Random LFU Cache Tie Break Trace Generator

Description

Plant an equal-frequency eviction tie when capacity is at least two; capacity one is an explicit single-candidate eviction control. Retain FIFO, LRU or lexical choices and resident counts that reset after eviction.

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.

When to use this tool

Use this generator to create reproducible lfu cache tie break 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 keys, capacity, extraRequests, tiePolicy 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 requests, events, counts. Use the conventions below and keep answer-bearing fields separate when presenting an exercise.

Start with capacity plus one distinct shuffled requests to force an equal-frequency eviction situation, then append extra sampled requests. Evict a resident with the smallest resident frequency, breaking ties lexically, by insertion time, or by recency as selected.^[1]

Input field	Meaning and units	Accepted input
keys	Keys	Required. Array of Text; maximum UTF-16 length 64.; minimum items 2; maximum items 16.
capacity	Capacity	Required. Safe integer; minimum 1; maximum 8.
extraRequests	Extra Requests	Required. Safe integer; minimum 0; maximum 32.
tiePolicy	Tie Policy	Required. Text; one of "fifo", "lru", "lexicographic".
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
requests	Requests	Required. Array of Text; maximum UTF-16 length 64.; minimum items 0; maximum items 41.
events	Events	Required. Array of Object; no unknown keys.; minimum items 0; maximum items 41.
events[].key	Key	Required. Text; maximum UTF-16 length 64.
events[].hit	Hit	Required. Boolean.
events[].evicted	Evicted	Required. Text; maximum UTF-16 length 64. or Null.
events[].tieCandidates	Tie Candidates	Required. Array of Text; maximum UTF-16 length 64.; minimum items 0; maximum items 8.
events[].residents	Residents	Required. Array of Object; no unknown keys.; minimum items 0; maximum items 8.
events[].residents[].key	Key	Required. Text; maximum UTF-16 length 64.
events[].residents[].count	Requested count; the mechanics explain whether one draw expands into several returned records.	Required. Safe integer; minimum 1; maximum 41.
counts	Counts	Required. Array of Object; no unknown keys.; minimum items 0; maximum items 16.
counts[].key	Key	Required. Text; maximum UTF-16 length 64.
counts[].count	Requested count; the mechanics explain whether one draw expands into several returned records.	Required. Safe integer; minimum 1; maximum 41.
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": {
    "keys": [
      "a",
      "b",
      "c"
    ],
    "capacity": 2,
    "extraRequests": 1,
    "tiePolicy": "fifo",
    "seed": 42
  },
  "output": {
    "requests": [
      "c",
      "a",
      "b",
      "c"
    ],
    "events": [
      {
        "key": "c",
        "hit": false,
        "evicted": null,
        "tieCandidates": [],
        "residents": [
          {
            "key": "c",
            "count": 1
          }
        ]
      },
      {
        "key": "a",
        "hit": false,
        "evicted": null,
        "tieCandidates": [],
        "residents": [
          {
            "key": "c",
            "count": 1
          },
          {
            "key": "a",
            "count": 1
          }
        ]
      },
      {
        "key": "b",
        "hit": false,
        "evicted": "c",
        "tieCandidates": [
          "c",
          "a"
        ],
        "residents": [
          {
            "key": "a",
            "count": 1
          },
          {
            "key": "b",
            "count": 1
          }
        ]
      },
      {
        "key": "c",
        "hit": false,
        "evicted": "a",
        "tieCandidates": [
          "a",
          "b"
        ],
        "residents": [
          {
            "key": "b",
            "count": 1
          },
          {
            "key": "c",
            "count": 1
          }
        ]
      }
    ],
    "counts": [
      {
        "key": "c",
        "count": 2
      },
      {
        "key": "a",
        "count": 1
      },
      {
        "key": "b",
        "count": 1
      }
    ],
    "randomness": {
      "seed": 42,
      "source": "seed"
    }
  }
}

Limitations and assumptions

Frequency resets to one on reinsertion; global request counts differ from resident counts. Cache capacity must be smaller than the key bank, and the trace is sequential rather than concurrent.
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 LFU Cache Tie Break Trace Generator — tool.io

Similar or alternative tools

Random LRU Cache Request Trace Generator
Generate bounded key bursts with declared previous-burst locality probability and retain least-to-most-recent cache snapshots, hits, evictions and exact global request counts.
Random Priority Queue Operation Trace Generator
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.