTF-16 offsets and retain exact lexical audits, including preexisting controls; this does not certify security.

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Description

Insert caller-selected tab, line-break, DEL or NEL controls at sampled UTF-16 offsets and retain exact lexical audits, including preexisting controls; this does not certify security.

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.

Insert caller-selected tab, line-break, DEL or NEL controls at sampled UTF-16 offsets and retain exact lexical audits, including preexisting controls; this does not certify security.

When to use this tool

Use this generator to create reproducible csv control character audit 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

  1. Supply fragments, codePoints, count in the field shapes below. Set seed when you need an explicit replay.
  2. 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.
  3. Read cases. Use the conventions below. Keep answer-bearing fields separate when presenting an exercise.

Sample a fragment, a UTF-16 insertion offset, and a supplied control code point. Insert it literally and delegate the field control-character audit, retaining original, mutated text, position, and code point.1

Delegated operations used for this result: control character finder in fields. Their calculation or parsing conventions apply to the corresponding result fields.2

Input fieldMeaning and unitsAccepted input
fragmentsFragmentsRequired. Array of Text; maximum UTF-16 length 64.; minimum items 1; maximum items 16.
codePointsCode PointsRequired. Array of Safe integer; one of 9, 10, 13, 127, 133.; minimum items 1; maximum items 5.
countCountRequired. Safe integer; minimum 1; maximum 16.
seedOptional numeric seed; takes precedence over context randomness. Without either, use the fixed tool.io default seed.Optional. Safe integer.
Output fieldInterpretationReturned shape
casesCasesRequired. Array of Object; no unknown keys.; minimum items 0; maximum items 16.
cases[].originalOriginalRequired. Text; maximum UTF-16 length 64.
cases[].mutatedMutatedRequired. Text; maximum UTF-16 length 65.
cases[].offsetOffsetRequired. Safe integer; minimum 0; maximum 64.
cases[].codePointCode PointRequired. Safe integer; one of 9, 10, 13, 127, 133.
cases[].auditAuditRequired. Object; no unknown keys.
cases[].audit.matchesMatchesRequired. Array of Object; no unknown keys..
cases[].audit.matches[].cellCellRequired. Safe integer.
cases[].audit.matches[].offsetOffsetRequired. Safe integer.
cases[].audit.matches[].codePointCode PointRequired. Safe integer.
randomnessReplay source and normalized 32-bit seed, or null seed for an advancing context source.Required. Object; no unknown keys.
randomness.seedOptional safe-integer replay seed; normalization and precedence are explained below.Required. Safe integer. or Null.
randomness.sourceSourceRequired. 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": {
    "fragments": [
      "ab",
      "cd"
    ],
    "codePoints": [
      9,
      127
    ],
    "count": 1,
    "seed": 42
  },
  "output": {
    "cases": [
      {
        "original": "cd",
        "mutated": "c\u007fd",
        "offset": 1,
        "codePoint": 127,
        "audit": {
          "matches": [
            {
              "cell": 0,
              "offset": 1,
              "codePoint": 127
            }
          ]
        }
      }
    ],
    "randomness": {
      "seed": 42,
      "source": "seed"
    }
  }
}

Limitations and assumptions

  • Insertion offsets count UTF-16 units and can fall inside a surrogate pair. Returned text is test data that should be escaped when displayed; the audit is not a CSV sanitizer or a rule to delete every control character.
  • 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

  1. Tool behavior and example: Random CSV Control Character Audit Fixture Generator — tool.io

  2. Calculation or validation: csv/control-character-finder-in-fields — tool.io

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