Random URL Path Segment Corpus Generator

Description

Construct encoded synthetic path segments and retain WHATWG dot normalization and empty-segment parser expectations.

A protocol fixture is local test data representing headers, messages, identifiers, or request decisions. Serialization and parsing can be checked without contacting a server, while authentication, delivery, and actual client behavior require separate tests.

Construct encoded synthetic path segments and retain WHATWG dot normalization and empty-segment parser expectations.

When to use this tool

Use this generator to create reproducible url path segment corpus 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 baseUrl, segments, segmentCount, count 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 cases. Use the conventions below and keep answer-bearing fields separate when presenting an exercise.

Draw raw path segments, URI-encode each, join with slash and construct an HTTP(S) URL from the base origin. Normalize with WHATWG parsing and delegate segment extraction while retaining the raw path and original segments.^[1]

Delegated operations used for this result: url path segments. Their calculation or parsing conventions apply to the corresponding result fields.^[2]

Input field	Meaning and units	Accepted input
baseUrl	Base Url	Required. Text; maximum UTF-16 length 65536.
segments	Segments	Required. Array of Text; maximum UTF-16 length 65536.; minimum items 1; maximum items 16.
segmentCount	Segment Count	Required. Safe integer; minimum 1; maximum 16.
count	Requested count; the mechanics explain whether one draw expands into several returned records.	Required. Safe integer; minimum 1; 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
cases	Cases	Required. Array of Object; no unknown keys.; minimum items 1; maximum items 32.
cases[].sourceSegments	Source Segments	Required. Array of Text; maximum UTF-16 length 65536.; minimum items 0; maximum items 16.
cases[].rawPath	Raw Path	Required. Text; maximum UTF-16 length 65536.
cases[].url	Url	Required. Text; maximum UTF-16 length 65536.
cases[].normalizedSegments	Normalized Segments	Required. Array of Text; maximum UTF-16 length 65536.; minimum items 0; maximum items 17.
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": {
    "baseUrl": "https://example.com/",
    "segments": [
      "a b",
      ""
    ],
    "segmentCount": 2,
    "count": 1,
    "seed": 42
  },
  "output": {
    "cases": [
      {
        "sourceSegments": [
          "",
          "a b"
        ],
        "rawPath": "//a%20b",
        "url": "https://example.com//a%20b",
        "normalizedSegments": [
          "",
          "a%20b"
        ]
      }
    ],
    "randomness": {
      "seed": 42,
      "source": "seed"
    }
  }
}

Limitations and assumptions

Encoded expansion is bounded. Dot-segment normalization and empty segments can change the parsed path; the generator does not access the URL or infer a filesystem path.
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 URL Path Segment Corpus Generator — tool.io
Calculation or validation: web/url-path-segments — tool.io

Similar or alternative tools

Random URL Credential Redaction Corpus Generator
Construct synthetic credential URLs, extract encoded members and strip complete userinfo from normalized HTTP(S) URLs.
Random URL Fragment Routing Fixture Generator
Construct supplied query and fragment combinations with encoded, empty and absent fragment controls and delegated hash expectations.