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Random Selector Specificity Quiz Generator

Compose selectors from caller templates and safe identifiers and return delegated specificity triples for supported syntax.

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Description

Compose selectors from caller templates and safe identifiers and return delegated specificity triples for supported syntax.

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.

Compose selectors from caller templates and safe identifiers and return delegated specificity triples for supported syntax.

When to use this tool

Use this generator to create reproducible selector specificity quiz 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 templates, typeNames, classNames, idNames, 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 questions. Use the conventions below and keep answer-bearing fields separate when presenting an exercise.

Expand supplied selector templates with sampled type, class, and ID names. Preflight every template for unresolved braces and a single accepted selector, then delegate specificity calculation for each generated question.1

Delegated operations used for this result: selector specificity. Their calculation or parsing conventions apply to the corresponding result fields.2

Input fieldMeaning and unitsAccepted input
templatesTemplatesRequired. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 512.; minimum items 1; maximum items 32.
typeNamesType NamesRequired. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 64.; minimum items 1; maximum items 32.
classNamesClass NamesRequired. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 64.; minimum items 1; maximum items 32.
idNamesId NamesRequired. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 64.; minimum items 1; maximum items 32.
countRequested count; the mechanics explain whether one draw expands into several returned records.Required. Safe integer; minimum 1; maximum 64.
seedOptional numeric seed; takes precedence over context randomness. Without either, use the fixed tool.io default seed.Optional. Safe integer.
Output fieldInterpretationReturned shape
questionsQuestionsRequired. Array of Object; no unknown keys.; minimum items 1; maximum items 64.
questions[].selectorSelectorRequired. Text; maximum UTF-16 length 1024.
questions[].specificitySpecificityRequired. Object; no unknown keys.
questions[].specificity.idsIdsRequired. Safe integer; minimum 0.
questions[].specificity.classesClassesRequired. Safe integer; minimum 0.
questions[].specificity.typesTypesRequired. Safe integer; minimum 0.
randomnessReplay 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.seedOptional numeric 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": {
    "templates": [
      "{type}.{class}#{id}:hover",
      ":where(#{id}) {type}.{class}"
    ],
    "typeNames": [
      "article",
      "button"
    ],
    "classNames": [
      "card",
      "active"
    ],
    "idNames": [
      "hero",
      "main"
    ],
    "count": 2,
    "seed": 42
  },
  "output": {
    "questions": [
      {
        "selector": ":where(#main) article.active",
        "specificity": {
          "ids": 0,
          "classes": 1,
          "types": 1
        }
      },
      {
        "selector": "button.card#main:hover",
        "specificity": {
          "ids": 1,
          "classes": 2,
          "types": 1
        }
      }
    ],
    "randomness": {
      "seed": 42,
      "source": "seed"
    }
  }
}

Limitations and assumptions

  • Specificity inherits the linked parser's supported selector grammar. The tool neither matches a DOM nor resolves cascade layers, importance, or complete CSS precedence.
  • 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

  1. Tool behavior and example: Random Selector Specificity Quiz Generator — tool.io

  2. Calculation or validation: css/selector-specificity — tool.io

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