Random Priority Queue Operation Trace Generator

Description

Generate insert, existing-heap-slot update and extract-min operations on a binary heap with explicit insertion-age ties, heap snapshots and empty-operation controls.

An operation trace pairs an ordered request stream with the state after each step. Empty operations, ties, evictions, and boundary indexes are part of the modeled contract rather than incidental display details.

Generate insert, existing-heap-slot update and extract-min operations on a binary heap with explicit insertion-age ties, heap snapshots and empty-operation controls.

When to use this tool

Use this generator to create reproducible priority queue operation trace 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 initialPriorities, operations, eventCount, minimumPriority, maximumPriority, tieBreak 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 events, finalHeap. Use the conventions below and keep answer-bearing fields separate when presenting an exercise.

Maintain a binary min-heap with insertion IDs, sampling insert, update, and extract operations. Equal priorities use oldest or newest ID as specified. Updates preserve IDs and rebuild the heap; return snapshots and cross-check each minimum against numeric sorting.^[1]

Input field	Meaning and units	Accepted input
initialPriorities	Initial Priorities	Required. Array of Safe integer.; minimum items 0; maximum items 16.
operations	Operations	Required. Array of Text; one of "insert", "update", "extract".; minimum items 1; maximum items 3.
eventCount	Event Count	Required. Safe integer; minimum 1; maximum 64.
minimumPriority	Minimum Priority	Required. Safe integer.
maximumPriority	Maximum Priority	Required. Safe integer.
tieBreak	Tie Break	Required. Text; one of "oldest", "newest".
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
events	Events	Required. Array of Object; no unknown keys.; minimum items 0; maximum items 64.
events[].kind	Kind	Required. Text; one of "insert", "update", "extract".
events[].entry	Entry	Required. Object; no unknown keys. or Null.
events[].missing	Missing	Required. Boolean.
events[].heap	Heap	Required. Array of Object; no unknown keys.; minimum items 0; maximum items 80.
events[].heap[].id	Literal identifier used to match records, independently of their display labels.	Required. Safe integer; minimum 0; maximum 79.
events[].heap[].priority	Priority	Required. Safe integer.
finalHeap	Final Heap	Required. Array of Object; no unknown keys.; minimum items 0; maximum items 80.
finalHeap[].id	Literal identifier used to match records, independently of their display labels.	Required. Safe integer; minimum 0; maximum 79.
finalHeap[].priority	Priority	Required. Safe integer.
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": {
    "initialPriorities": [
      2
    ],
    "operations": [
      "insert",
      "update",
      "extract"
    ],
    "eventCount": 3,
    "minimumPriority": 0,
    "maximumPriority": 3,
    "tieBreak": "oldest",
    "seed": 42
  },
  "output": {
    "events": [
      {
        "kind": "update",
        "entry": {
          "id": 0,
          "priority": 3
        },
        "missing": false,
        "heap": [
          {
            "id": 0,
            "priority": 3
          }
        ]
      },
      {
        "kind": "extract",
        "entry": {
          "id": 0,
          "priority": 3
        },
        "missing": false,
        "heap": []
      },
      {
        "kind": "insert",
        "entry": {
          "id": 1,
          "priority": 2
        },
        "missing": false,
        "heap": [
          {
            "id": 1,
            "priority": 2
          }
        ]
      }
    ],
    "finalHeap": [
      {
        "id": 1,
        "priority": 2
      }
    ],
    "randomness": {
      "seed": 42,
      "source": "seed"
    }
  }
}

Limitations and assumptions

Heap array order is not fully sorted order. Empty extract or update has null entry and missing true. Snapshot work is bounded, and this models sequential operations rather than concurrent scheduling.
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 Priority Queue Operation Trace Generator — tool.io

Similar or alternative tools

Random Queue Operation Trace Generator
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Random Stack Operation Trace Generator
Generate sampled push, pop and peek operations with bottom-to-top LIFO snapshots, explicit empty-stack underflows and a delegated top-first final view.